Journal of Advanced Research

The mortalities of female-specific cancers in China and other countries with distinct socioeconomic statuses: A longitudinal study

Female-specific cancers seriously affect physical and psychological health of women worldwide. We aimed to elucidate trends in the age-standardized mortality rates (ASMRs) of breast cancer, cervical cancer, uterine cancer, and ovarian cancer in female populations with different socioeconomic statuses in China and in countries with different Human Development Index (HDI). A longitudinal study was performed using the data of cancer death in China and other 39 countries. The mortality rates were standardized with the Segi's world population. Trends in the mortalities were exhibited by estimated annual percentage change (EAPC). Pearson correlation was used to assess the association between EAPC and HDI. In mainland China, female breast cancer, cervical cancer, uterine cancer, and ovarian cancer accounted for 6.60 %, 4.21 %, 2.50 %, and 2.02 % of cancer death (n = 1,314,040) in women with 1,220,251,032 person-years, respectively. The ASMRs of cervical cancer (EAPC = 3.87 %, P < 0.001) and ovarian cancer (EAPC = 1.81 %, P < 0.001) increased, that of female breast cancer unchanged, whereas that of uterine cancer was extremely higher and rapidly decreased (EAPC =  - 7.65 %, P < 0.001), during 2004-2019. The ASMRs of female breast and ovarian cancers were higher in urban and developed regions than in rural and undeveloped regions, in contrast to cervical and uterine cancers. The ASMRs of female breast and ovarian cancers were lower in China than in other countries, in contrast to uterine cancer. The ASMR of cervical cancer decreased, that of uterine cancer increased, in other countries during 2004-2017. EAPCs for the ASMRs of breast and ovarian cancers were inversely correlated to HDI. The ASMRs of cervical and ovarian cancers increased, in contrast to uterine cancer, in China during socioeconomic transition. Trends in the ASMRs of breast and ovarian cancers were inversely associated with HDI. These data help control female-specific cancers.

Mitochondrial fatty acid oxidation as the target for blocking therapy-resistance and inhibiting tumor recurrence: The proof-of-principle model demonstrated for ovarian cancer cells

Cancer patients treated with current chemotherapeutic and targeted therapies frequently achieve partial remission, which ultimately relapse with more aggressive, drug-resistant tumor phenotypes. To a certain extent, drug-tolerant persister (DTP) cells are responsible for residual tumors after systemic anticancer therapy and the onset of acquired drug resistance. Therefore, novel therapies targeting DTP cells to prevent drug resistance and tumor recurrence are urgently needed. We aimed to investigate the traits and key vulnerabilities of drug-tolerant ovarian cancer persister cells and to seek out potential therapeutic strategies. We constructed paclitaxel-tolerant ovarian cancer persister cells by exposing ovarian cancer parental cells to a lethal dose of paclitaxel. Proteomics analysis, in vitro and in vivo assays were performed to identify biological processes that could serve as potential vulnerabilities in persister cells. Paclitaxel-tolerant ovarian cancer persister cells were found to undergo a metabolic reprogramming through the upregulation of fatty acid oxidation (FAO). Treatment with the FAO inhibitor ST1326 suppressed FAO and increased sensitivity to paclitaxel in persister cells. Moreover, combination therapy with paclitaxel and ST1326 prevented ovarian tumor recurrence with satisfactory biosafety in a mouse model of ovarian cancer relapse, indicating that FAO disruption can improve the efficacy of paclitaxel-based therapy in ovarian cancer. Mechanistically, we found that paclitaxel treatment upregulated CEBPB, a transcription factor that induced the expression of the FAO-related enzyme HADHA and contributed to FAO elevation in persister cells. This study revealed an upregulation of FAO in paclitaxel-tolerant ovarian cancer persister cells and provided a prospective paclitaxel-ST1326 combination therapy targeting persister cells that may prevent the development of acquired drug resistance and achieve superior long-term ovarian cancer control in the future. Our research established a conceptual framework for advancing personalized treatment approaches and enhancing patient outcomes in ovarian cancer therapy.

S100B induces angiogenesis via the clathrin/FOXO1/β-catenin signaling pathway and contributes to Bevacizumab resistance in epithelial ovarian cancer

Bevacizumab (BEV), the most common antiangiogenic agent for treating ovarian cancer, prolongs progression-free survival (PFS) but does not significantly improve overall survival (OS). Improving the limited clinical benefit of BEV remains a major challenge in ovarian cancer treatment. Although several studies have explored the mechanisms underlying tumor resistance to BEV, the clinical translation of these findings to overcome BEV resistance has been limited. To identify the key molecules and mechanisms that modulate ovarian cancer sensitivity to BEV. RNA sequencing was conducted on BEV-sensitive and BEV-resistant mouse ovarian cancer tissue to identify differentially expressed genes (DEGs). A prognostic assessment was performed and a risk signature was constructed using these DEGs and the BEV-related sequencing datasets. S100B was identified and assessed in angiogenesis using tube formation, 3D fibrin bead sprouting, wound healing, and migration assays. Downstream targets and signaling pathways of S100B in HUVECs were identified by proteomics and validated by western blot. The effect of S100B inhibitors on BEV efficacy was evaluated using in vivo experiments. A BEV-related prognostic signature comprising 11 genes was constructed. Of these, S100B expression significantly increased in BEV-resistant mouse ovarian cancer tissue and significantly correlated with poor PFS and OS of ovarian cancer patients treated with a BEV combination chemotherapy. HUVECs co-cultured with S100B-overexpressing ovarian cancer cells promoted tube formation, sprouting, and migration. Exogenous S100B entered HUVECs via clathrin-mediated endocytosis, downregulated FOXO1 expression, and promoted β-catenin nuclear translocation and transcriptional activity, ultimately enhancing tube formation. The S100B inhibitor pentamidine significantly increased BEV responsiveness and prolonged survival in ovarian tumor-bearing mice. S100B is a key molecule regulating ovarian cancer sensitivity to BEV. Paracrine S100B secreted by ovarian cancer cells acts on HUVECs, promoting angiogenesis through the FOXO1/β-catenin pathway. Pentamidine combined with BEV holds potential for overcoming BEV resistance in clinical use.

A risk prediction model of gene signatures in ovarian cancer through bagging of GA-XGBoost models

Ovarian cancer (OC) is one of the most frequent gynecologic cancers among women, and high-accuracy risk prediction techniques are essential to effectively select the best intervention strategies and clinical management for OC patients at different risk levels. Current risk prediction models used in OC have low sensitivity, and few of them are able to identify OC patients at high risk of mortality, which would both optimize the treatment of high-risk patients and prevent unnecessary medical intervention in those at low risk. To this end, we have developed a bagging-based algorithm with GA-XGBoost models that predicts the risk of death from OC using gene expression profiles. Four gene expression datasets from public sources were used as training (n = 1) or validation (n = 3) sets. The performance of our proposed algorithm was compared with fine-tuning and other existing methods. Moreover, the biological function of selected genetic features was further interpreted, and the response to a panel of approved drugs was predicted for different risk levels. The proposed algorithm showed good sensitivity (74-100%) in the validation sets, compared with two simple models whose sensitivity only reached 47% and 60%. The prognostic gene signature used in this study was highly connected to These findings demonstrated an improvement in the sensitivity of risk classification of OC patients with our risk prediction models compared with other methods. Ongoing effort is needed to validate the outcomes of this approach for precise clinical treatment.

The prognostic miR-532-5p-correlated ceRNA-mediated lipid droplet accumulation drives nodal metastasis of cervical cancer

The prognosis for cervical cancer (CC) patients with lymph node metastasis (LNM) is extremely poor. Lipid droplets (LDs) have a pivotal role in promoting tumor metastasis. The crosstalk mechanism between LDs and LNM modulated in CC remains largely unknown. This study aimed to construct a miRNA-dependent progonostic model for CC patients and investigate whether miR-532-5p has a biological impact on LNM by regualting LDs accumulation. LASSO-Cox regression was applied to establish a prognostic prediction model. miR-532-5p had the lowest P-value in RNA expression (P < 0.001) and prognostic prediction (P < 0.0001) and was selected for further study. The functional role of the prognostic miR-532-5p-correlated competing endogenous RNA (ceRNA) network was investigated to clarify the crosstalk between LDs and LNM. The underlying mechanism was determined using site-directed mutagenesis, dual luciferase reporter assays, RNA immunoprecipitation assays, and rescue experiments. A xenograft LNM model was established to evaluate the effect of miR-532-5p and orlistat combination therapy on tumor growth and LNM. A novel 5-miRNAs prognostic signature was constructed to better predict the prognosis of CC patient. Further study demonstrated that miR-532-5p inhibited epithelial-mesenchymal transition and lymphangiogenesis by regulating LDs accumulation. Interestingly, we also found that LDs accumulation promoted cell metastasis in vitro. Mechanistically, we demonstrated a miR-532-5p-correlated ceRNA network in which LINC01410 was bound directly to miR-532-5p and effectively functioned as miR-532-5p sponge to disinhibit its target gene-fatty acid synthase ( Our findings highlight a LD accumulation-dependent mechanism of miR-532-5p-modulated LNM and support treatment with miR-532-5p/orlistat as novel strategy for treating patients with LNM in CC.

Biomarkers differentiating regression from progression among untreated cervical intraepithelial neoplasia grade 2 lesions

Cervical intraepithelial neoplasia grade 2 (CIN2) is one of the precursor stages before cervical lesions develop into cervical cancer. The spontaneous development of CIN2 is ambiguous. One part of CIN2 lesions will progress to cervical intraepithelial neoplasia grade 3 or worse (CIN3+), another part will regress to cervical intraepithelial neoplasia grade 1 or less (CIN1-), and the last part will persist. Although the guidelines suggest that CIN2 patients with fertility requirements can be treated conservatively to minimize the risk of infertility and obstetric complications, most CIN2 patients undergo surgical treatment to prevent the progression of the disease, which will lead to over-treatment and unnecessary complications. The clinical outcome of CIN2 lesions is unpredictable and depends on histopathological examinations. Thus, it is necessary to identify the biomarkers differentiating regression lesions from progression lesions, which is conducive to supporting individualised treatment. The natural history of CIN2 is commonly regulated by the interaction of human papillomavirus (HPV) viral factors (HPV genotype and HPV methylation), host factors (p16/Ki-67 status, host gene methylation effects, human leukocyte antigen subtypes and immune microenvironment) and other factors (vaginal microbiota). This review summarized the biomarkers predicting the spontaneous regression of CIN2, which correlated with HPV infection, the (epi)genetic change of host genes and microenvironment change. However, potential biomarkers must be validated with prospective cohort studies, which should be conducted with expanded enrollment, a longer observational period and the tracking of more patients.

Integrated immunogenomic analysis of single-cell and bulk tissue transcriptome profiling unravels a macrophage activation paradigm associated with immunologically and clinically distinct behaviors in ovarian cancer

Increasing evidence demonstrates that the activation states and diverse spectrum of macrophage subtypes display dynamic heterogeneity in the tumor microenvironment, which plays a critical role in a variety of cancer types. To investigate the heterogeneity and the homeostasis of different macrophage subtypes, as well as their effect on biological and clinical manifestations of ovarian cancer (OV). Integrated immunogenomic analysis of single-cell and bulk tissuetranscriptome profiling was performed to systematically investigate the association between macrophage activation and prognostic and therapeutic efficacy. Consensus clustering analysis was used to define novel macrophage subtypes. An artificial neural network was used to simulate the dynamic activation of macrophages. The pan-cohort results suggested that high relative infiltration abundance of M0 and M1 macrophages was associated with improved outcome and therapeutic efficacy. However, it was the opposite for M2 macrophages. Unsupervised consensus clustering analysis revealed two OV subgroups characterized by a balance between M0, M1 and M2 macrophages with distinct clinical and immunological behaviors. Finally, a macrophage polarization-derived artificial neural network model was proposed to serve as a robust prognostic factor and predictive biomarker for therapeutic efficacy, which was validated in different independent patient cohorts. The present study provides a new understanding of macrophage heterogeneity and its association with OV prognosis and underlines the future clinical potential of a macrophage activation model for tumor prevention and treatment.

PIBF1 regulates multiple gene expression via impeding long-range chromatin interaction to drive the malignant transformation of HPV16 integration epithelial cells

Human papillomavirus (HPV) integration can induce gene expression dysregulation by destroying higher-order chromatin structure in cervical cancer. We established a 13q22 site-specific HPV16 gene knock-in cell model to interrogate the changes in chromatin structure at the initial stages of host cell malignant transformation. We designed a CRISPR-Cas9 system with sgRNA targeting 13q22 site and constructed the HPV16 gene donor. Cells were cotransfected, screened, and fluorescence sorted. The whole genome sequencing (WGS) was used to confirm the precise HPV16 gene integration site. Western blot and qRT-PCR were used to measure gene expression. In vitro and in vivo analysis were performed to estimate the tumorigenic potential of the HPV16 knock-in cell model. Combined Hi-C, chromatin immunoprecipitation and RNA sequencing analyses revealed correlations between chromatin structure and gene expression. We performed a coimmunoprecipitation assay with anti-PIBF1 antibody to identify endogenous interacting proteins. In vivo analysis was used to determine the role of PIBF1 in the tumor growth of cervical cancer cells. We successfully established a 13q22 site-specific HPV16 gene knock-in cell model. We found that HPV integration promoted cell proliferation, invasion and stratified growth in vitro, and monoclonal proliferation in vivo. HPV integration divided the affected topologically associated domain (TAD) into two smaller domains, and the progesterone-induced blocking factor 1 (PIBF1) gene near the integration site was upregulated, although PIBF1 was not enriched at the domain boundary by CUT-Tag signal analysis. Moreover, PIBF1 was found to interact with the cohesin complex off chromatin to reduce contact domain formation by disrupting the cohesin ring-shaped structure, causing dysregulation of tumorigenesis-related genes. Xenograft experiments determined the role of PIBF1 in the proliferation in cervical cancer cells. We highlight that PIBF1, a potential chromatin structure regulatory protein, is activated by HPV integration, which provides new insights into HPV integration-driven cervical carcinogenesis.

Sodium citrate targeting Ca2+/CAMKK2 pathway exhibits anti-tumor activity through inducing apoptosis and ferroptosis in ovarian cancer

Ovarian cancer (OC) is known for its high mortality rate. Although sodium citrate has anti-tumor effects in various cancers, its effect and mechanism in OC remain unclear. To analyze the inhibitory effect of sodium citrate on ovarian cancer cells and the underlying mechanism. Cell apoptosis was examined by TUNEL staining, flow cytometry, and ferroptosis was examined intracellular Fe This study suggested that sodium citrate not only promoted ovarian cancer cell apoptosis but also triggeredferroptosis, manifested as elevated levels of Fe These results revealed that the sodium citrate exerted its anti-cancer activity by inhibiting Ca

Safe and efficient 2D molybdenum disulfide platform for cooperative imaging-guided photothermal-selective chemotherapy: A preclinical study

The striking imbalance between the ever-increasing amount of nanomedicines and low clinical translation of products has become the focus of intense debate. For clinical translation, the critical issue is to select the appropriate agents and combination regimen for targeted diseases, not to prepare increasingly complex nanoplatforms. A safe and efficient platform, α-tocopheryl succinate (α-TOS) married 2D molybdenum disulfide, was devised by a facile method and applied for cooperative imaging-guided photothermal-selective chemotherapy of ovarian carcinoma. A novel platform of PEGylated α-TOS and folic acid (FA) conjugated 2D MoS The photothermal efficiency (65.3%) of the platform under safe near-infrared irradiation is much higher than that of other photothermal materials reported elsewhere. Moreover, the covalently linked α-TOS renders platform with selective chemotherapy for cancer cells. Remarkably, with these excellent properties, the platform can be used to completely eliminate the solid tumor by safe photothermal therapy, and then kill the residual cancer cells by selective chemotherapy to prevent tumor recurrence. More significantly, barely side effects occur in the whole treatment process. The excellent efficacy and safety benefits The safe and efficient platform might be a candidate of clinical nanomedicines for multimode theranostics. This study demonstrates an innovative thought in precise nanomedicine regarding the design of next generation of cancer theranostic protocol for potential clinical practice.

Dualistic classification of high grade serous ovarian carcinoma has its root in spatial heterogeneity

Widespread intra-peritoneal metastases is a main feature of high grade serous ovarian carcinoma (HGSOC). Recently, the extent of tumour heterogeneity was used to evaluate the cancer genomes among multi-regions in HGSOC. However, there is no consensus on the effect of tumour heterogeneity on the evolution of the tumour metastasis process in HGSOC. We performed whole-exome sequencing in multiple regions of matched primary and metastatic HGSOC specimens to reveal the genetic mechanisms of ovarian tumourigenesis and malignant progression. 63 samples (including ovarian carcinoma, omentum metastasis, and normal tissues) were used. We analyzed the genomic heterogeneity, traced the subclone dissemination and establishment history and compared the different genetic characters of cancer evolutionary models in HGSOC. We found that HGSOC had substantial intra-tumour heterogeneity (median 54.2, range 0 ∼ 106.7), high inter-patient heterogeneity (P < 0.001), but relatively limited intra-patient heterogeneity (P = 0.949). Two COSMIC mutational signatures were identified in HGSOCs: signature 3 was related to homologous recombination, and signature 1 was associated with aging. Two scenarios were identified by phylogenetic reconstruction in our study: 3 cases (33.3 %) showed star topology, and the other 6 cases (66.7 %) displayed tree topology. Compared with star topology group, more driver events were identified in tree topology group (P < 0.001), and occurred more frequently in early stage than in late stage of clonal evolution (P < 0.001). Moreover, compared with the star topology group, the tree topology group showed higher rate of intra-tumour heterogeneity (P = 0.045). A dualistic classification model was proposed for the classification of HGSOC based on spatial heterogeneity, which may contribute to better managing patients and providing individual treatment for HGSOC patients.