Citations

AimsThe aim of this study was to compare the early clinical outcomes of robotically-assisted total knee arthroplasty (RA-TKA) and manual total knee arthroplasty (M-TKA), using daily remote patient monitoring.MethodsWe prospectively enrolled and compared patients who underwent 95 RA-TKAs with those who underwent 114 M-TKAs. All patients used an activity monitor and a patient engagement platform for two weeks preoperatively and 90 days postoperatively to collect daily visual analogue scale (VAS) pain scores, opioid consumption (in morphine milligram equivalents (MMEs)), step counts, weekly Oxford Knee Scores (OKSs), and monthly Forgotten Joint Scores (FJS). There were no significant differences between groups in sex or BMI. Patients in the RA-TKA group were significantly younger (mean age 63 vs 65 years; p = 0.006). Independent-samples t-tests, chi-squared tests, and Fisher’s exact tests were used for statistical analysis.ResultsRA-TKA led to significantly decreased pain (mean VAS 3.6 vs 4.2; p = 0.011) and significantly reduced opioid consumption in the first seven days postoperatively (a mean of 10 less MMEs per day; p < 0.001) compared with M-TKA. The RA-TKA group stopped taking opioids six days sooner (mean 24 days vs 30 days; p = 0.041). There were no significant differences in the number of days before stopping the use of walking aids (mean 31 days vs 35 days; p = 0.091). Patients in the RA-TKA group had significantly increased OKSs for the first five weeks (p = 0.013). There were no significant differences in the FJSs at all times or in OKSs beyond five weeks. There were no significant differences in the operating times (p = 0.405), step counts (p = 0.642), or complications (p = 0.222) between the groups.ConclusionThe use of robotic assistance in TKA led to significant improvements in pain, opioid consumption, and OKSs compared with manual instrumentation in the early recovery after primary TKA.Cite this article: Bone Joint J 2025;107-B(10):1054–1063.

Of the thousands of genes and substrates identified in KRAS-mutant signaling networks in pancreatic ductal adenocarcinoma (PDAC), more than 200 are transcription factors, implying extensive and complex transcriptional regulation. However, we observed that genetic suppression of the transcription factor MYC alone was sufficient to phenocopy the effect of KRAS suppression in signaling, growth, and metabolic processes in PDAC cells. We determined the gene transcription changes caused by acute suppression of MYC function in KRAS -mutant PDAC cell lines and performed dependency map and pathway analyses on the affected gene sets. The expression of 1685 genes was increased upon suppression of MYC, and this gene set may comprise the bulk of the MYC-regulated genes essential for PDAC growth. In contrast, the 1325 genes whose expression was inhibited may comprise a compensatory response to oncogenic stress, mediated in part by the GTPase RHO. MYC-dependent transcriptional activity was largely ERK dependent, and almost one-third of ERK-regulated genes were also regulated by MYC in PDAC cells. Furthermore, chemical proteomic profiling revealed MYC-regulated protein kinases that can be targeted therapeutically. Together, these data provide a molecular portrait of MYC-dependent signaling that encompasses potentially exploitable mechanisms for treating PDAC.

ABSTRACTSurgical biopsy of brainstem tumors carries a risk of neurological injury. We performed magnetic resonance spectroscopy (MRS) of 2‐hydroxyglutarate (2HG) and glycine in patients with brainstem tumors to assess the feasibility of detecting and quantifying 2HG in the brainstem to obviate the need for a diagnostic biopsy and to establish the clinical significance of glycine MRS in brainstem tumors in vivo. Twenty adult patients with radiographically identified presumed brainstem gliomas were prospectively enrolled in the study. Proton MRS was obtained at 3T with a protocol tailored for detection of 2HG and glycine (TE 97‐ms PRESS). Spectra were fit using LCModel software and in‐house basis signals of metabolites and lipids. The metabolite concentrations were quantified with reference to water and examined with respect to clinical outcomes, including postgadolinium MRI and overall survival time. MRS data from 19 patients were included in subsequent analysis, excluding suboptimal data from one patient. Tumors with elevated 2HG (> 1.9 mM, N = 8) and undetectable 2HG (< 0.3 mM, N = 11) were clearly distinguishable. Tumors with elevated glycine (> 1.5 mM, N = 4) showed rapid progression. Kaplan–Meier survival analyses with metabolite measures demonstrated that tumors with 2HG higher than 1.0 mM were significantly associated with a favorable prognosis (p = 0.01). In contrast, tumors with glycine higher than 2.5 mM showed a strong association with poor survival (p = 0.0005). The data confirm detection of 2HG in brainstem tumors at a concentration that is consistent with an IDH mutation and expected good prognosis, whereas elevated glycine in brainstem tumors portends rapid tumor progression and a worse prognosis.

Background and Aims: Cholangiocarcinoma (CCA) is one of the most lethal cancers, characterized by molecular heterogeneity and treatment resistance. To uncover new biological signals and therapeutic opportunities, we employed multiomic characterization combined with machine learning. Approach and Results: We profiled all anatomical CCA subtypes using whole exome sequencing, mRNA sequencing, and proteome/phosphoproteome analysis. Integrative dimensional reduction revealed RNA, protein, and phosphoprotein features driving tumor heterogeneity, enabling clustering. Machine learning algorithms identified molecular features for each cluster and mapped external datasets and patient-derived xenograft (PDX) models onto these clusters. Kinase enrichment analysis highlighted targetable kinases active in each cluster. In vivo validation was performed in cluster-specific PDX models using the selective TNK1 inhibitor, TP-5801. We identified 3 molecular clusters with distinct pathway characterization: immunomodulatory (cluster 1), metabolic (cluster 2), and gene regulation/cellular fate (cluster 3). Cluster assignment was independent of anatomic subtype but correlated with overall survival following curative-intent resection. We also identified multiomic features and pathways linked to overall survival and lymph node metastases, crucial for patient treatment selection. Kinase enrichment analysis pinpointed TNK1 as a highly active kinase in the metabolic cluster. Treatment with TP-5801 significantly reduced tumor growth in a metabolic PDX model, but not in models representing the other clusters. Combining internal data with publicly available datasets, we identified the immunomodulatory cluster as most responsive to gemcitabine/cisplatin therapy, confirmed in vivo using cluster-specific PDX models. Conclusions: Integrated multiomic characterization provides translational insights by defining unique molecular subtypes associated both with therapeutic response and overall clinical outcomes. This approach identified TNK1 as a previously unrecognized therapeutic target in a defined subset of CCA tumors.

Background/Objectives: Multi-cancer detection (MCD) tests have emerged as a promising tool to redefine the landscape of early cancer detection. Implementation of this novel technology will likely fall to primary care clinicians (PCC). The purpose of this study is to characterize and explore differences in PCCs perceptions and preferences towards MCD testing. Methods: Between March and May of 2023, this cross-sectional survey was administered to 281 PCCs, including physicians and advanced care providers practicing within an integrated healthcare system spanning five states. The survey collected data on self-reported characteristics, perceptions of MCD testing, and preferences for learning about MCD testing. Analysis was limited to those with no prior experience with MCD testing (N = 181, response rate 22.8%). Descriptive statistics summarized key variables and chi-square tests assessed differences in perceptions and preferences by key characteristics. Results: Most PCCs were interested in MCD testing (66.3%), but limited knowledge/awareness of MCD testing and confidence to manage patients with a positive test were observed, along with concerns around cost (76.7%) and misuse/poor implementation. The primary preferences for learning about MCD testing were online courses or classroom instruction (64.5%). Significant differences in perceptions and preferences for learning were observed by location, degree, and years in practice. Conclusions: PCCs in our study held positive views towards MCD testing, but gaps and variation in knowledge and confidence towards MCD testing and concerns around the cost and misuse/poor implementation were observed. While efforts to train and educate all PCCs on MCD testing is a critical first step, more research is needed to understand how best to support implementation tailored to individual and system-level needs and characteristics.

Abstract Introduction Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers. While total neoadjuvant therapy (TNT) has improved outcomes, recurrence rates remain high. Major pathologic response after TNT is prognostic of better survival, but is rarely achieved. Current pathologic systems primarily consider residual tumor percentage, nodal status, and perineural invasion but overlook spatial organization within the tumor microenvironment (TME). We aimed to evaluate spatial features of the TME to identify biologically and clinically relevant patterns of TME conformation and configuration after TNT and surgical resection of PDAC. Methods We retrospectively analyzed patients with PDAC treated with TNT followed by surgery at Mayo Clinic (2010-2022) with partial or no response per College of American Pathologists (CAP) criteria. Hematoxylin and eosin-stained whole slide images (WSIs) were processed using PathExplore™ PDAC (v1.0) to quantify spatial TME features. These were correlated with disease-free survival (DFS). Results A total of 203 patients were included: 47.3% female, median age 66.5 years. All received TNT; 73.4% had neoadjuvant chemotherapy followed by chemoradiation. Surgical procedures included pancreaticoduodenectomy (62.1%), distal pancreatectomy (22.2%), and total pancreatectomy (15.8%). CAP-defined response was partial in 82.1% and absent in 17.9%. As expected, pathologic T stage (p=0.001), N stage (p=0.002), lymphovascular invasion (p=0.048), and R2 resection (p=0.007) were significantly associated with DFS. However, CAP response category (p=0.053), residual cancer area (p=0.47), and cancer-to-stroma ratio (p=0.25) were not. We analyzed 297 WSIs from 203 patients. Of 31 spatial features evaluated, 5 were associated with DFS (p&lt;0.20). Recursive partitioning using ln(mean cancer shape index [CSI]) &lt;1.775 and ln(SD of stroma shape index [SSI]) &gt;0.651 identified a high-risk group (n=63) with median DFS of 7.23 months (95% CI: 5.19–9.63), compared to 11.57 months in the low-risk group (95% CI: 9.24–17.92) (HR=1.82; 95% CI: 1.31–2.52; p=0.0003). This remained significant after adjusting for T and N stage (HR=1.75; 95% CI: 1.17–2.63; p=0.007). An alternate prognostic index derived via backwards elimination, calculated using 0.2701(mean stromal area) + 0.3905(edge density), also stratified patients. High-risk patients (n=51) had a significantly shorter (p&lt;0.001) DFS (6.2 months) than those in the low-risk category (20.0 months). This significant difference holds in a multivariable analysis controlling for pathologic stage, N stage, and resection margins (HR=1.94, 95% CI: 1.21-3.10, p=0.006). Discussion Current assessment of residual PDAC after TNT is limited by subjective grading and lack of spatial context. Using Tumor Landscape Analysis, we identified high-risk spatial features of the TME that independently predict recurrence. These findings support a novel spatially-informed framework for risk stratification in resected PDAC with residual disease. Citation Format: Miranda Lin, Luis Cisneros, Merih D. Toruner, Andrea Maraone, Paul Dizona, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Spatial features of the tumor microenvironment predict recurrence risk in resected pancreatic ductal adenocarcinoma after total neoadjuvant therapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr A051.