Citations

Abstract Introduction: Surveillance biopsies after kidney transplantation provide an opportunity to assess early renal disease processes, including diabetic nephropathy, before clinical manifestation. This study aimed to identify proteomic alterations in renal allografts at 5 years post-transplant (5yrPT) and their associations with histologic features in diabetic/obese (DM/OB) versus non-diabetic/non-obese (nDM/nOB) recipients. Methods: We studied protocol biopsies from 17 DM/OB and 14 nDM/nOB kidney transplant recipients at Mayo Clinic (2000–2012). Laser capture microdissection followed by mass spectrometry was used for proteomic profiling. Histologic assessment included Banff and Tervaert scoring and morphometric analysis. Statistical comparisons were performed using ANOVA with Tukey post-hoc testing. Results: DM/OB recipients demonstrated greater histologic and metabolic injury at 5yrPT. Proteomic analysis identified 101 glomerular and 86 non-glomerular proteins differentially expressed between groups. Significant alterations were observed in proteins associated with mitochondrial dysfunction, including VDAC1 (fold change [FC] 2.6, p = 0.03), NDUFB9 (FC 0.15, p = 0.009), and NDUFA9 (FC 1.72, p = 0.01). Extracellular matrix remodeling proteins COL6A1, COL6A2, and COL6A3 were upregulated (FC 1.6–1.8, p < 0.05). Immune and inflammatory markers C9 (FC 1.6, p < 0.03) and TGFBI (FC 1.7, p < 0.001), as well as oxidative stress–related CLU, were increased. GGACT showed the greatest decrease (FC 0.30, p < 0.001), implicating altered energy metabolism. Conclusion: Distinct proteomic signatures at 5yrPT in DM/OB recipients highlight early mitochondrial, metabolic, immune, and extracellular matrix pathways involved in diabetic kidney disease. These changes precede clinical disease and identify candidate biomarkers and therapeutic targets to improve graft longevity.

ABSTRACT Aging reshapes the architecture of human skeletal muscle, yet objective tissue‐level markers that capture this process remain limited. We combined large‐scale histology with deep learning to identify reproducible features of muscle aging and to test their biological relevance. We analyzed 974 hematoxylin–eosin whole‐slide images from a population resource using a dual‐attention convolutional neural network and an independent Mask R‐CNN model to quantify nuclear size and density, verified by manual review. The classifier distinguished young from aged muscle with high accuracy (AUC 0.91; accuracy 86.2%), and attention maps consistently highlighted nuclear enlargement and spatial disorganization as salient features. Nuclear diameter increased with age (Spearman's ρ = 0.71, p < 0.0001) across automated and manual measurements. Transcriptomes matched to the same donors showed that samples with larger nuclei were enriched for pathways related to chromatin remodeling, proteostasis, cellular senescence, mitochondrial activity, and telomere regulation, whereas smaller nuclei aligned with anti‐inflammatory and DNA repair programs. External pediatric inflammatory myopathies exhibited nuclear enlargement comparable to aged muscle, suggesting inflammation‐related premature histologic aging. These findings identify nuclear enlargement as a robust, quantifiable feature that integrates structural and molecular signatures of muscle aging. The proposed deep learning–based nuclear morphometry provides a scalable framework for tissue‐level aging biomarkers and suggests a potential “muscle aging clock” applicable to both physiological aging and disease states.

The NCCN Guidelines for Melanoma: Cutaneous provide strategies for the diagnosis, treatment, and follow-up of patients with cutaneous melanoma, which is among the most common cancers in the United States. The outcome of cutaneous melanoma is significantly influenced by stage at initial presentation. Generally, localized disease and smaller primary tumors have been associated with more favorable prognosis. Thus, the select content featured in this issue focuses on risk factors associated with cutaneous melanoma development and which should be considered during an initial assessment. These include (1) phenotypic predispositions, (2) personal medical history or comorbidities, (3) genetic predispositions, and (4) environmental factors.

Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy characterized by the clonal expansion of myeloid blasts in the peripheral blood, bone marrow, and/or other tissues. It is the most common form of acute leukemia among adults and accounts for the largest number of annual deaths from leukemias in the United States. 1 The NCCN Guidelines Panel for AML convenes annually to update recommendations for the diagnosis and treatment of AML in adults. These recommendations are based on a review of recently published clinical trials that have led to significant improvements in treatment or have yielded new information regarding biologic factors that may have prognostic importance. These NCCN Guidelines Insights summarize the panel’s most recent recommendations regarding the monitoring and management of measurable (minimal) residual disease.

Ziftomenib - a potent, selective, oral menin inhibitor - is approved as monotherapy for adults with relapsed/refractory (R/R) NPM1-mutated acute myeloid leukemia (NPM1-m AML). The KOMET-007 phase 1 trial investigated clinical activity and tolerability of ziftomenib in combination with standard therapies for R/R and newly diagnosed AML. Here, we report outcomes of adults with R/R NPM1-m AML treated with ziftomenib plus venetoclax/azacitidine. In phase 1a, patients received ziftomenib 200, 400, or 600 mg once daily with standard doses of venetoclax/azacitidine. In phase 1b, ziftomenib 600 mg was selected for expansion. Sixty-seven patients were treated (27 phase 1a; 40 phase 1b). Median age was 66 years, and 55% were men. Median number of prior therapies was 1 (range 1-8); 55% received prior venetoclax and 22% had prior transplantation. Most common (≥20%) grade ≥3 treatment-emergent adverse events were leukopenia (34%), thrombocytopenia (28%), febrile neutropenia and neutropenia (25% each). Six patients developed QTc prolongation (1 ziftomenib-related; grade 1), and 2 experienced differentiation syndrome (grade 3); all events were successfully managed. In patients receiving ziftomenib 600 mg, composite complete remission (CRc) rate was 46% (22/48), with 67% (12/18) achieving central measurable residual disease (MRD) negativity (&lt;0.01% threshold). In venetoclax-naïve and -exposed patients, CRc rates were 70% (16/23) and 24% (6/25), with MRD-negativity rates of 75% (9/12) and 50% (3/6), respectively. Median duration of response was 8.6 months, and median overall survival was not reached. The combination of ziftomenib 600 mg with venetoclax/azacitidine was well tolerated with deep and durable clinical activity in R/R NPM1-m AML. This trial was registered at www.ClinicalTrials.gov as #NCT05735184.

Abstract Purpose Modeling relative biological effectiveness (RBE) is central to carbon ion radiotherapy treatment planning. The modified Microdosimetric Kinetic Model (mMKM) is a clinically established RBE framework that has guided treatment protocols at many existing carbon centers, while the Mayo Clinic Florida Microdosimetric Kinetic Model (MCF MKM) is a recently developed alternative. This work aims to implement the MCF MKM in the open‐source treatment planning system matRad and to quantitatively compare its RBE‐weighted dose predictions with those of the clinically established mMKM using identical physical dose distributions across multiple disease sites. These findings will help assess their dosimetric equivalence and inform protocol development for carbon ion radiotherapy at MCF. Methods Monte Carlo simulations of the MCF carbon beamline were performed to generate physical (IDD, LET, lateral spread) and biological base data for integration of each RBE model into matRad . Treatment plans were generated for six patients, each corresponding to a different disease site, using clinical beam configurations with carbon‐reference dose prescriptions, and plans were optimized using the MCF MKM. To isolate differences attributable solely to the RBE model, the resulting physical dose distributions were held fixed and RBE‐weighted doses were recalculated using the mMKM. Dose volume histogram (DVH) metrics and spatial dose‐difference maps were used to compare target coverage and organ‐at‐risk doses between the two models. Results Across patient cases, RBE‐weighted dose distributions from MCF MKM and mMKM showed strong agreement. Differences in target coverage were small, with CTV D95% differing by less than 1.6% across all disease sites and maximum target dose differences not exceeding 0.88%. Organ‐at‐risk dose deviations were limited, with differences of 3.0% or less across evaluated DVH metrics. Spatial dose‐difference maps showed that the largest discrepancies occurred in regions of steep dose gradients near target to organ‐at‐risk interfaces, while overall dose conformity and plan quality remained comparable between the two models. Conclusions: This study served as the first systematic model comparison of the MCF MKM and mMKM within a treatment planning environment. These findings suggest that the MCF MKM and mMKM produce dosimetrically consistent RBE‐weighted dose predictions under realistic planning conditions using carbon‐reference parameters. Accordingly, the fractionation schemes developed from years of clinical experience with mMKM implementations may serve as a practical foundation for protocol development at MCF.

Abstract Background Immune-related adverse events disrupt immune checkpoint inhibitor therapy and impact quality of life. Peripheral edema is common among patients with cancer, however the causality of peripheral edema can be unclear in the context of multidrug regimens. Methods PubMed/MEDLINE, Embase, and Web of Science were searched to identify phase 3 randomized controlled trials (RCTs) evaluating immune checkpoint inhibitors reporting peripheral edema incidence. The incidence of edema was calculated according to adverse event, immune checkpoint inhibitor, and treatment patterns. A random-effects meta-analysis pooled odds ratios (ORs) of edema incidence between immune checkpoint inhibitor and non–immune checkpoint inhibitor groups. A systematic review characterizing the interventions for immune-related peripheral edema was also conducted. Results From 58 RCTs (22 590 patients), treatment-related peripheral edema (grade 1-5) occurred in 2.80% (n = 195 of 6969) of patients receiving immune checkpoint inhibitor monotherapy, 4.96% (n = 112 of 2257) of patients receiving immune checkpoint inhibitor with chemotherapy, and 8.73% (n = 205 of 2349) of patients receiving immune checkpoint inhibitor with targeted therapy. Meta-analysis showed immune checkpoint inhibitor monotherapy had lower treatment-related peripheral edema incidence compared with chemotherapy (OR = 0.45, 95% CI = 0.27 to 0.73; P = .001, I2 = 69%) with the lowest relative incidence among programmed cell death protein 1 vs chemotherapy (OR = 0.41, 95% CI = 0.23 to 0.73; P = .003) and immune checkpoint inhibitor vs taxane chemotherapy (OR = 0.32, 95% CI = 0.18 to 0.58; P &lt; .001). A systematic review of treatment outcomes for immune-related peripheral edema among 40 patients (19 studies) revealed 82.5% (n = 33 of 40) of cases received glucocorticoid treatment, and immune checkpoint inhibitors were permanently discontinued in 35% (n = 14 of 40). Conclusions Peripheral edema is a rare but potentially serious adverse event associated with immune checkpoint inhibitors. Immune checkpoint inhibitors likely confer less peripheral edema risk than taxane therapy. To avoid unnecessary treatment interruptions, treatment discontinuation requires careful consideration, particularly when edema develops following immune checkpoint inhibitor combination therapy.