Targeting Unique Ligand Binding Domain Structural Features Downregulates DKK1 in Y537S ESR1 Mutant Breast Cancer Cells.

Resistance to endocrine therapies remains a major clinical hurdle in breast cancer. Mutations to estrogen receptor alpha (ERα) arise after continued therapeutic pressure. Next generation selective estrogen receptor modulators and degraders/downregulators (SERMs and SERDs) show clinical efficacy, but responses are often non-durable. A tyrosine to serine point mutation at position 537 in the ERα ligand binding domain (LBD) is among the most common and most pathogenic alteration in this setting. It enables endocrine therapy resistance by superceding intrinsic structural-energetic gatekeepers of ER hormone-dependence, it enhances metastatic burden by enabling neomorphic ER-dependent transcriptional programs, and it resists SERM and SERD inhibiton by reducing their binding affinities and abilities to antagonize transcriptional coregulator binding. However, a subset of SERMs and SERDs can achieve efficacy by adopting poses that force the mutation to engage in a new interaction that favors the therapeutic receptor antagonist conformation. We previously described a chemically unconventional SERM, T6I-29, that demonstrates significant anti-proliferative activities in Y537S ERα breast cancer cells. Here, we use a comprehensive suite of structural-biochemical, in vitro, and in vivo approaches to better T6I-29's activities in breast cancer cells harboring Y537S ERα. RNA sequencing in cells treated with T6I-29 reveals a neomorphic downregulation of DKK1, a secreted glycoprotein known to play oncogenic roles in other cancers. Importantly, we find that DKK1 is significantly enriched in ER+ breast cancer plasma compared to healthy controls. This study shows how new SERMs and SERDs can identify new therapeutic pathways in endocrine-resistant ER+ breast cancers.

Fragmentomic analysis of circulating tumor DNA-targeted cancer panels.

BACKGROUND: The isolation of cell-free DNA (cfDNA) from the bloodstream can be used to detect and analyze somatic alterations in circulating tumor DNA (ctDNA), and multiple cfDNA-targeted sequencing panels are now commercially available for Food and Drug Administration (FDA)-approved biomarker indications to guide treatment. More recently, cfDNA fragmentation patterns have emerged as a tool to infer epigenomic and transcriptomic information. However, most of these analyses used whole-genome sequencing, which is insufficient to identify FDA-approved biomarker indications in a cost-effective manner. PATIENTS AND METHODS: We used machine learning models of fragmentation patterns at the first coding exon in standard targeted cancer gene cfDNA sequencing panels to distinguish between cancer and non-cancer patients, as well as the specific tumor type and subtype. We assessed this approach in two independent cohorts: a published cohort from GRAIL (breast, lung, and prostate cancers, non-cancer, n = 198) and an institutional cohort from the University of Wisconsin (UW; breast, lung, prostate, bladder cancers, n = 320). Each cohort was split 70%/30% into training and validation sets. RESULTS: In the UW cohort, training cross-validated accuracy was 82.1%, and accuracy in the independent validation cohort was 86.6% despite a median ctDNA fraction of only 0.06. In the GRAIL cohort, to assess how this approach performs in very low ctDNA fractions, training and independent validation were split based on ctDNA fraction. Training cross-validated accuracy was 80.6%, and accuracy in the independent validation cohort was 76.3%. In the validation cohort where the ctDNA fractions were all <0.05 and as low as 0.0003, the cancer versus non-cancer area under the curve was 0.99. CONCLUSIONS: To our knowledge, this is the first study to demonstrate that sequencing from targeted cfDNA panels can be utilized to analyze fragmentation patterns to classify cancer types, dramatically expanding the potential capabilities of existing clinically used panels at minimal additional cost.

Autophagy in cancer metastasis.

Autophagy is a highly conserved self-degradative process that has a key role in cellular stress responses and survival. Recent work has begun to explore the function of autophagy in cancer metastasis, which is of particular interest given the dearth of effective therapeutic options for metastatic disease. Autophagy is induced upon progression of various human cancers to metastasis and together with data from genetically engineered mice and experimental metastasis models, a role for autophagy at nearly every phase of the metastatic cascade has been identified. Specifically, autophagy has been shown to be involved in modulating tumor cell motility and invasion, cancer stem cell viability and differentiation, resistance to anoikis, epithelial-to-mesenchymal transition, tumor cell dormancy and escape from immune surveillance, with emerging functions in establishing the pre-metastatic niche and other aspects of metastasis. In this review, we provide a general overview of how autophagy modulates cancer metastasis and discuss the significance of new findings for disease management.

Alternative restorative techniques of the CeraOne single-tooth abutment: a technical note.

The screw-joint stability of single-tooth implant-supported restorations has been shown to be significantly improved with an abutment system (CeraOne) that uses a gold-alloy screw tightened at a prescribed amount of torque. The abutment system requires the cementation of the restoration to the abutment. This negates the possibility of accessing the abutment screw when the removal of the restoration is desired. This article described two alternative restorative techniques to maintain accessibility to the screw joint.