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Radiomics has been applied to predict recurrence in several disease sites, but current approaches are typically restricted to analyzing tumor features, neglecting nontumor information in the rest of the body. The purpose of this work was to develop and validate a model incorporating nontumor radiomics, including whole-body features, to predict treatment outcomes in patients with previously untreated locoregionally advanced cervical cancer. Methods: We analyzed 127 cervical cancer patients treated definitively with chemoradiotherapy and intracavitary brachytherapy. All patients underwent pretreatment whole-body 18F-FDG PET/CT. To quantify effects due to the tumor itself, the gross tumor volume (GTV) was directly contoured on the PET/CT image. Meanwhile, to quantify effects arising from the rest of the body, the planning target volume (PTV) was deformably registered from each planning CT to the PET/CT scan, and a semiautomated approach combining seed-growing and manual contour review generated whole-body muscle, bone, and fat segmentations on each PET/CT image. A total of 965 radiomic features were extracted for GTV, PTV, muscle, bone, and fat. Ninety-five patients were used to train a Cox model of disease recurrence including both radiomic and clinical features (age, stage, tumor grade, histology, and baseline complete blood cell counts), using bagging and split-sample-validation for feature reduction and model selection. To further avoid overfitting, the resulting models were tested for generalization on the remaining 32 patients, by calculating a risk score based on Cox regression and evaluating the c-index (c-index > 0.5 indicates predictive power). Results: Optimal performance was seen in a Cox model including 1 clinical biomarker (whether or not a tumor was stage III-IVA), 2 GTV radiomic biomarkers (PET gray-level size-zone matrix small area low gray level emphasis and zone entropy), 1 PTV radiomic biomarker (major axis length), and 1 whole-body radiomic biomarker (CT bone root mean square). In particular, stratification into high- and low-risk groups, based on the linear risk score from this Cox model, resulted in a hazard ratio of 0.019 (95% CI, 0.004, 0.082), an improvement over stratification based on clinical stage alone, which had a hazard ratio of 0.36 (95% CI, 0.16, 0.83). Conclusion: Incorporating nontumor radiomic biomarkers can improve the performance of prognostic models compared with using only clinical and tumor radiomic biomarkers. Future work should look to further test these models in larger, multiinstitutional cohorts.

Existing methods often fail to recognize the conversions for the biological roles of the pairs of genes and microRNAs (miRNAs) between the tumor and normal samples. We have developed a novel cluster scoring method to identify messenger RNA (mRNA) and miRNA interaction pairs and clusters while considering tumor and normal samples jointly. Our method has identified 54 significant clusters for 15 cancer types selected from The Cancer Genome Atlas project. We also determined the shared clusters across tumor types and/or subtypes. In addition, we compared gene and miRNA overlap between lists identified in our liver hepatocellular carcinoma (LIHC) study and regulatory relationships reported from human and rat nonalcoholic fatty liver disease studies (NAFLD). Finally, we analyzed biological functions for the single significant cluster in LIHC and uncovered a significantly enriched pathway (phospholipase D signaling pathway) with six genes represented in the cluster, symbols: DGKQ, LPAR2, PDGFRB, PIK3R3, PTGFR and RAPGEF3. [ABSTRACT FROM AUTHOR]

Background: Randomized trials have found that patients with locoregionally advanced p16+ oropharyngeal squamous cell carcinoma (OPSCC) do not benefit from treatment deintensification, even among favorable risk groups. While various methods have been used to identify candidates for treatment deintensification, the optimal approach is unknown., Methods: We conducted a multi-institutional cohort study of 444 patients with previously untreated p16+ OPSCC undergoing definitive radiotherapy with or without systemic therapy between 2009-2022. We compared two approaches for identifying candidates for deintensification: (1) favorable vs. unfavorable risk, using NRG-HN005 eligibility criteria, and (2) low vs. high relative risk for cancer events, using the HNCIG predictive classifier ("omega score"). We tested differences in outcomes and systemic therapy allocation by risk group using multivariable Cox models, competing event models, and logistic regression, and compared characteristics of hypothetical deintensification trials using the two approaches. PFS events were defined as cancer recurrence (locoregional or distant) or death from any cause., Results: Median follow-up time was 52 months; 120 patients (27.0%) were favorable risk; a different 120 patients had low omega score; 28 patients (6.3%) met both criteria; 184 patients (41.4%) had discordant classification. On ordinal logistic regression, decreasing omega score was associated with a statistically significantly lower odds of receiving intensive therapy (normalized OR 0.37 per standard deviation; 95% CI: 0.24-0.57), with a greater magnitude than favorable risk group (OR 0.66; 95% CI: 0.44-0.99). Among patients receiving cisplatin and/or platinum-based induction (N=374), favorable risk was associated with significantly improved PFS (HR 0.59, 95% CI 0.36-0.99), whereas lower omega score was associated with a significantly decreased relative hazard for cancer events (RHR 0.18, 95% CI 0.070-0.46). In simulations, selecting patients with low omega scores increased the efficiency of hypothetical non-inferiority trials., Conclusions: Considering patients' relative risk for cancer events can help define optimal populations for treatment deintensification in p16+ OPSCC., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to disclose relevant to this work., (Copyright © 2024. Published by Elsevier Inc.)

Experiments show that the absorption spectrum of the hydrated electron ( e hyd - ) blue-shifts in electrolyte solutions compared with what is seen in pure water. This shift has been assigned to the e hyd - 's competitive ion-pairing interactions with the salt cation relative to the salt anion based on the ions' positions on the Hofmeister series. Remarkably, little work has been done investigating the e hyd - 's behavior when the salts have chaotropic cations, which should greatly change the ion-pairing interactions given that the e hyd - is a champion chaotrope. In this work, we remedy this by using mixed quantum/classical simulations to analyze the behavior of two different models of the e hyd - in aqueous RbF and RbI electrolyte solutions as a function of salt concentration. We find that the magnitude of the salt-induced spectral blue-shift is determined by a combination of the number of chaotropic Rb + cations near the e hyd - and the number of salt anions near those cations so that the spectrum of the e hyd - directly reflects its local environment. We also find that the use of a soft-cavity e hyd - model predicts stronger competitive interactions with Rb + relative to I - than a more traditional hard cavity model, leading to different predicted spectral shifts that should provide a way to distinguish between the two models experimentally. Our simulations predict that at the same concentration, salts with chaotropic cations should produce larger spectral blue-shifts than salts with kosmotropic cations. We also found that at high salt concentrations with chaotropic cations, the predicted blue-shift is greater when the salt anion is kosmotropic instead of chaotropic. Our goal is for this work to inspire experimentalists to make such measurements, which will help provide a spectroscopic means to distinguish between simulations models that predict different hydration structures for the e hyd - .

Prurigo nodularis is a chronic, relapsing neurodermatitis that is often resistant to standard therapies with topical corticosteroids and oral antihistamines. Thalidomide, while efficacious in treating recalcitrant cases of prurigo nodularis, causes significant toxicity. Thalidomide-induced peripheral neuropathy frequently results in drug discontinuation. Lenalidomide (Revlimid; Celgene Corporation, Summit, NJ) is a derivative of thalidomide with less neurotoxicity approved for the treatment of multiple myeloma and myelodysplastic syndromes that has not been widely studied in dermatologic disorders. Here, we report a case of refractory prurigo nodularis effectively treated with lenalidomide. Given its favorable side-effect profile, lenalidomide may offer a superior alternative to thalidomide in the treatment of this condition.