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In oncogenesis and development of malignant tumor, microRNAs (miRNAs) regulate the complex gene expression associated with the tumor pathogenesis. Currently, only few studies have been conducted to identify miRNAs and the potential pathways involved in the pathogenesis of brain metastasis in patients who underwent radiotherapy, especially miRNAs in the plasma exosomes. Therefore, this study is aimed to use small RNA analysis to identify miRNAs and their potential target genes in plasma exosomes during the initiation and development of brain metastasis in patients who underwent radiotherapy. Using high-throughput sequencing technologies, we identified 35 differentially expressed miRNAs in patients with brain metastasis who had undergone radiotherapy. In annotation of miRNA targets, gene ontology enrichment analysis revealed that the targets of the differentially expressed miRNAs were significantly enriched in the regulation of cellular processes. Kyoto Encyclopedia of Genes and Genomes revealed that most of the miRNA targets were cancer-related, including genes involved in the mitogen-activated protein kinase signaling pathway, cancer-related pathways, phosphatidylinositol 3-kinase-protein kinase B signaling pathway, microtubule-associated protein kinase signaling pathway, Ras signaling pathway, regulation of the actin cytoskeleton, and axon guidance. In conclusion, this study provides a new perspective to understand the possible function of these miRNAs in the pathogenesis of brain metastasis. This was the first time that a pilot study identified plasma exosomal miRNAs in five patients with brain metastasis before and after radiotherapy. This study is the beginning; more specimen and further research are needed to explore the functional role of specific miRNAs and their potential as therapeutic targets for brain metastasis.

Purpose: This study aimed to evaluate whether photoacoustic (PA), sound touch elastography (STE), and viscoelasticity (VE) can distinguish between normal and abnormal postradiation therapy breast skin and compare these methods with Radiation Therapy Oncology Group (RTOG) criteria at a 20 Gy threshold., Methods and Materials: Patients who met inclusion and exclusion criteria underwent PA, STE, and VE on the same day. Collected data included radiation dose, molecular type, RTOG, Fitzpatrick skin type, pathology, neoadjuvant chemotherapy status, TNM (tumor, node, metastasis) classification, surgical procedures, primary breast cancer location, body mass index, and age. A sample of 41 patients was determined using a 2-sample t test. Statistical tools such as t-tests, variance analysis, rank sum tests, and χ 2 tests, along with random forest analysis and receiver operating characteristic curves, were used to evaluate the radiation dose effects., Results: Data from 66 patients showed significant differences in parameters such as dermis and subcutaneous tissue oxygen saturation, dermal thickness, and skin elasticity (P values < .05). However, minimum values of oxygen saturation and some photoacoustic measures were not significantly different. Notably, at a 20 Gy radiation threshold, significant variations in oxygen saturation, abnormal dermal thickness, and skin STE and VE were observed, proving more accurate than RTOG grading., Conclusions: Our findings demonstrate that PA and elastography imaging are effective in differentiating between normal and abnormal breast tissue and assessing radiation-induced changes, thereby highlighting the potential of these imaging techniques., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: Large language models (LLMs) are deep learning models designed to comprehend and generate meaningful responses, which have gained public attention in recent years. The purpose of this study is to evaluate and compare the performance of LLMs in answering questions regarding breast cancer in the Chinese context., Material and Methods: ChatGPT, ERNIE Bot, and ChatGLM were chosen to answer 60 questions related to breast cancer posed by two oncologists. Responses were scored as comprehensive, correct but inadequate, mixed with correct and incorrect data, completely incorrect, or unanswered. The accuracy, length, and readability among answers from different models were evaluated using statistical software., Results: ChatGPT answered 60 questions, with 40 (66.7%) comprehensive answers and six (10.0%) correct but inadequate answers. ERNIE Bot answered 60 questions, with 34 (56.7%) comprehensive answers and seven (11.7%) correct but inadequate answers. ChatGLM generated 60 answers, with 35 (58.3%) comprehensive answers and six (10.0%) correct but inadequate answers. The differences for chosen accuracy metrics among the three LLMs did not reach statistical significance, but only ChatGPT demonstrated a sense of human compassion. The accuracy of the three models in answering questions regarding breast cancer treatment was the lowest, with an average of 44.4%. ERNIE Bot's responses were significantly shorter compared to ChatGPT and ChatGLM ( p  < .001 for both). The readability scores of the three models showed no statistical significance., Conclusions: In the Chinese context, the capabilities of ChatGPT, ERNIE Bot, and ChatGLM are similar in answering breast cancer-related questions at present. These three LLMs may serve as adjunct informational tools for breast cancer patients in the Chinese context, offering guidance for general inquiries. However, for highly specialized issues, particularly in the realm of breast cancer treatment, LLMs cannot deliver reliable performance. It is necessary to utilize them under the supervision of healthcare professionals., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Cervical cancer (CC) is a malignancy seriously endangering women's life and health worldwide. GEPIA demonstrated that attractin-like 1 (ATRNL1) presents downregulation in CC tissue. Transcription factor CCAAT enhancer binding protein beta (CEBPB) was previously revealed to present depletion in CC tissue. We attempted to clarify molecular mechanism between ATRNL1 and CEBPB underlying CC progression. Bioinformatics, RT-qPCR and western blotting revealed expression characteristics of ATRNL1 in CC. RT-qPCR measured ATRNL1 and CEBPB levels in CC cell lines. Gain-of-function assays clarified role of ATRNL1 in CC cell behaviors. Bioinformatics, Pearson correlation, ChIP and luciferase reporter experiments assessed association of ATRNL1 and CEBPB in CC cells. Rescue assays assessed regulatory function of CEBPB-ATRNL1 in CC cellular processes. ATRNL1 showed depletion in CC tissue and cells at mRNA and protein levels. ATRNL1 upregulation repressed CC cell viability, migration and EMT. CEBPB bound to ATRNL1 promoter to transcriptionally upregulate ATRNL1 in CC cells. The impact of CEBPB elevation on CC cell viability, migration and EMT were countervailed by ATRNL1 depletion. ATRNL1 and CEBPB present depletion and serve as tumor suppressors in CC cells. ATRNL1 suppresses CC cell malignancy through CEBPB activation, which may provide a potential new direction for seeking therapeutic plans for CC.

Hypoxia-inducible factor-1α (HIF-1α) is a crucial transcription factor that plays an important role in the carcinogenesis and development of nasopharyngeal carcinoma. In this research, a novel biodegradable D-α-tocopheryl polyethylene glycol 1000 succinate-b-poly(ε-caprolactone-ran-glycolide) (TPGS-b-(PCL-ran-PGA)) nanoparticle (NP) was prepared as a delivery system for small interfering ribonucleic acid (siRNA) molecules targeting HIF-1α in nasopharyngeal carcinoma gene therapy. The results showed that the NPs could efficiently deliver siRNA into CNE-2 cells. CNE-2 cells treated with the HIF-1α siRNA-loaded TPGS-b-(PCL-ran-PGA) NPs showed reduction of HIF-1α expression after 48 hours of incubation via real-time reverse transcriptase-polymerase chain reaction and Western blot analysis. The cytotoxic effect on CNE-2 cells was significantly increased by HIF-1α siRNA-loaded NPs when compared with control groups. In a mouse tumor xenograft model, the HIF-1α siRNA-loaded NPs efficiently suppressed tumor growth, and the levels of HIF-1α mRNA and protein were significantly decreased. These results suggest that TPGS-b-(PCL-ran-PGA) NPs could function as a promising genetic material carrier in antitumor therapy, including therapy for nasopharyngeal carcinoma.