Citations

Abstract Imatinib mesylate (IM) has revolutionized the treatment of gastrointestinal stromal tumor (GIST). However, most patients inevitably acquire IM resistance. Second- and third-line treatments exhibit modest clinical benefits with a median time to disease progression of 4 to 6 months, highlighting the urgency for novel therapeutic approaches. Here, we report that the expression of BCL6, a known oncogenic driver and transcriptional repressor, was significantly induced in GIST cells following IM treatment. Elevated BCL6 levels suppressed apoptosis and contributed to IM resistance. Mechanistically, BCL6 recruited SIRT1 to the TP53 promoter to modulate histone acetylation and transcriptionally repress TP53 expression. The reduction in p53 subsequently attenuated cell apoptosis and promoted tolerance of GIST cells to IM. Concordantly, treatment of GIST cells showing high BCL6 expression with a BCL6 inhibitor, BI-3802, conferred IM sensitivity. Furthermore, BI-3802 showed striking synergy with IM in IM-responsive and IM-resistant GIST cells in vitro and in vivo. Thus, these findings reveal a role for BCL6 in IM resistance and suggest that a combination of BCL6 inhibitors and IM could be a potentially effective treatment for GIST. Significance: BCL6 drives resistance to imatinib by inhibiting p53-mediated apoptosis and can be targeted in combination with imatinib to synergistically suppress tumor growth, providing a therapeutic strategy for treating gastrointestinal stromal tumor.

Abstract Motivation Analyzing the overlap between two sets of genomic intervals is a frequent task in the field of bioinformatics. Typically, this is accomplished by counting the number (or proportion) of overlapped regions, which applies an arbitrary threshold to determine if two genomic intervals are overlapped. By making binary calls but disregarding the magnitude of the overlap, such an approach often leads to biased, non-reproducible, and incomparable results. Results We developed the cobind package, which incorporates six statistical measures: the Jaccard coefficient, Sørensen–Dice coefficient, Szymkiewicz–Simpson coefficient, collocation coefficient, pointwise mutual information (PMI), and normalized PMI. These measures allow for a quantitative assessment of the collocation strength between two sets of genomic intervals. To demonstrate the effectiveness of these methods, we applied them to analyze CTCF’s binding sites identified from ChIP-seq, cancer-specific open-chromatin regions (OCRs) identified from ATAC-seq of 17 cancer types, and oligodendrocytes-specific OCRs identified from scATAC-seq. Our results indicated that these new approaches effectively re-discover CTCF’s cofactors, as well as cancer-specific and oligodendrocytes-specific master regulators implicated in disease and cell type development. Availability and implementation The cobind package is implemented in Python and freely available at https://cobind.readthedocs.io/en/latest/.

Abstract Medulloblastoma (MB) is a highly malignant childhood brain tumor comprising a collection of molecularly and clinically distinct entities. Mutations in chromatin-modifying genes distribute across subgroups and account for nearly half of all MBs. However, the molecular consequences of chromatin modifier alterations remain poorly understood. Herein, we characterize the chromatin landscape of fifty-two primary MBs representing each MB subgroup using chromatin immunoprecipitation followed by sequencing (ChIP-seq) for six histone marks and perform multi-layered integration with somatic genetics, genome-wide DNA methylation, and transcriptomic datasets extracted from the same tumors. Analysis of differential chromatin states across MB subgroups identified significant enrichment of a bivalent enhancer state (EnhBiv) in Group 4 MB. Group 4-specific EnhBivs mapped to promoters of key neurodevelopmental genes and transcription factors and was associated with increased DNA methylation and reduced expression. In accordance with higher EnhBivs coverage in Group 4 MB, we found that KDM2B, a H3K4me3 and H3K36me2 demethylase, is highly expressed in Group 4 MBs and patient-derived xenografts (PDXs). KDM2B knockout mediated by CRISPR targeting suppressed growth of both Group 3 MB cell lines in vitro and Group 4 MB PDXs in vivo but had no effect on control SHH-MB cells, suggesting that KDM2B is a novel selective dependency in MB. Knockout of KDM2B in MB cells induced profound upregulation of PRC2 targets, genes regulated by bivalent histone marks, as well as genes involved in neuronal differentiation. Further biochemical and molecular studies demonstrated that KDM2B interacts with PRC2 complex subunits and occupies gene promoters associated with Group 4-specific EnhBiv chromatin. In summary, our comprehensive characterization of the MB chromatin landscape in a large cohort of primary tumors provides novel insights into the epigenetic basis of MB and implicates KDM2B as a novel Group 4 MB dependency that should be prioritized as a therapeutic target in this subgroup.

Abstract Objective Social determinants of health (SDoH) play critical roles in health outcomes and well-being. Understanding the interplay of SDoH and health outcomes is critical to reducing healthcare inequalities and transforming a “sick care” system into a “health-promoting” system. To address the SDOH terminology gap and better embed relevant elements in advanced biomedical informatics, we propose an SDoH ontology (SDoHO), which represents fundamental SDoH factors and their relationships in a standardized and measurable way. Material and Methods Drawing on the content of existing ontologies relevant to certain aspects of SDoH, we used a top-down approach to formally model classes, relationships, and constraints based on multiple SDoH-related resources. Expert review and coverage evaluation, using a bottom-up approach employing clinical notes data and a national survey, were performed. Results We constructed the SDoHO with 708 classes, 106 object properties, and 20 data properties, with 1,561 logical axioms and 976 declaration axioms in the current version. Three experts achieved 0.967 agreement in the semantic evaluation of the ontology. A comparison between the coverage of the ontology and SDOH concepts in 2 sets of clinical notes and a national survey instrument also showed satisfactory results. Discussion SDoHO could potentially play an essential role in providing a foundation for a comprehensive understanding of the associations between SDoH and health outcomes and paving the way for health equity across populations. Conclusion SDoHO has well-designed hierarchies, practical objective properties, and versatile functionalities, and the comprehensive semantic and coverage evaluation achieved promising performance compared to the existing ontologies relevant to SDoH.

Abstract Purpose: Clinical trials reported 25% to 30% pathologic complete response (pCR) rates in HER2+ patients with breast cancer treated with anti-HER2 therapies without chemotherapy. We hypothesize that a multiparameter classifier can identify patients with HER2-“addicted” tumors who may benefit from a chemotherapy-sparing strategy. Experimental Design: Baseline HER2+ breast cancer specimens from the TBCRC023 and PAMELA trials, which included neoadjuvant treatment with lapatinib and trastuzumab, were used. In the case of estrogen receptor–positive (ER+) tumors, endocrine therapy was also administered. HER2 protein and gene amplification (ratio), HER2-enriched (HER2-E), and PIK3CA mutation status were assessed by dual gene protein assay (GPA), research-based PAM50, and targeted DNA-sequencing. GPA cutoffs and classifier of response were constructed in TBCRC023 using a decision tree algorithm, then validated in PAMELA. Results: In TBCRC023, 72 breast cancer specimens had GPA, PAM50, and sequencing data, of which 15 had pCR. Recursive partitioning identified cutoffs of HER2 ratio ≥ 4.6 and %3+ IHC staining ≥ 97.5%. With PAM50 and sequencing data, the model added HER2-E and PIK3CA wild-type (WT). For clinical implementation, the classifier was locked as HER2 ratio ≥ 4.5, %3+ IHC staining ≥ 90%, and PIK3CA-WT and HER2-E, yielding 55% and 94% positive (PPV) and negative (NPV) predictive values, respectively. Independent validation using 44 PAMELA cases with all three biomarkers yielded 47% PPV and 82% NPV. Importantly, our classifier's high NPV signifies its strength in accurately identifying patients who may not be good candidates for treatment deescalation. Conclusions: Our multiparameter classifier differentially identifies patients who may benefit from HER2-targeted therapy alone from those who need chemotherapy and predicts pCR to anti-HER2 therapy alone comparable with chemotherapy plus dual anti-HER2 therapy in unselected patients.

Objectives: Patients with unresectable hilar cholangiocarcinoma (hCCA) may be eligible for curative treatment through liver transplantation (LT). Neoadjuvant protocols often include radiotherapy (RT), however, there is no standard RT approach. The purpose of this study is to characterize practice patterns of RT use before transplantation for hCCA. Methods: A survey was administered to radiation oncologists practicing at LT centers identified through the U.S. Organ Procurement and Transplant Network and the International Cholangiocarcinoma Research Network. The survey consisted of 13 questions regarding RT details as well as approaches to systemic therapy. For cross-regimen comparison, the cumulative RT tumor dose was standardized using the EQD2 method. Results: Twenty-three centers utilizing neoadjuvant therapy for hCCA were identified. Most respondents (96%) use both chemotherapy and RT as part of their protocol. Elective nodal volumes commonly included the portal vein lymph nodes (91%) and celiac artery lymph nodes (70%). After an initial 45 Gy plan, a wide range of sequential boost regimens was used. The median cumulative dose including boosts to the gross disease was 58 Gy (EQD2) with a wide range of 40 to 110 Gy. Five (22%) include brachytherapy as part of their treatment plan. The majority (96%) used concurrent chemotherapy with fluoropyrimidines. Conclusions: These results suggest significant variability of neoadjuvant RT use for hCCA before LT. A wide range of doses and fractionation schemes are utilized with cumulative doses ranging from 40 to 110 Gy (EQD2). A further study evaluating the efficacy and toxicity of these various approaches is warranted to better inform best practices.

Transient ischemic attack (TIA) has gained significant attention recently due to the increased incidence of subsequent stroke. However, there are many nonvascular clinical mimics of TIA, creating a need for improved biomarkers to identify a vascular origin. Following the recent approval of ultra-high field (UHF) 7T MRI in clinical practice, several clinical studies have highlighted its added utility in neuroimaging compared to lower-field 1.5T and 3T MRI, particularly in epilepsy and multiple sclerosis. Our case series of three patients with TIA illustrates that 7T MRI can depict small areas of intracortical microhemorrhages and microinfarctions, which could not be resolved with 3T or 1.5T MRI. There are currently no reports of intracortical localization of microhemorrhages in patients with TIA. This discovery may enhance our understanding and characterization of cerebrovascular abnormalities in TIAs. In addition, UHF imaging could potentially be utilized to distinguish transient neurological episodes secondary to cerebrovascular events from other differential considerations. Our cases highlight the underestimation of imaging abnormalities in cases of TIA and support the potential expanded application of clinical 7T to assess patients with TIA. Future studies are necessary at 7T redundant to determine the true incidence of such lesions in TIA and to examine the correlation between cortical microhemorrhages and subsequent ischemic stroke, hemorrhagic events, and neurocognitive impairment.

Significance Statement Changes in albuminuria and GFR slope are individually used as surrogate end points in clinical trials of CKD progression, and studies have demonstrated that each is associated with treatment effects on clinical end points. In this study, the authors sought to develop a conceptual framework that combines both surrogate end points to better predict treatment effects on clinical end points in Phase 2 trials. The results demonstrate that information from the combined treatment effects on albuminuria and GFR slope improves the prediction of treatment effects on the clinical end point for Phase 2 trials with sample sizes between 100 and 200 patients and duration of follow-up ranging from 1 to 2 years. These findings may help inform design of clinical trials for interventions aimed at slowing CKD progression. Background Changes in log urinary albumin-to-creatinine ratio (UACR) and GFR slope are individually used as surrogate end points in clinical trials of CKD progression. Whether combining these surrogate end points might strengthen inferences about clinical benefit is unknown. Methods Using Bayesian meta-regressions across 41 randomized trials of CKD progression, we characterized the combined relationship between the treatment effects on the clinical end point (sustained doubling of serum creatinine, GFR <15 ml/min per 1.73 m 2 , or kidney failure) and treatment effects on UACR change and chronic GFR slope after 3 months. We applied the results to the design of Phase 2 trials on the basis of UACR change and chronic GFR slope in combination. Results Treatment effects on the clinical end point were strongly associated with the combination of treatment effects on UACR change and chronic slope. The posterior median meta-regression coefficients for treatment effects were −0.41 (95% Bayesian Credible Interval, −0.64 to −0.17) per 1 ml/min per 1.73 m 2 per year for the treatment effect on GFR slope and −0.06 (95% Bayesian Credible Interval, −0.90 to 0.77) for the treatment effect on UACR change. The predicted probability of clinical benefit when considering both surrogates was determined primarily by estimated treatment effects on UACR when sample size was small (approximately 60 patients per treatment arm) and follow-up brief (approximately 1 year), with the importance of GFR slope increasing for larger sample sizes and longer follow-up. Conclusions In Phase 2 trials of CKD with sample sizes of 100–200 patients per arm and follow-up between 1 and 2 years, combining information from treatment effects on UACR change and GFR slope improved the prediction of treatment effects on clinical end points.