Citations

PURPOSE To compare overall survival (OS) in patients with baseline metastatic gastric adenocarcinoma (GA) with and without ovarian metastasis (OM). Furthermore, within the group that had ovarian metastases, we aimed to assess whether there was a survival benefit (SB) with palliative oophorectomy (PO). PATIENTS AND METHODS This is a single-institution retrospective analysis of the clinicopathological features of women diagnosed with metastatic GA with a comparison of outcomes based on PO status. We identified 240 women with baseline metastatic GAs who were treated at MD Anderson Cancer Center between February 2003 and September 2022. Among these women, we categorized a subgroup of 102 women who had OM from their primary GA. Patients were analyzed whether they underwent PO. RESULTS Patients who developed OM were most often non-Caucasian, had peritoneal involvement, and had tumors that were both human epidermal growth factor receptor 2–negative and PD-L1–negative, with signet ring cell features and diffuse histological type. Among patients with ovarian metastases, those who had PO had an Eastern Cooperative Oncology Group = 0, more comprehensive molecular and immunohistochemical profiling, lower percentage of family history of gastroesophageal malignancies, and lower interval between diagnosis of the GA primary and the OM. PO was associated with significantly improved OS in this subgroup (hazard ratio, 0.5 [95% CI, 0.31 to 0.81]; P = .005). CONCLUSION To our knowledge, this is the largest multiethnic population study assessing SB of PO in patients with GA with OM. Additionally, it is the largest study analyzing survival in this population according to the patient's multiethnic characteristics and metastasis timing and growth patterns. PO presents as a therapeutic option for women with GAs with OM if the patient is clinically suitable for surgical resection.

Abstract Peptide receptor radionuclide therapy (PRRT) with lutetium-177-Dotatate (177Lu-DOTATATE) has transformed neuroendocrine tumor (NET) treatment, improving progression-free survival, symptom control, and quality of life. However, long-term hematologic toxicities, including therapy-related myeloid neoplasms (tMN), are increasingly recognized. These rare but severe complications, such as myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), appear multifactorial, influenced by prior cytotoxic therapies, radiation exposure, clonal hematopoiesis, and germline predispositions. This review synthesizes data on PRRT-related hematologic toxicities, including findings from pivotal studies and real-world evidence. We explore risk factors, underlying mechanisms, and the potential role of biomarkers, such as clonal hematopoiesis and germline mutations, in predicting toxicity. Emerging approaches, including alpha particle radioligand therapy and advanced dosimetry, are explored as strategies to optimize patient selection and minimize adverse outcomes. To maximize the benefits of PRRT while safeguarding patient safety, future efforts should focus on integrating predictive biomarkers, refining treatment sequencing, and developing personalized risk-stratified approaches to therapy.

Abstract Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs), pancreatic cysts requiring surgery, from low-risk lesions remains a clinical challenge, often resulting in unnecessary procedures due to limited specificity of current methods. While radiomics and deep learning (DL) have been explored for pancreatic cancer, cyst-level malignancy risk stratification of IPMNs remains untapped. We conducted a multi-institutional study (seven centers, 359 T2W MRI images) to assess the feasibility of AI for predicting IPMN dysplasia grade using cyst-level image features. We developed and compared 2D and 3D radiomics-only, deep learning (DL)-only, and radiomics-DL fusion models, using expert radiologist scoring as a baseline reference. Model performance was evaluated using held-out test data. The radiomics-DL fusion model showed the highest discriminatory ability on the test set (AUC 0.692), outperforming the radiomics-only model (AUC 0.665). Expert accuracy varied widely (37.4%-66.7%). The fusion model integrating deep learning and radiomics features from routine T2W MRI (AUC: 0.692) demonstrates potential for objective, cyst-level risk stratification of IPMNs in a multi-center cohort, outperforming both radiomics-only models and expert radiologists. While performance requires improvement for standalone clinical use, this approach offers a scalable, non-invasive method to potentially improve diagnostic accuracy and reduce unnecessary surgical interventions.

Abstract Over the last 30 years, axillary surgery in patients with breast cancer has undergone a consistent patient-centered, evidence-based de-escalation of surgical intervention, including considerable practice changes over the last decade. As surgical approaches change, the role of breast imaging radiologists and axillary imaging must also evolve. Axillary imaging remains variable across radiology practices, with implementation of new protocols occurring at various speeds. Breast radiologists must be aware of recent trials and remain agile in adopting or responding to changing treatment paradigms. Breakthrough studies, such as the SOUND (Sentinel Node Vs Observation After Axillary Ultra-souND) trial, must be vetted and evaluated by individual practices before adoption. Breast radiologists should play a key role in multidisciplinary collaboration with colleagues involved in breast cancer care to assist with strategic planning and appropriate resource utilization.

Circulating glucagon concentrations differ between individuals with no diabetes (ND) and those with type 1 diabetes (T1D). We combined an isotope dilution technique using stable tracers [6,22-13C9,15N1]glucagon and [6,14,19,22-13C9,15N1]glucagon with splanchnic and leg catheterization in participants with ND (n = 8; age 23.1 ± 2.9 years, BMI 26.6 ± 3.5 kg/m2, HbA1c 5.0 ± 0.2% [31 ± 2 mmol/mol]) and T1D (n = 6; 29.0 ± 8.8 years, BMI 26.3 ± 5.0 kg/m2, HbA1c 7.9 ± 0.8% [63 ± 8 mmol/mol]) in the overnight fasted state. After baseline period, exogenous glucagon was infused at rates designed to achieve plasma glucagon concentrations spanning the physiological ranges, to determine the effects of rising glucagon concentrations on splanchnic and leg glucagon balance. At baseline, splanchnic glucagon extraction (SGE) was similar (30.7 ± 2.7 vs. 29.1 ± 2.9%) but leg glucagon extraction (LGE) was lower (27.0 ± 4.2 vs. 40.6 ± 3.1%) in participants with T1D versus those with ND. However, with increasing plasma glucagon concentrations, while SGE remained unchanged within and between groups, LGE fell in participants with ND (41 vs. 31 vs. 24%) but did not change in those with T1D. Despite a numerically lower net splanchnic glucagon production in participants with T1D than in those with ND, no changes were observed with increasing glucagon concentrations within the physiological range in both groups. This is the first human study applying novel glucagon isotopes that describes regional glucagon metabolism in participants with ND and T1D. Our observations provide translational relevance for dual hormone closed-loop systems and provide tools for probing the effects of GLP-1, dual, and triple receptor agonists on pancreatic α-cell functions. Article Highlights This study was conducted to assess splanchnic and leg glucagon metabolism in humans using stable glucagon isotopes. We wanted to evaluate whether splanchnic and leg glucagon metabolism differed between participants with no diabetes (ND) and those with type 1 diabetes (T1D) at glucagon concentrations spanning the physiological range. Whereas splanchnic glucagon extraction did not differ between participants with ND and those with T1D, leg glucagon extraction fell in those with ND but did not change in those with T1D as glucagon concentrations increased. Net splanchnic glucagon production did not change with exogenous glucagon infusion. Our study has implications for dual hormone closed-loop control in T1D where glucagon is infused for prevention of hypoglycemia and for investigating the effects of emerging GLP-1, glucose-dependent insulinotropic polypeptide, and glucagon receptor agonists on endogenous glucagon secretion and clearance.

Abstract Motivation Single-cell RNA sequencing (scRNA-seq) has become an important method for characterizing cellular heterogeneity, revealing more biological insights than the bulk RNA-seq. The surge in scRNA-seq data across multiple individuals calls for efficient and statistically powerful methods for differential expression (DE) analysis that addresses individual-level biological variability. Results We introduced DiSC, a method for conducting individual-level DE analysis by extracting multiple distributional characteristics, jointly testing their association with a variable of interest, and using a flexible permutation testing framework to control the false discovery rate (FDR). Our simulation studies demonstrated that DiSC effectively controlled the FDR across various settings and exhibited high statistical power in detecting different types of gene expression changes. Moreover, DiSC is computationally efficient and scalable to the rapidly increasing sample sizes in scRNA-seq studies. When applying DiSC to identify DE genes potentially associated with COVID-19 severity and Alzheimer’s disease across various types of peripheral blood mononuclear cells and neural cells, we found that our method was approximately 100 times faster than other state-of-the-art methods and the results were consistent and supported by existing literature. While DiSC was developed for scRNA-seq data, its robust testing framework can also be applied to other types of single-cell data. We applied DiSC to cytometry by time-of-flight data, DiSC identified significantly more DE markers than traditional methods. Availability and implementation The R software package “SingleCellStat” is freely available on CRAN (https://cran.r-project.org/web/packages/SingleCellStat/index.html) and GitHub (https://github.com/Lujun995/DiSC). The replication code for reproducing the analyses in this study is publicly accessible at https://github.com/Lujun995/DiSC_Replication_Code. The scRNA-seq expression matrix and metadata utilized in our simulations and analyses can be retrieved from https://cells.ucsc.edu/autism/rawMatrix.zip, https://cellxgene.cziscience.com/collections/1ca90a2d-2943-483d-b678-b809bf464c30, and https://covid19.cog.sanger.ac.uk/submissions/release1/haniffa21.processed.h5ad.

Objective: To assess the efficacy of trichloroacetic acid (TCA) as treatment for high-grade cervical intraepithelial neoplasia (CIN 2 or 3). Methods: Retrospective study of patients with CIN 2 or greater treated with TCA from 2016 to 2022. Patients who desired future childbearing had a satisfactory colposcopy and had not received prior treatment for CIN. Patients were offered excision as initial treatment and for lesions that did not regress. TCA was discussed as an alternative, off-label treatment. Under colposcopic guidance, 85% TCA was applied to the transformation zone and distal endocervix. Patients were followed with colposcopy and cytology every 3–6 months and subsequently underwent excision or reapplication of TCA. Primary outcomes were regression and remission after a minimum of 6 months of treatment with TCA. Results: A total of 43 patients elected treatment with TCA. The mean age was 28.6 years with a median follow-up time of 12 months. The majority of patients were nonsmokers (95.3%) and White (73.9%). Pretreatment diagnosis was CIN3 and CIN2 in 32.6% and 67.4% of cases, respectively. After a median of three TCA treatments, 23.3% regression and 55.8% remission were noted for an overall cytological response rate of 79.1%. 16.3% required excision within 1 year. There were no cervical cancer diagnoses. The median time to regression and remission was 9 months and 6 months, respectively. Conclusion: In patients with high-grade CIN, treatment with TCA may have favorable short-term outcomes. TCA may represent an alternative to excision in reproductive-aged patients, though additional studies are needed with a larger cohort in a prospective manner.

Abstract Background In two 12‐week, randomized, placebo‐controlled trials (RCTs) in individuals with alcohol use disorder (AUD), topiramate significantly reduced heavy drinking days (HDDs), and alcohol‐related problems. In a secondary analysis of those findings, we examined four broad measures of genetic risk—polygenic scores (PGS)—of problematic alcohol use (PAU), drinks per week (DPW), and time to relapse to any drinking (TR) and heavy drinking (THR) as moderators of topiramate's effect on HDDs and alcohol‐related problems. Methods We analyzed data from 285 individuals with AUD (65.6% male) of European‐like ancestry, who were treated with either topiramate (49.1%) or placebo (50.9%). All patients underwent genome‐wide array genotyping, and PGS were calculated using summary statistics from genome‐wide association studies of PAU, DPW, and TR and THR (two time‐to‐event outcomes among patients treated in AUD pharmacotherapy trials). We hypothesized an interaction effect in which greater genetic risk—particularly for PAU—would be associated with a greater therapeutic response to topiramate than placebo. Results As shown previously, topiramate significantly reduced both HDDs (odds ratio [OR] = 0.50, p < 0.001) and Short Index of Problems (SIP) scores ( b = −3.04, p < 0.001) more than placebo. There were nonsignificant associations of higher PGS with more HDDs (OR = 1.17, 95% CI = 0.98–1.41, p = 0.091) and a greater reduction in HDDs in the topiramate group (OR = 0.80, 95% CI = 0.62–1.03, p = 0.089). There were also significant interaction effects with treatment on SIP score by PGS for PAU ( b = −1.64, SE = 0.78, p = 0.033), TR ( b = −2.16, SE = 0.72, p = 0.003), and TRH ( b = −2.17, SE = 0.72, p = 0.003). Conclusions These findings provide proof of principle for the use of alcohol‐related PGS as moderators of the effects of topiramate for treating AUD. Larger RCTs of topiramate are needed to provide adequate statistical power to validate this pharmacogenetic approach to precision AUD treatment.

AbstractBackgroundWorkforce engagement can provide structure, income, feelings of accomplishment, and personal contacts, growing an individual's recovery capital (RC). Employed individuals are also more likely to complete addiction treatment. We sought to investigate whether changes in employment status from alcohol treatment admission to discharge correlated with changes in alcohol use frequency over those time points.MethodsThe Treatment Episode Dataset—Discharges (2017–2021) provided the data. Employment status (full‐time, part‐time, unemployed, and not in labor force) and alcohol use frequency (daily use, some use, and no use in past month) were assessed at treatment admission and discharge. Changes in alcohol use frequency during treatment were recorded as Reduction or No reduction. Logistic regression using reduced alcohol use frequency as the dependent variable included employment status at admission and discharge separately. A second analysis included employment status at both admission and discharge and their interaction term. An adjusted model included all covariates (race, ethnicity, age, education, and referral source), with its results being used to derive the marginal probabilities of reduced alcohol use frequency.ResultsThere were 856,085 alcohol treatment admissions over the 5 years, with 221,724 (25.9%) first admissions. Transitioning from not in the labor force or unemployed to full‐time saw the largest percentage of encounters decreasing alcohol use frequency: 71.9% (95% CI: 70.0–73.7) and 69.3% (95% CI: 68.1–70.5), respectively. Those remaining unemployed had the lowest reduction at 26.7% (95% CI: 26.3–27.1), with a sample reduction of 42.7% (95% CI: 42.5–42.9) overall. Far more people (60.4%) completed treatment within the Reduction group than in the No reduction group (30.2%).ConclusionsFindings suggest that improving employment status may be relevant for reducing alcohol use frequency. This aligns with past work showing overall improved health outcomes with lower unemployment levels. Incorporating vocational training and workforce engagement activities into outpatient treatment may help augment traditional approaches to improve an individual's RC.