Jian Zhu

Perfusion-based functional magnetic resonance imaging for differentiating serous borderline ovarian tumors from early serous ovarian cancers in a rat model

Background Differentiation of borderline tumors from early ovarian cancer has recently received increasing attention, since borderline tumors often affect young women of childbearing age who desire to preserve fertility. However, previous studies have demonstrated that non-enhanced magnetic resonance imaging (MRI) sequences cannot sufficiently differentiate these tumors. Purpose To investigate the value of dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating serous borderline ovarian tumors (SBOT) from early serous ovarian cancers (eSOCA). Material and Methods Twenty SBOT and 20 eSOCA rat models were performed with DCE-MRI and IVIM-DWI at 3.0-T MR scanner. Qualitative and quantitative parameters of DCE-MRI were acquired and compared between two groups and correlated with the microvessel density (MVD). The receiver operating characteristic (ROC) curve analyses were conducted to determine their differentiating performances. Results SBOTs presented significantly lower values of the initial area under the enhancement curve (iAUC), volume transfer constant (Ktrans), and extracellular extravascular volume fraction (ve) ( P <  0.05) and a significantly higher value of true diffusion (D) ( P =  0.001) compared with eSOCAs. The diagnostic effectiveness of ve combined with D was significantly better than that of ve or Ktrans alone ( P ≤  0.039). Conclusion DCE-MRI may represent a promising tool for differentiating SBOTs from eSOCAs and may not be replaced by IVIM-DWI. Combining DCE-MRI with DWI may improve the diagnostic performance of ovarian tumors.

Magnetic Resonance Imaging and Diffusion Weighted Imaging-Based Histogram in Predicting Mesenchymal Transition High-Grade Serous Ovarian Cancer

To investigate the value of magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) findings in predicting mesenchymal transition (MT) high-grade serous ovarian cancer (HGSOC). Patients with HGSOC were enrolled from May 2017 to December 2020, who underwent pelvic MRI including DWI (b = 0,1000 s/mm A total of 81 consecutive patients were recruited for pelvic MRI before surgery, including 37 (45.7%) MT patients and 44 (54.3%) non-MT patients. At univariate analysis, the features significantly related to MT HGSOC were identified as absence of discrete primary ovarian mass, pouch of Douglas implants, ovarian mass size, tumor volume, mean, SD, median, and 95th percentile apparent diffusion coefficient (ADC) values (all p < 0.05). At multivariate analysis, the absence of discrete primary ovarian mass {odds ratio (OR): 46.477; p = 0.025}, mean ADC value ≤ 1.105 (OR: 1.023; p = 0.009), and median ADC value ≤ 1.038 (OR: 0.982; p = 0.034) were found to be independent risk factors associated with MT HGSOC. The combination of all independent criteria yielded the largest AUC of 0.82 with a sensitivity of 83.87% and specificity of 66.67%, superior to any of the single predictor alone (p ≤ 0.012). The predictive C-index nomogram performance of the combination was 0.82. The combination of absence of discrete primary ovarian mass, lower mean ADC value, and median ADC value may be helpful for preoperatively predicting MT HGSOC.

AIB1 is a novel target of the high‐risk HPV E6 protein and a biomarker of cervical cancer progression

Abstract The high‐risk human papillomaviruses (HPV‐16, ‐18) are critical etiologic agents in human malignancy, most importantly in cervical cancer. These oncogenic viruses encode the E6 and E7 proteins that are uniformly retained and expressed in cervical cancers and required for maintenance of the tumorigenic phenotype. The E6 and E7 proteins were first identified as targeting the p53 and pRB tumor suppressor pathways, respectively, in host cells, thereby leading to disruption of cell cycle controls. In addition to p53 degradation, a number of other functions and critical targets for E6 have been described, including telomerase, Myc, PDZ‐containing proteins, Akt, Wnt, mTORC1, as well as others. In this study, we identified Amplified in Breast Cancer 1 (AIB1) as a new E6 target. We first found that E6 and hTERT altered similar profiling of gene expression in human foreskin keratinocytes (HFK), independent of telomerase activity. Importantly, AIB1 was a common transcriptional target of both E6 and hTERT. We then verified that high‐risk E6 but not low‐risk E6 expression led to increases in AIB1 transcript levels by real‐time RT‐PCR, suggesting that AIB1 upregulation may play an important role in cancer development. Western blots demonstrated that AIB1 expression increased in HPV‐16 E6 and E7 expressing (E6E7) immortalized foreskin and cervical keratinocytes, and in three of four common cervical cancer cell lines as well. Then, we evaluated the expression of AIB1 in human cervical lesions and invasive carcinoma using immunohistochemical staining. Strikingly, AIB1 showed positivity in the nucleus of cells in the immediate suprabasal epithelium, while nuclei of the basal epithelium were negative, as evident in the Cervical Intraepithelial Neoplasia 1 (CIN1) samples. As the pathological grading of cervical lesions increased from CIN1, CIN2, CIN3 carcinoma in situ and invasive carcinoma, AIB1 staining increased progressively, suggesting that AIB1 may serve as a novel histological biomarker for cervical cancer development. For cases of invasive cervical carcinoma, AIB1 staining was specific to cancerous lesions. Increased expression of AIB1 was also observed in transgenic mouse cervical neoplasia and cancer models induced by E6E7 and estrogen. Knockdown of AIB1 expression in E6E7 immortalized human cervical cells significantly abolished cell proliferation. Taken together, these data support AIB1 as a novel target of HPV E6 and a biomarker of cervical cancer progression.