Citations

Context.— In 2018 the College of American Pathologists Diagnostic Immunology and Flow Cytometry Committee designed and implemented a new plasma cell neoplasia flow cytometry proficiency testing program—PCNEO—to allow clinical flow cytometry laboratories to monitor and assess their performance compared with a peer group. Objective.— To report the results from the first 4 years of the PCNEO program. Design.— Program participants were sent 2 sets of challenges per year, each including 1 wet challenge and 2 dry challenges, with associated clinical and laboratory findings. The wet challenges were composed of myeloma cell line specimens (with or without dilution in preserved whole blood) for flow cytometric analysis. The dry (paper) challenges were composed of clinical case summaries and images of flow cytometric test results from various flow cytometry laboratories of committee members. Results.— A total of 116 to 145 laboratories from 17 countries enrolled in the proficiency testing program. For the wet challenges, almost all participants (97%–100%; cumulative, 98.2%) correctly identified the presence of neoplastic plasma cell populations based on flow cytometric analysis of undiluted myeloma cell lines. Slightly fewer participants (89.0%–97.4%; cumulative, 95.2%) correctly identified the presence of neoplastic plasma cell populations based on flow cytometric analysis of diluted myeloma cell lines (10% or 50% dilutions into peripheral blood) intended to better represent a typical clinical sample. There was generally agreement among 80% or more of participants for positive or negative staining for CD38, CD138, CD19, CD20, and surface and cytoplasmic κ and λ light chains. Similarly, 84% to 100% of participants were able to correctly identify the presence of neoplastic plasma cell populations in paper challenges, including the presence of small, neoplastic plasma cell populations (0.01%–5.0% clonal plasma cells) and the presence of nonneoplastic plasma cell populations (correctly identified by 91%–96% of participants). Conclusions.— Participant performance in the new proficiency testing program was excellent overall, with the vast majority of participants able to perform flow cytometric analysis and identify neoplastic plasma cell populations and to identify small plasma cell clones or expanded populations of reactive plasma cells in dry challenge flow cytometry results. This program will allow laboratories to verify the accuracy of their testing program and test interpretations for the assessment of patients suspected of having a plasma cell neoplasm.

Abstract 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

Background. When a partial liver graft is unable to meet the demands of the recipient, a clinical phenomenon, small-for-size syndrome (SFSS), may ensue. Clear definition, diagnosis, and management are needed to optimize transplant outcomes. Methods. A Consensus Scientific committee (106 members from 21 countries) performed an extensive literature review on specific aspects of SFSS, recommendations underwent blinded review by an independent panel, and discussion/voting on the recommendations occurred at the Consensus Conference. Results. The ideal graft-to-recipient weight ratio of ≥0.8% (or graft volume standard liver volume ratio of ≥40%) is recommended. It is also recommended to measure portal pressure or portal blood flow during living donor liver transplantation and maintain a postreperfusion portal pressure of <15 mm Hg and/or portal blood flow of <250 mL/min/100 g graft weight to optimize outcomes. The typical time point to diagnose SFSS is the postoperative day 7 to facilitate treatment and intervention. An objective 3-grade stratification of severity for protocolized management of SFSS is proposed. Conclusions. The proposed grading system based on clinical and biochemical factors will help clinicians in the early identification of patients at risk of developing SFSS and institute timely therapeutic measures. The validity of this newly created grading system should be evaluated in future prospective studies.

AbstractBackgroundAccurate and efficient dose calculation is essential for on‐line adaptive planning in proton therapy. Deep learning (DL) has shown promising dose prediction results in photon therapy. However, there is a scarcity of DL‐based dose prediction methods specifically designed for proton therapy. Successful dose prediction method for proton therapy should account for more challenging dose prediction problems in pencil beam scanning proton therapy (PBSPT) due to its sensitivity to heterogeneities.PurposeTo develop a DL‐based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on‐line adaptive proton therapy clinical decision and subsequent replanning.MethodsPBSPT plans of 103 prostate cancer patients (93 for training and the other 10 for independent testing) and 83 lung cancer patients (73 for training and the other 10 for independent testing) previously treated at our institution were included in the study, each with computed tomography scans (CTs), structure sets, and plan doses calculated by the in‐house developed Monte‐Carlo dose engine (considered as the ground truth in the model training and testing). For the ablation study, we designed three experiments corresponding to the following three methods: (1) Experiment 1, the conventional region of interest (ROI) (composed of targets and organs‐at‐risk [OARs]) method. (2) Experiment 2, the beam mask (generated by raytracing of proton beams) method to improve proton dose prediction. (3) Experiment 3, the sliding window method for the model to focus on local details to further improve proton dose prediction. A fully connected 3D‐Unet was adopted as the backbone. Dose volume histogram (DVH) indices, 3D Gamma passing rates with a criterion of 3%/3 mm/10%, and dice coefficients for the structures enclosed by the iso‐dose lines between the predicted and the ground truth doses were used as the evaluation metrics. The calculation time for each proton dose prediction was recorded to evaluate the method's efficiency.ResultsCompared to the conventional ROI method, the beam mask method improved the agreement of DVH indices for both targets and OARs and the sliding window method further improved the agreement of the DVH indices (for lung cancer, CTV D98 absolute deviation: 0.74 ± 0.18 vs. 0.57 ± 0.21 vs. 0.54 ± 0.15 Gy[RBE], ROI vs. beam mask vs. sliding window methods, respectively). For the 3D Gamma passing rates in the target, OARs, and BODY (outside target and OARs), the beam mask method improved the passing rates in these regions and the sliding window method further improved them (for prostate cancer, targets: 96.93% ± 0.53% vs. 98.88% ± 0.49% vs. 99.97% ± 0.07%, BODY: 86.88% ± 0.74% vs. 93.21% ± 0.56% vs. 95.17% ± 0.59%). A similar trend was also observed for the dice coefficients. This trend was especially remarkable for relatively low prescription isodose lines (for lung cancer, 10% isodose line dice: 0.871 ± 0.027 vs. 0.911 ± 0.023 vs. 0.927 ± 0.017). The dose predictions for all the testing cases were completed within 0.25 s.ConclusionsAn accurate and efficient deep learning‐augmented proton dose prediction framework has been developed for PBSPT, which can predict accurate dose distributions not only inside but also outside ROI efficiently. The framework can potentially further reduce the initial planning and adaptive replanning workload in PBSPT.

Abstract Microglia-mediated neuroinflammation contributes to acute demyelination in neuromyelitis optica spectrum disorders (NMOSD). Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in the CSF has been associated with microglial activation in several neurodegenerative diseases. However, the basis for this immune-mediated attack and the pathophysiological role of sTREM2 in NMOSD remain to be elucidated. Here, we performed Mendelian randomization analysis and identified a genetic association between increased CSF sTREM2 and NMOSD risk. CSF sTREM2 was elevated in patients with NMOSD and was positively correlated with neural injury and other neuroinflammation markers. Single-cell RNA sequencing of human macrophage/microglia-like cells in CSF, a proxy for microglia, showed that increased CSF sTREM2 was positively associated with microglial dysfunction in patients with NMOSD. Furthermore, we demonstrated that sTREM2 is a reliable biomarker of microglial activation in a mouse model of NMOSD. Using unbiased transcriptomic and lipidomic screens, we identified that excessive activation, overwhelmed phagocytosis of myelin debris, suppressed lipid metabolism and enhanced glycolysis underlie sTREM2-mediated microglial dysfunction, possibly through the nuclear factor kappa B (NF-κB) signalling pathway. These molecular and cellular findings provide a mechanistic explanation for the genetic association between CSF sTREM2 and NMOSD risk and indicate that sTREM2 could be a potential biomarker of NMOSD progression and a therapeutic target for microglia-mediated neuroinflammation.

Gene fusions involving tumor protein p63 gene (TP63) occur in multiple T and B cell lymphomas and portend a dismal prognosis for patients. The function and mechanisms of TP63 fusions remain unclear, and there is no target therapy for patients with lymphoma harboring TP63 fusions. Here, we show that TP63 fusions act as bona fide oncogenes and are essential for fusion-positive lymphomas. Transgenic mice expressing TBL1XR1::TP63, the most common TP63 fusion, develop diverse lymphomas that recapitulate multiple human T and B cell lymphomas. Here, we identify that TP63 fusions coordinate the recruitment of two epigenetic modifying complexes, the nuclear receptor corepressor (NCoR)—histone deacetylase 3 (HDAC3) by the N-terminal TP63 fusion partner and the lysine methyltransferase 2D (KMT2D) by the C-terminal TP63 component, which are both required for fusion-dependent survival. TBL1XR1::TP63 localization at enhancers drives a unique cell state that involves up-regulation of MYC and the polycomb repressor complex 2 (PRC2) components EED and EZH2. Inhibiting EZH2 with the therapeutic agent valemetostat is highly effective at treating transgenic lymphoma murine models, xenografts, and patient-derived xenografts harboring TP63 fusions. One patient with TP63 -rearranged lymphoma showed a rapid response to valemetostat treatment. In summary, TP63 fusions link partner components that, together, coordinate multiple epigenetic complexes, resulting in therapeutic vulnerability to EZH2 inhibition.

Objectives: This article describes key data sources and methods used to estimate hearing loss in the United States, in the Global Burden of Disease study. Then, trends in hearing loss are described for 2019, including temporal trends from 1990 to 2019, changing prevalence over age, severity patterns, and utilization of hearing aids. Design: We utilized population-representative surveys from the United States to estimate hearing loss prevalence for the Global Burden of Disease study. A key input data source in modeled estimates are the National Health and Nutrition Examination Surveys (NHANES), years 1988 to 2010. We ran hierarchical severity-specific models to estimate hearing loss prevalence. We then scaled severity-specific models to sum to total hearing impairment prevalence, adjusted estimates for hearing aid coverage, and split estimates by etiology and tinnitus status. We computed years lived with disability (YLDs), which quantifies the amount of health loss associated with a condition depending on severity and creates a common metric to compare the burden of disparate diseases. This was done by multiplying the prevalence of severity-specific hearing loss by corresponding disability weights, with additional weighting for tinnitus comorbidity. Results: An estimated 72.88 million (95% uncertainty interval (UI) 68.53 to 77.30) people in the United States had hearing loss in 2019, accounting for 22.2% (20.9 to 23.6) of the total population. Hearing loss was responsible for 2.24 million (1.56 to 3.11) YLDs (3.6% (2.8 to 4.7) of total US YLDs). Age-standardized prevalence was higher in males (17.7% [16.7 to 18.8]) compared with females (11.9%, [11.2 to 12.5]). While most cases of hearing loss were mild (64.3%, 95% UI 61.0 to 67.6), disability was concentrated in cases that were moderate or more severe. The all-age prevalence of hearing loss in the United States was 28.1% (25.7 to 30.8) higher in 2019 than in 1990, despite stable age-standardized prevalence. An estimated 9.7% (8.6 to 11.0) of individuals with mild to profound hearing loss utilized a hearing aid, while 32.5% (31.9 to 33.2) of individuals with hearing loss experienced tinnitus. Occupational noise exposure was responsible for 11.2% (10.2 to 12.4) of hearing loss YLDs. Conclusions: Results indicate large burden of hearing loss in the United States, with an estimated 1 in 5 people experiencing this condition. While many cases of hearing loss in the United States were mild, growing prevalence, low usage of hearing aids, and aging populations indicate the rising impact of this condition in future years and the increasing importance of domestic access to hearing healthcare services. Large-scale audiometric surveys such as NHANES are needed to regularly assess hearing loss burden and access to healthcare, improving our understanding of who is impacted by hearing loss and what groups are most amenable to intervention.

A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity—findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.

ImportancePatients should have an active role in decisions about pursuing or forgoing specific therapies in treatment de-escalation trials.ObjectiveTo evaluate longitudinal patient-reported outcomes (PROs) encompassing decisional comfort and health-related quality of life (HRQOL) among patients who elected to enroll in a clinical trial evaluating radiotherapy alone, without breast surgery, for invasive breast cancers with exceptional response to neoadjuvant systemic therapy (NST).Design, Setting, and ParticipantsProspective, single-group, phase 2 clinical trial at 7 US medical centers. Women aged 40 years or older with invasive cT1-2 N0-1 M0 triple-negative or human epidermal growth factor receptor 2 (ERBB2)–positive breast cancer with no pathologic evidence of residual disease following standard NST enrolled from March 6, 2017, to November 9, 2021. Validated PRO measures were administered at baseline and 6, 12, and 36 months post-radiotherapy. Data were analyzed from January to February 2023.InterventionsPRO measures included the Decision Regret Scale (DRS), Functional Assessment of Cancer Therapy—Lymphedema (FACT-B+4), and Breast Cancer Treatment Outcomes Scale (BCTOS).Main Outcomes and MeasuresChanges in PRO measure scores and subscores over time.ResultsAmong 31 patients, the median (IQR) age was 61 (56-66) years, 26 (84%) were White, and 26 (84%) were non-Hispanic. A total of 15 (48%) had triple-negative disease and 16 (52%) had ERBB2-positive disease. Decisional comfort was high at baseline (median [IQR] DRS score 10 [0-25] on a 0-100 scale, with higher scores indicating higher decisional regret) and significantly increased over time (median [IQR] DRS score at 36 months, 0 [0-20]; P &amp;lt; .001). HRQOL was relatively high at baseline (median [IQR] FACT-B composite score 121 [111-134] on a 0-148 scale, with higher scores indicating higher HRQOL) and significantly increased over time (median [IQR] FACT-B score at 36 months, 128 [116-137]; P = .04). Perceived differences between the affected breast and contralateral breast were minimal at baseline (median [IQR] BCTOS score 1.05 [1.00-1.23] on a 1-4 scale, with higher scores indicating greater differences) and increased significantly over time (median [IQR] BCTOS score at 36 months, 1.36 [1.18-1.64]; P &amp;lt; .001). At 36 months postradiotherapy, the cosmetic subscore was 0.45 points higher than baseline (95% CI, 0.16-0.74; P = .001), whereas function, pain, and edema subscores were not significantly different than baseline.Conclusions and RelevanceIn this nonrandomized phase 2 clinical trial, analysis of PROs demonstrated an overall positive experience for trial participants, with longitudinal improvements in decisional comfort and overall HRQOL over time and minimal lasting adverse effects of therapy.Trial RegistrationClinicalTrials.gov Identifier: NCT02945579

Abstract BACKGROUND Few methods exist via which to assess treatment response with high fidelity in gliomas. Cell-free DNA (cfDNA) is of growing interest as a liquid biomarker in plasma and CSF and has been used in other cancer types to optimize therapeutic regimens for individual patients. While CSF has previously been used as a source of cfDNA for gliomas, it remains unknown how cfDNA abundance and sequencing change throughout treatment and inevitable recurrence. To that end, we leveraged our growing biobank of longitudinal CSF specimens, acquired via CSF access devices, to determine the potential utility of CSF cfDNA as a monitoring tool for treatment response in patients with gliomas. MATERIAL AND METHODS Longitudinal CSF specimens were acquired via Ommaya reservoirs (NCT04692337) or ventriculoperitoneal shunts (NCT04692324) in patients with brain tumors, including gliomas. cfDNA was extracted from 1-5 mL of CSF based on available sample volumes and quantified via Qubit. Next-Generation sequencing (PredicineCARE) or low-pass whole genome sequencing (LPWGS) was performed by Predicine, Inc based on the amount of cfDNA available. RESULTS CSF acquired prior to versus after resection demonstrated an increase in quantified cfDNA (2.97x, range: 1.58-5.26x), consistent with the impact of increased parenchymal disruption and closer contact with CSF. Thereafter, CSF cfDNA continued to decrease throughout chemoradiation and adjuvant treatment and increased at recurrence, including in patients co-enrolled in immunotherapy trials for IL-7 agonists and pembrolizumab. Interestingly, copy number burden (CNB) increased by the time of recurrence in three patients with known disease progression, and continued to decrease throughout immunotherapy treatment in one patient despite concerns of pseudoprogression. In one patient with a hypermutated glioblastoma, CSF cfDNA revealed over 59 genomic alterations, including MAP2K1, KIT, and PDGFRA, and over 100 more variants of unknown significance, each of which had been detected in sequencing of the tissue acquired at resection and subsequently decreased with chemoradiation. In another patient with a known progressing EGFR-amplified GBM, over 200 new variants were identified by the patient’s final sample and EGFR copy number increased from 2 to over 30. CONCLUSION Analysis of cfDNA over a patient’s disease course, including resection and treatment with standard-of-care and experimental therapies, may be of use for disease monitoring and treatment response. Further work is needed to evaluate these findings in a larger cohort of patients and to determine the sensitivity of changes in mutations, CNB, and cfDNA quantity for glioma disease burden.