Ovarian cancer is one of the leading causes of deaths among patients with gynecological malignancies worldwide. In order to identify prognostic markers for ovarian cancer, we performed RNA-sequencing and analyzed the transcriptome data from 51 patients who received conventional therapies for high-grade serous ovarian carcinoma (HGSC). Patients with early-stage (I or II) HGSC exhibited higher immune gene expression than patients with advanced stage (III or IV) HGSC. In order to predict the prognosis of patients with HGSC, we created machine learning-based models and identified USP19 and RPL23 as candidate prognostic markers. Specifically, patients with lower USP19 mRNA levels and those with higher RPL23 mRNA levels had worse prognoses. This model was then used to analyze the data of patients with HGSC hosted on The Cancer Genome Atlas; this analysis validated the prognostic abilities of these two genes with respect to patient survival. Taken together, the transcriptome profiles of USP19 and RPL23 determined using a machine-learning model could serve as prognostic markers for patients with HGSC receiving conventional therapy.

Dexmedetomidine has sedative, sympatholytic, analgesic, and anti-inflammatory effects. We investigated the effects of intraoperative dexmedetomidine infusion without a loading dose in the prevention of pain and inflammation after laparoscopic hysterectomy. In this study, 100 patients undergoing laparoscopic hysterectomy under desflurane anesthesia were randomized to receive either 0.9% saline or dexmedetomidine (0.4 μg/kg/h) after induction to trocar removal. The primary endpoints were postoperative pain and inflammatory response presented by the level of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), IL-10, and C-reactive protein (CRP). The secondary endpoints were hemodynamics during the anesthesia and surgery and postoperative nausea and vomiting. Postoperative pain was decreased in the dexmedetomidine group for every time point, and post-anesthesia care unit (PACU) rescue fentanyl doses were decreased in the dexmedetomidine group. The inflammatory response representing TNF-α, IL-6, IL-10, and CRP were similar across the two groups. Postoperative nausea and vomiting from PACU discharge to 24 h post-surgery were reduced in the dexmedetomidine group. During anesthesia and surgery, the patient’s heart rate was maintained lower in the dexmedetomidine-receiving group. Dexmedetomidine of 0.4 μg/kg/h given as an intraoperative infusion significantly reduced postoperative pain but did not reduce the inflammatory responses in patients undergoing laparoscopic hysterectomy.

Alteration in expression of miRNAs can cause various malignant changes and the metastatic process. Our aim was to identify the miRNAs involved in cervical squamous cell carcinoma (SqCC) and metastasis, and to test their utility as indicators of metastasis and survival. Using microarray technology, we performed miRNA expression profiling on primary cervical SqCC tissue (n = 6) compared with normal control (NC) tissue and compared SqCC that had (SqC-M; n = 3) and had not (SqC-NM; n = 3) metastasized. Four miRNAs were selected for validation by qRT-PCR on 29 SqC-NM and 27 SqC-M samples, and nine metastatic lesions (ML-SqC), from a total of 56 patients. Correlation of miRNA expression and clinicopathological parameters was analyzed to evaluate the clinical impact of candidate miRNAs. We found 40 miRNAs differentially altered in cervical SqCC tissue: 21 miRNAs were upregulated and 19 were downregulated (≥2-fold, p < 0.05). Eight were differentially altered in SqC-M compared with SqC-NM samples: four were upregulated (miR-494, miR-92a-3p, miR-205-5p, and miR-221-3p), and four were downregulated (miR-574-3p, miR-4769-3p, miR-1281, and miR-1825) (≥1.5-fold, p < 0.05). MiR-22-3p might be a metastamiR, which was gradually further downregulated in SqC-NM > SqC-M > ML-SqC. Downregulation of miR-30e-5p significantly correlated with high stage, lymph node metastasis, and low survival rate, suggesting an independent poor prognostic factor.

Ovarian cancer is a lethal malignancy, with most patients initially responding to chemotherapy but frequently experiencing recurrence. Previous studies primarily examined tumor characteristics using limited genetic markers or bulk RNA sequencing. Here, we used spatial transcriptomics via the GeoMx^® platform, alongside multispectral immune cell immunofluorescence (IF), to identify biomarkers associated with disease progression following first-line treatment of high-grade serous carcinoma (HGSC). We identified several spatial biomarkers linked to non-recurrence, including elevated NKG7 expression in CD45+ immune cell regions (p = 0.0011) and higher TFPI2 and PIGR expression in tumor areas (p = 2.09 × 10⁻⁶), both associated with improved progression-free survival. Multispectral IF revealed significantly higher regulatory T cell (Treg) to CD8+ T cell ratios in the tumor nests and stroma of recurrent patients (p = 0.016, 0.048). Tregs were also found closer to cancer cells or macrophages than CD8+ T cells in recurrent tumors (p = 0.048), correlating with poor survival. Integrated analysis showed that immune cell density and immune pathway scores in the recurrent group positively correlated with cancer pathway scores, except for NF-κB. This comprehensive analysis revealed clues to interactions between different immune cells and identified biomarkers that may be useful for predicting recurrence of HGSC.