Citations

Abstract The minichromosome maintenance 2-7 (MCM2-7) proteins form a hexameric protein complex that is the structural core of replicative helicase, which is essential for accurate DNA replication. While their role in replication is well-established, the biological functions of excess chromatin-bound MCM2-7 proteins remain unclear. Here, we identify a transcriptional regulatory function of MCM2-7 through its interaction with nuclear factor κB (NF-κB) p65. We demonstrate that MCM2-7 proteins and NF-κB p65 reciprocally recruit each other to target gene promoters. Consequently, MCM2-7 proteins facilitate the localization of RNA Pol II to NF-κB target gene promoters and along the gene body, thereby promoting transcription of NF-κB target genes. These findings reveal MCM2-7 proteins promote NF-κB target gene transcription by facilitating p65 and RNA Pol II recruitment, offering a potential avenue for fine-tuning NF-κB target gene transcription.

Sharing research code in an open access version-controlled repository offers significant benefits for both science as a whole and for individual researchers. In this article, we focus on this practice, which is fully aligned with the NIH’s Gold Standard Science (GSS) program as well as FAIR (findable, accessible, interoperable, reusable) and TRUST (transparency, responsibility, user focus, sustainability, technology) principles. Gold Standard Science supports open science by emphasizing transparency, reproducibility, and the use of best practices that enable others to verify and extend research. Pairing a research article’s cited data snapshot with a versioned, environment-specific code release, deposited in a companion code repository, ensures that, upon submission to a medical journal, readers and reviewers can directly verify results. An executable and updatable companion code repository complements, rather than replaces, established research data repositories. When code underlying medical research results is made openly available, then other scientists can inspect, run, and validate analyses. These activities enhance reproducibility, which is a core aim of GSS. Shared code also facilitates collaborative innovation by allowing researchers to extend the utility of the code to new datasets and applications. For researchers, code sharing can increase visibility, credibility, and citation impact. Demonstrating transparency through shared executable and updatable code builds trust with journal readers, peer reviewers, funders, and peers. Shared code in an open access repository signals adherence to high standards of scientific integrity and attracts opportunities for collaboration. A researcher who shares code receives recognition as a leader in reproducible, trustworthy research consistent with NIH’s GSS principles.

Abstract With the rapid advancements in large language model technology and the emergence of bioinformatics‐specific language models (BioLMs), there is a growing need for a comprehensive analysis of the current landscape, computational characteristics, and diverse applications. This survey aims to address this need by providing a thorough review of BioLMs, focusing on their evolution, classification, and distinguishing features, alongside a detailed examination of training methodologies, datasets, and evaluation frameworks. We explore the wide‐ranging applications of BioLMs in critical areas such as disease diagnosis, drug discovery, and vaccine development, highlighting their impact and transformative potential in bioinformatics. We identify key challenges and limitations inherent in BioLMs, including data privacy and security concerns, interpretability issues, biases in training data and model outputs, and domain adaptation complexities. Finally, we highlight emerging trends and future directions, offering valuable insights to guide researchers and clinicians toward advancing BioLMs for increasingly sophisticated biological and clinical applications.

Abstract Acute kidney injury (AKI) frequently follows hematopoietic cell transplantation (HCT). Soluble urokinase-type plasminogen activator receptor (suPAR) is a biomarker of AKI in the general population. We evaluated suPAR and its association with AKI requiring dialysis (AKI-D) in patients undergoing allogeneic HCT (alloHCT). Performance of suPAR was compared with serum creatinine (sCr) and neutrophil gelatinase-associated lipocalin (NGAL). Data were obtained from the Blood and Marrow Transplant Clinical Trials Network 1202 cohort, an observational study of 1709 alloHCT recipients. Adults aged ≥18 years with AKI-D after HCT were included. Adults who did not develop AKI were included as controls and matched 1:1. Periodic serum samples (7-90 days) were analyzed for NGAL, suPAR, and sCr. The 1:1 matched case-control groups (n = 62 each) were balanced in demographic variables, except for graft-versus-host disease prophylaxis. The median time from transplant to AKI-D was 2.6 months (range, 0.03-20.39). The day +7 suPAR level after HCT was higher in patients with AKI (median, 2.7 ng/mL) than in controls (2.1 ng/mL; P = .002). In the multivariate analysis, the day +7 suPAR level was associated with the development of AKI-D (P = .009). The area under the curve for the receiver operating characteristic curve for day +7 suPAR levels was 0.75. Neither NGAL nor sCr were associated with AKI-D. Elevated day +7 suPAR levels predicted AKI and lower overall survival (OS). The suPAR level at day +7 after HCT may be an early prognostic factor for the development of AKI-D and OS. Future prospective studies could evaluate this at different stages of AKI. This trial was registered at www.ClinicalTrial.gov as #NCT01879072.

Abstract Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significance Integration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

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.