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Abstract BACKGROUND Whilst the broad clonal architecture of naturally progressing chronic lymphocytic leukemia (CLL) has been described, a comprehensive picture of how chemotherapy and targeted agents reshape that landscape is lacking. Here we integrate clone-specific growth kinetics with mutational profiles, transcriptomic subtypes, and CpG-methylation-based epigenetic classes to capture the multidimensional evolutionary responses of CLL under native conditions and during treatment. METHODS We previously reported a systematic whole-exome sequencing (WES) analysis of 417 leukemia–germline pairs from 169 treatment-naïve patients ≥ 65 y (Karisani et al., Blood 2024). The treatment arm comprised 83 patients who received ibrutinib and 39 who received chlorambucil in the RESONATE-2 trial (NCT01722487). Forty-seven age-matched “watch-and-wait” patients from the CLL Research Consortium served as untreated controls. Peripheral-blood samples were collected at baseline and again ~300 d and ~600 d after therapy initiation (or diagnosis in the watch-and-wait cohort), enabling longitudinal clonal tracking. WES data were processed with PhylogicNDT to reconstruct clonal architectures, define phylogenies, and identify significant clonal shifts. MutSig tools identified mutations enriched in expanding or contracting clones. Pretreatment RNA-sequencing profiles were grouped into transcriptional subtypes by consensus clustering based on the Louvain algorithm. Differentially methylated regions plus epitypes were called from reduced representation bisulfite sequencing data. RESULTS Across the 169 patients with WES, we resolved 579 subclonal clusters. Significant clonal shifts (defined as a distribution shift of cancer cell fraction in a subclone of >95% between two timepoints) were uncommon during watch-and-wait (36%) but markedly higher after therapy — chlorambucil 67% (q = 0.01), and ibrutinib 77% (q < 10-4). In ibrutinib-treated CLL, regressing subclones were enriched for KRAS (q<10-3) and SF3B1 mutations (q<10-3), whereas expanding subclones preferentially harboured mutations in BIRC3 (q<10-4), NOTCH1 (q <10-3), TP53 (q=0.02), and POT1 (q=0.098). In chlorambucil-treated patients, no specific mutations were found to be enriched in expanding or regressing subclones. Using the recently defined CLL expression clusters (ECs) in patients treated with chemoimmunotherapy as defined by Knisbacher et al. (Nat Genet 2022), we were unable to identify any relationship between ECs and outcomes. We therefore sought to identify de novo ECs with prognostic relevance in the context of BTK-inhibition (BTKi-ECs). We identified a transcriptionally defined patient subgroup (C4, n=20) associated with inferior progression-free survival (median PFS = 63 months, log-rank q=0.05), independent of known prognostic clinical and molecular features, including epitypes, in multivariate analysis (Cox HR=3.7, 95% CI: 1.6-8.6, q=0.02). Gene-set enrichment in this cluster highlighted TNF-ɑ signalling via NF-κB (REL, TNFAIP3, NFKB2) and G2M checkpoint pathways (SMC4, EZH2). We also identified a distinct transcriptionally defined patient subgroup (C3, n=18) that was enriched for patients harboring at least one contracting subclone and no expanding subclones (q=0.005). This cluster showed a relative depletion of mutations within the chromatin modification pathway (6% vs 50%, q<0.01). Gene-set enrichment in this cluster highlighted a downregulation of genes in the TNF-ɑ signalling via NF-κB pathway (SOCS3, ICOSLG, NFKB2). CONCLUSION BTK inhibition and chemotherapy drive distinct evolutionary trajectories in CLL. Multi-omics profiling reveals mutation-defined subclones with divergent sensitivity to targeted therapy and delineates two informative expression states: a high-risk NF-κB/inflammatory cluster (C4; poor PFS) and a cluster enriched with contracting subclones with depleted TNF-ɑ signalling via NF-κB (C3). Integrating clonal growth kinetics with genomic, transcriptomic, and methylation data can potentially identify patients likely to progress on BTK inhibitors and identify actionable pathways for adaptive or combination therapy.

Introduction Registrational trials are clinical trials which are used to justify regulatory approval of a new medication by the FDA. However, clinical trials may not be designed around patient-centred outcomes, like overall survival (OS) or quality of life. This disconnect raises concerns about whether current trial designs are truly aligned with the long-term needs and priorities of patients. A comprehensive analysis of trial designs and endpoints is necessary to ensure that future oncological therapies deliver meaningful clinical improvements. Our objective was to describe types of clinical trial design and primary endpoints used for registrational trials, and their trends over time. Research design and methods In this cohort study, the HemOnc database was used to identify registrational trials supporting cancer drug approval from 2004 through 2023. Clinical trial design (escalation, de-escalation, in-class switch, out-of-class switch) and primary endpoint (OS; time-to-event including progression-free survival; response-based endpoint) were characterized. Results Escalation trial designs were more common than in-class switches or out-of-class switches. De-escalation and mixed designs were exceedingly rare. The most common primary endpoint was a composite time-to-event endpoint. Conclusion Most clinical trials leading to FDA approval for cancer-directed therapies employ escalation designs with composite time-to-event endpoints. Designs reflecting paradigm shifts in therapy (in-class switches and out-of-class switches) are sparsely used. This approach raises the concern that trials may increase therapeutic toxicity without delivering meaningful improvements in OS or quality of life.

Objective To assess the impact of renal replacement therapy in people with lupus nephritis (LN)–associated end‐stage kidney disease (ESKD) and support the development of the 2024 American College of Rheumatology LN treatment guidelines. Methods We conducted a systematic literature review and meta‐analysis to address three Population, Intervention, Comparison, and Outcome (PICO) questions related to renal replacement therapy for ESKD due to LN, including comparisons of kidney transplant versus dialysis, hemodialysis versus peritoneal dialysis, and preemptive kidney transplant versus no preemptive kidney transplant. Outcomes of interest included mortality, cardiovascular (CV) events, infections, lupus flares, disease‐related damage, graft failure, and quality of life. We conducted a meta‐analysis and analyzed hazard ratios for time‐to‐event analyses and risk ratios for dichotomous outcomes, as well as absolute risk estimates. Results Sixteen comparative observational studies addressed at least one of the three PICO questions. Kidney transplant was found to reduce the risks of all‐cause mortality, CV mortality, infection‐related mortality, and CV events compared with dialysis (high certainty). Dialysis modality (peritoneal vs hemodialysis) was not associated with mortality (high certainty) or with other outcomes of infection, CV complications, and systemic lupus erythematosus flares (low certainty). Preemptive kidney transplant was associated with lower risks of graft failure and mortality (low certainty). Conclusion This systematic review identified improved outcomes with kidney transplant versus dialysis for people with LN‐associated ESKD and potential benefits of preemptive kidney transplant. This evidence supports the use of kidney transplant as a preferred renal replacement therapy for people with LN‐ESKD.

Abstract The progression of osteoarthritis (OA) is fundamentally characterized by the aberrant transformation of chondrocytes into a fibrotic phenotype, although the precise molecular mechanisms involved remain inadequately understood. In this study, the interplay between epigenetic modifications and metabolic reprogramming during the activation of fibrocartilage cells in osteoarthritis was investigated. The findings demonstrate that FSTL1 markedly upregulates key glycolytic enzymes, including LDHA, HK2, and PKM, in chondrocytes, triggering a “glycolytic burst” that results in elevated intracellular lactate levels. This accumulated lactate acts as a precursor for epigenetic modifications, specifically promoting the lactylation of histone H3 lysine 18 (H3K18la) in fibrocartilage cells, thereby facilitating the transcriptional activation of critical fibrosis‐related genes such as Itga6, Cxcl10, and Parp16. Notably, pharmacological inhibition of the PI3K/mTOR pathway or lactate dehydrogenase significantly diminishes H3K18la levels and markers of chondrocyte fibrosis, while exogenous lactate supplementation can counteract this effect. In summary, this study unveils the core mechanism by which FSTL1 reshapes the epigenetic landscape of chondrocytes and drives the fibrotic process through the activation of the “glycolysis‐lactate‐H3K18la” cascade axis, offering a dual‐target intervention strategy for OA involving metabolic reprogramming and epigenetic modification.

Abstract CDK12 is frequently deleted and/or mutated in human cancers, and CDK12 inactivation is associated with aggressive phenotypes, including the tendency to metastasis. In this study, we showed that CDK12 deficiency induced intronic polyadenylation (IPA) usage in BRD4 to upregulate expression of the bromodomain-containing protein 4 (BRD4) short isoform (BRD4S). BRD4S demonstrated an enhanced capacity to form phase separation despite lacking the intrinsically disordered region located in the C-terminal of full-length BRD4. Oligomerization of BRD4S mediated phase separation through a base-interacting structural domain. CUT&Tag and RNA sequencing analyses revealed that BRD4S preferentially bound to the promoters of TGFβ signaling genes, including TGFB2 and LTBP1, driving their expression. Consistently, BRD4S drove cancer cell dissemination in vitro and metastasis in vivo, which could be blocked by BET or TGFβ signaling pathway inhibitors. Overall, this study identifies IPA usage at the BRD4 gene locus induced by CDK12 deficiency as a mechanism responsible for BRD4S genesis, which represents an important mechanism driving cancer metastasis and a potential target for therapeutic intervention in CDK12-deficient cancers. Significance: The CDK12–BRD4S–TGFβ signaling axis represents a key regulatory module that promotes metastatic progression and can be targeted by BET or TGFβ pathway inhibitors for treating CDK12-deficient cancers.

Abstract Purpose This study investigates a novel optimization framework that integrates the newly developed MCF MKM relative biological effectiveness (RBE) model into intensity modulated particle therapy (IMPT) planning for carbon ion therapy. Unlike conventional RBE models such as MKM or LEM, the MCF MKM provides detailed microdosimetric information, which improves predictive accuracy of cell survival but elevates both memory and time requirement in the optimization process. Furthermore, to the implicit nature of the MCF MKM, the gradient information, which is essential in inverse planning, is hardly accessible. In response, a randomized gradient‐free optimization method (RGFM) was developed to mitigate the computational challenge and achieve improved RBE dose distributions. Materials and Methods An RBE dose optimization problem was formulated based on the discretized MCF MKM, known as the Abridged Microdosimetry Distribution Model (AMDM). The RGFM was derived to find feasible and high‐quality settings of monitor unit for IMPT plans without the need for explicit gradient calculations. To verify the clinical plausibility of the proposed method, it was tested on two clinical scenarios—prostate and brain cases in comparison with benchmark plans derived solely from physical dose optimization. Computational times and dose‐volume histograms (DVHs) for both physical and RBE doses were evaluated. Results The RGFM algorithm successfully optimized the MCF MKM‐based IMPT plans. Compared to the benchmark, the RBE dose distributions showed improved coverage of the target and reduced hot spots. Such improvements were observed to coincide with trade‐offs in physical dose distributions. The complexity of the MCF MKM extended the computational time, yet high‐quality solutions were attainable in a clinically reasonable timeframe. Multi‐field optimization (MFO) further enhanced target coverage and critical organ sparing over single‐field optimization (SFO). Conclusions This proof‐of‐principle study confirmed the feasibility of using a randomized gradient‐free method to optimize RBE dose based on the MCF MKM in IMPT planning for carbon ion therapy. The approach provides a pathway for clinical adoption of advanced RBE models, potentially leading to more biologically informed and effective carbon ion therapy treatments. Future work involves refining algorithms, incorporating parallel computing, and performing additional case studies to improve computational efficiency and generalizability.

Abstract Uterine leiomyosarcoma (ULMS) is an orphan disease that frequently recurs and metastasizes, with patients undergoing multiple lines of chemotherapy due to lack of effective therapeutic targets. To address this gap, we used single-cell RNA sequencing and spatial transcriptomic analysis to comprehensively profile ULMS. We uncovered multiple states of tumor cells, including tumor cells with mesenchyme-like features, ischemic tumor cells defined by a MYC program, inflammatory tumor cells with active interferon signaling, and stem cell-like hormone receptor-positive cells. The inferred spatial correlates of these tumor cell states demonstrated unique localization patterns. By correlating these signatures to bulk RNA sequencing data, we demonstrate the relevance of these findings to clinical outcomes. Finally, using the single-cell integration and drug response prediction algorithm (scIDUC), we propose drug predictions that may target specific tumor states. Our findings suggest new avenues for further exploration of individualized and multifaceted therapeutic strategies to treat ULMS.

Abstract Aims Activating transcription factor 4 (ATF4) functions as a transcriptional regulator in various cell types and tissues under both physiological and pathological conditions. While previous studies have linked ATF4 activation with promoting cardiomyocyte (CM) death in dilated cardiomyopathy (DCM), atrial fibrillation, and heart failure, its role in developing CMs remains unexplored. Methods and results We generated multiple distinct CM-specific (Atf4cKO(e2/3/pA) and Atf4cKO(e2)) and global Atf4 knockout (KO; Atf47del/7del and Atf41ins/1ins) mouse models targeting different Atf4 regions, as well as CM-specific deletion of Rps19bp1 to study cardiac phenotypes. Detailed morphological and molecular analyses were performed. Atf4cKO(e2/3/pA) [targeting exon 2–3 including the polyadenylation signal (polyA)] mice exhibited severe cardiac defects and died before E17.5, likely due to ectopic activation of the p53 signaling pathway resulting from Rps19bp1 downregulation, a potent suppressor of p53. Further investigation revealed that deleting the polyA signal of Atf4 in Atf4cKO(e2/3/pA) mice led to transcriptional readthrough, resulting in the formation of an Atf4-Cacna1i fusion transcript and Rps19bp1 downregulation. To avoid readthrough while abolishing ATF4 function, we introduced small indels into exon 3 of Atf4 in mice (Atf47del/7del and Atf41ins/1ins), which showed normal Rps19bp1 expression and cardiac morphology. Importantly, CM-specific deletion of Rps19bp1 recapitulated the cardiac defects and transcriptional change seen in Atf4cKO(e2/3/pA) mice. Conclusion We found that the downregulation of Rps19bp1, not the loss of ATF4 function, underlies the cardiac phenotypes in Atf4cKO(e2/3/pA) mice. The reduced expression of Rps19bp1 in Atf4cKO(e2/3/pA) mice is likely due to the unintentional deletion of Atf4 polyA signal and subsequent transcriptional readthrough, underscoring the essential role of RPS19BP1, not ATF4, in cardiac development. Consistent Rps19bp1 downregulation has been observed in other tissue-specific Atf4 KO models utilizing the Atf4fl(e2/3/pA) allele, suggesting that previously reported Atf4 KO phenotypes may result from Atf4 transcriptional readthrough effects. These findings reveal a locus-dependent transcriptional interference mechanism and emphasize the importance of avoiding confounding cis effects in genetically engineered models.

Abstract The brain avidly consumes glucose to fuel neurophysiology. Cancers of the brain, such as glioblastoma (GBM), relinquish physiological integrity and gain the ability to proliferate and invade healthy tissue. How brain cancers rewire glucose utilization to drive aggressive growth remains elusive. Here, we infused 13C-labeled glucose into patients and mice with brain cancer, coupled with quantitative metabolic flux analysis, to map the fates of glucose-derived carbon in tumor vs. cortex. Through the first direct and comprehensive measurements of carbon and nitrogen labeling in both cortex and glioma tissues, we uncover profound metabolic transformations. In human cortex, glucose carbons fuel essential physiologic processes including TCA cycle oxidation and neurotransmitter synthesis. Conversely, gliomas downregulate these processes and scavenge alternative carbon sources such as amino acids from the environment, repurposing glucose-derived carbons to generate molecules needed for proliferation and invasion. Targeting this metabolic rewiring in mice through dietary amino acid modulation selectively alters GBM metabolism, slows tumor growth, and augments the efficacy of standard-of-care treatments. These findings illuminate how aggressive brain tumors exploit glucose to suppress normal physiological activity in favor of malignant expansion and offer potential therapeutic strategies to enhance treatment outcomes.