Transcriptional Heterogeneity Overcomes Super-Enhancer Disrupting Drug Combinations in Multiple Myeloma.

Multiple myeloma (MM) is a malignancy that is often driven by MYC and that is sustained by IRF4, which are upregulated by super-enhancers. IKZF1 and IKZF3 bind to super-enhancers and can be degraded using immunomodulatory imide drugs (IMiD). Successful IMiD responses downregulate MYC and IRF4; however, this fails in IMiD-resistant cells. MYC and IRF4 downregulation can also be achieved in IMiD-resistant tumors using inhibitors of BET and EP300 transcriptional coactivator proteins; however, in vivo these drugs have a narrow therapeutic window. By combining IMiDs with EP300 inhibition, we demonstrate greater downregulation of MYC and IRF4, synergistic killing of myeloma in vitro and in vivo, and an increased therapeutic window. Interestingly, this potent combination failed where MYC and IRF4 expression was maintained by high levels of the AP-1 factor BATF. Our results identify an effective drug combination and a previously unrecognized mechanism of IMiD resistance. SIGNIFICANCE: These results highlight the dependence of MM on IKZF1-bound super-enhancers, which can be effectively targeted by a potent therapeutic combination pairing IMiD-mediated degradation of IKZF1 and IKZF3 with EP300 inhibition. They also identify AP-1 factors as an unrecognized mechanism of IMiD resistance in MM. See related article by Neri, Barwick, et al., p. 56. See related commentary by Yun and Cleveland, p. 5. This article is featured in Selected Articles from This Issue, p. 4.

Assessment of artificial intelligence-based remote monitoring of clear aligner therapy: A prospective study.

INTRODUCTION: Artificial intelligence remote monitoring of clear aligner therapy has recently gained popularity. It uses deep learning algorithms on a patient's mobile smartphone to determine readiness to progress to the next aligner (ie, GO vs NO-GO) and identify areas in which the teeth are not tracking with the clear aligners. This study aimed to assess the repeatability of the Go or No-Go instructions provided by the application and to determine the 3-dimensional discrepancies that constitute an unseat. METHODS: Thirty patients in treatment with clear aligners at an academic clinic were scanned twice using a remote monitoring application on a smartphone, and the results were compared. Gauge repeatability and reproducibility analysis were performed. Intraoral and remote monitoring scans were obtained on the same day from 24 additional clear aligner patients that completed treatment using their final aligners. The intraoral scan after using the final aligner and the stereolithography file of the planned position at the final aligner was compared with measure the maximum discrepancies between the actual and planned position of the teeth. RESULTS: Gauge compatibility of 44.7% was noted. In total 83.3% of patient instructions agreed between Scan 1 and 2, but 0% agreed completely on which and/or how many teeth had tracking issues. Patients who received GO instruction had mean greatest discrepancies of 1.997 mm, 1.901 mm, 0.530 mm, 8.911°, 7.827°, and 7.049° in mesiodistal, buccolingual, occlusogingival, tip, torque, and rotational dimensions, respectively. These discrepancies were not significantly different from patients receiving NO-GO instruction (1.771 mm, 1.808 mm, 0.606 mm, 8.673°, 8.134°, and 6.719° for the corresponding categories). CONCLUSIONS: Despite the study's limitations, these findings suggest concerns with the consistency of remote monitoring instructions because of gauge compatibility over the industry standard. Similarly, large discrepancies in tooth position for patients receiving GO and NO-GO instruction suggest that artificial intelligence decisions were inconsistent with quantitative findings.

Comparison of Contributing Risk Factors for Primary Tooth Caries in Down Syndrome and Non-Special Health Needs Children.

Purpose: To evaluate decayed, missing, and filled surfaces in primary teeth (dmfs) in Down syndrome subjects (DS) compared to typically developed (TD) controls using analysis. Methods: A retrospective study of 440 matched subjects (220 DS and 220 TD) was conducted. Categorical variables were evaluated for association with dental caries, with mean dmfs as the main outcome measure. Pearson's chi-square and independent sample t-tests for unequal variances for means were employed. Results: Overall, the TD control group was found to have significantly higher mean dmfs scores than the DS group: TD Equals 17.65 (mean dmfs), 95% confidence interval (CI) equals 15.48 to 19.90; DS equals 10.30 (mean dmfs), at 95% CI equals 7.96 to 12.78, (P<0.001). However, when controlled for the variable factors African American status (P=0.11), Hispanic status (P=0.07) and income level at or below 200 percent of poverty level (P=0.24) there was no significant difference in mean dmfs. Conclusions: In the study population DS and TD exhibited dissimilar dmfs scores, while when taking into consideration social and economic factors dmfs was equivalent. Caries risk factors modulate disease experience and should be considered in all population-specific studies. Patients with multiple high-risk factors should be treated as such, regardless of DS status.