TRIM33 Is a Co-Regulator of Estrogen Receptor Alpha.

Estrogen receptor alpha (ER)-positive breast cancer is responsible for over 60% of breast cancer cases in the U.S. Among patients diagnosed with early-stage ER+ disease, 1/3 will experience recurrence despite treatment with adjuvant endocrine therapy. ER is a nuclear hormone receptor responsible for estrogen-driven tumor growth. ER transcriptional activity is modulated by interactions with coregulators. Dysregulation of the levels of these coregulators is involved in the development of endocrine resistance. To identify ER interactors that modulate transcriptional activity in breast cancer, we utilized biotin ligase proximity profiling of ER interactomes. Mass spectrometry analysis revealed tripartite motif containing 33 (TRIM33) as an estrogen-dependent interactor of ER. shRNA knockdown showed that TRIM33 promoted ER transcriptional activity and estrogen-induced cell growth. Despite its known role as an E3 ubiquitin ligase, TRIM33 increased the stability of endogenous ER in breast cancer cells. TRIM33 offers a novel target for inhibiting estrogen-induced cancer cell growth, particularly in cases of endocrine resistance driven by ER (ESR1) gene amplification or overexpression.

The role of cancer cell bioenergetics in dormancy and drug resistance.

While anti-cancer drug treatments are often effective for the clinical management of cancer, these treatments frequently leave behind drug-tolerant persister cancer cells that can ultimately give rise to recurrent disease. Such persistent cancer cells can lie dormant for extended periods of time, going undetected by conventional clinical means. Understanding the mechanisms that such dormant cancer cells use to survive, and the mechanisms that drive emergence from dormancy, is critical to the development of improved therapeutic strategies to prevent and manage disease recurrence. Cancer cells often exhibit metabolic alterations compared to their non-transformed counterparts. An emerging body of evidence supports the notion that dormant cancer cells also have unique metabolic adaptations that may offer therapeutically targetable vulnerabilities. Herein, we review mechanisms through which cancer cells metabolically adapt to persist during drug treatments and develop drug resistance. We also highlight emerging therapeutic strategies to target dormant cancer cells via their metabolic features.

Statistical determination of synergy based on Bliss definition of drugs independence.

Although synergy is a pillar of modern pharmacology, toxicology, and medicine, there is no consensus on its definition despite its nearly one hundred-year history. Moreover, methods for statistical determination of synergy that account for variation of response to treatment are underdeveloped and if exist are reduced to the traditional t-test, but do not comply with the normal distribution assumption. We offer statistical models for estimation of synergy using an established definition of Bliss drugs' independence. Although Bliss definition is well-known, it remains a theoretical concept and has never been applied for statistical determination of synergy with various forms of treatment outcome. We rigorously and consistently extend the Bliss definition to detect statistically significant synergy under various designs: (1) in vitro, when the outcome of a cell culture experiment with replicates is the proportion of surviving cells for a single dose or multiple doses, (2) dose-response methodology, (3) in vivo studies in organisms, when the outcome is a longitudinal measurement such as tumor volume, and (4) clinical studies, when the outcome of treatment is measured by survival. For each design, we developed a specific statistical model and demonstrated how to test for independence, synergy, and antagonism, and compute the associated p-value.