A recent hypothesis for cancer chemoresistance posits that cytotoxic survival of a subpopulation of tumor progenitors drives the propagation of recurrent disease, underscoring the need for new therapeutics that target such primitive cells. To discover such novel compounds active against drug-resistant ovarian cancer, we identified a subset of chemoresistant ovarian tumor cells fulfilling current definitions of cancer-initiating cells from cell lines and patient tumors using multiple stemness phenotypes, including the expression of stem cell markers, membrane dye efflux, sphere formation, potent tumorigenicity, and serial tumor propagation. We then subjected such stem-like ovarian tumor-initiating cells (OTIC) to high-throughput drug screening using more than 1,200 clinically approved drugs. Of 61 potential compounds preliminarily identified, more stringent assessments showed that the antihelmintic niclosamide selectively targets OTICs in vitro and in vivo. Gene expression arrays following OTIC treatment revealed niclosamide to disrupt multiple metabolic pathways affecting biogenetics, biogenesis, and redox regulation. These studies support niclosamide as a promising therapy for ovarian cancer and warrant further preclinical and clinical evaluation of this safe, clinically proven drug for the management of this devastating gynecologic malignancy. Mol Cancer Ther; 11(8); 1703–12. ©2012 AACR.

The primary cause of death from breast cancer is the progressive growth of tumors and resistance to conventional therapies. It is currently believed that recurrent cancer is repopulated according to a recently proposed cancer stem cell hypothesis. New therapeutic strategies that specifically target cancer stem-like cells may represent a new avenue of cancer therapy. We aimed to discover novel compounds that target breast cancer stem-like cells. We used a dye-exclusion method to isolate side population (SP) cancer cells and, subsequently, subjected these SP cells to a sphere formation assay to generate SP spheres (SPS) from breast cancer cell lines. Surface markers, stemness genes, and tumorigenicity were used to test stem properties. We performed a high-throughput drug screening using these SPS. The effects of candidate compounds were assessed in vitro and in vivo. We successfully generated breast cancer SPS with stem-like properties. These SPS were enriched for CD44^high (2.8-fold) and CD24^low (4-fold) cells. OCT4 and ABCG2 were overexpressed in SPS. Moreover, SPS grew tumors at a density of 10³, whereas an equivalent number of parental cells did not initiate tumor formation. A clinically approved drug, niclosamide, was identified from the LOPAC chemical library of 1,258 compounds. Niclosamide downregulated stem pathways, inhibited the formation of spheroids, and induced apoptosis in breast cancer SPS. Animal studies also confirmed this therapeutic effect. The results of this proof-of-principle study may facilitate the development of new breast cancer therapies in the near future. The extension of niclosamide clinical trials is warranted.

Myometrial invasion affects the prognosis of endometrial cancer. However, discrepancies exist between pre-operative magnetic resonance imaging staging and post-operative pathological staging. This study aims to validate the accuracy of artificial intelligence (AI) for detecting the depth of myometrial invasion using a deep learning technique on magnetic resonance images. We obtained 4896 contrast-enhanced T1-weighted images (T1w) and T2-weighted images (T2w) from 72 patients who were diagnosed with surgico-pathological stage I endometrial carcinoma. We used the images from 24 patients (33.3%) to train the AI. The images from the remaining 48 patients (66.7%) were used to evaluate the accuracy of the model. The AI then interpreted each of the cases and sorted them into stage IA or IB. Compared with the accuracy rate of radiologists’ diagnoses (77.8%), the accuracy rate of AI interpretation in contrast-enhanced T1w was higher (79.2%), whereas that in T2w was lower (70.8%). The diagnostic accuracy was not significantly different between radiologists and AI for both T1w and T2w. However, AI was more likely to provide incorrect interpretations in patients with coexisting benign leiomyomas or polypoid tumors. Currently, the ability of this AI technology to make an accurate diagnosis has limitations. However, in hospitals with limited resources, AI may be able to assist in reading magnetic resonance images. We believe that AI has the potential to assist radiologists or serve as a reasonable alternative for pre-operative evaluation of the myometrial invasion depth of stage I endometrial cancers.

The causal role of human papillomavirus (HPV) in cervical carcinogenesis is beyond reasonable questioning. The progression from HPV infection, squamous intraepithelial lesions (SIL) to squamous cell carcinomata (SCC), however, is very uncommon and inefficient. Host genetic factors that may confer the susceptibility of disease progression are largely unknown. Apoptosis is an important fail‐safe check for tumor development, in which Fas/FasL interaction contributes substantially. The purpose of our study is to test the hypothesis that an A/G polymorphism at −670 of Fas promoter with different transcriptional activity is associated with the risk for cervical neoplasia. A hospital‐based case‐control study was conducted, in which 104 patients of low grade SIL (LSIL), 131 high grade SIL (HSIL) and 176 SCC as well as age‐matched, 1:1 controls were tested for Fas polymorphism by PCR‐RFLP. HPV genotypes were determined in case groups by MY PCR‐reverse line blot. The frequency of A allele was significantly (p = 0.006) higher in SCC than in control, conferring an odd ratio of 1.5 (95% CI = 1.1–2.0). The distribution of Fas (−670) genotypes also differed significantly between HSIL, SCC and each of their control (p = 0.017 and 0.03, respectively), with the A/A genotype conferring an OR of 1.3 (95% CI = 1.1–1.6) and 1.6 (95% CI = 1.0–2.5), respectively. Remarkably, the frequency of A allele and A/A genotype increased gradually in accordance with the multi‐step carcinogenesis from LSIL, HSIL to SCC (p_{test for trend} = 0.0066 and 0.0007, respectively). In addition, there was no difference of Fas genotypes between HPV (+) and HPV (−) cases. Fas genotypes, however, differed in LSIL infected with different HPV types (p = 0.033). The present study demonstrated an association between Fas polymorphism and cervical carcinogenesis. We deduced a possible effect of apoptosis of immune cells in this virus‐induced cancer.

Despite of the trend that the application of DNA methylation as a biomarker for cancer detection is promising, clinically applicable genes are few. Therefore, we looked for novel hypermethylated genes for cervical cancer screening. At the discovery phase, we analyzed the methylation profiles of human cervical carcinomas and normal cervixes by methylated DNA immunoprecipitation coupled to promoter tiling arrays (MeDIP-on-chip). Methylation-specific PCR (MSP), quantitative MSP and bisulfite sequencing were used to verify the methylation status in cancer tissues and cervical scrapings from patients with different severities. Immunohistochemical staining of a cervical tissue microarray was used to confirm protein expression. We narrowed to three candidate genes: DBC1, PDE8B, and ZNF582; their methylation frequencies in tumors were 93%, 29%, and 100%, respectively. At the pre-validation phase, the methylation frequency of DBC1 and ZNF582 in cervical scraping correlated significantly with disease severity in an independent cohort (n = 330, both P<0.001). For the detection of cervical intraepithelial neoplasia 3 (CIN3) and worse, the area under the receiver operating characteristic curve (AUC) of ZNF582 was 0.82 (95% confidence interval = 0.76–0.87). Our study shows ZNF582 is frequently methylated in CIN3 and worse lesions, and it is demonstrated as a potential biomarker for the molecular screening of cervical cancer.