Haeyoun Kang

Identification of Prognostic Biomarkers of Ovarian High-Grade Serous Carcinoma: A Preliminary Study Using Spatial Transcriptome Analysis and Multispectral Imaging

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.

Establishment and Its Utility of a Patient-Derived Cell Xenografts (PDCX) Model with Cryopreserved Cancer Cells from Human Tumor

Patient-derived xenograft (PDX) models are powerful tools in cancer research, offering an accurate platform for evaluating cancer treatment efficacy and predicting responsiveness. However, these models necessitate surgical techniques for tumor tissue transplantation and face challenges with non-uniform tumor growth among animals. To address these issues, we attempted to develop a new PDX modeling method using high-grade serous ovarian cancer (HGSC), a fatal disease with a 5-year survival rate of 29%, which requires personalized research due to its morphological, genetic, and molecular heterogeneities. In this study, we developed a new patient-derived cancer cell xenograft (PDCX) model with high engraftment efficiency (64%) that utilizes primary cancer cells instead of patient tissues. Primary cancer cells can be stably cryopreserved for extended periods (up to 485 days), and when transplanted into female NSGA mice, they maintain morphological and molecular characteristics without significant genetic differences compared to their original primary tumors. Furthermore, PDCX models can be easily produced using a syringe, allowing for uniform tumor sizes across multiple animals. Additionally, M2 PDCXs exhibited a significantly faster growth rate compared to M2 PDTXs. Consequently, our PDCX model offers a streamlined approach for evaluating personalized cancer treatments with minimal experimental variability.

miR-22-3p and miR-30e-5p Are Associated with Prognosis in Cervical Squamous Cell Carcinoma

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.