Investigator

Weiwei Feng

Ruijin Hospital

WFWeiwei Feng
Papers(8)
Modification‐Driven N…Red blood cell–hitchh…Impact of peritoneal …Circulating tumor DNA…Identification and Va…Intraoperative frozen…Can surgery boost the…Development and valid…
Collaborators(10)
Yudong WangKeqin HuaXipeng WangXiaorong QiXiaoxia CheXin GuanXin HeXinyu QuYan DingYijing Lin
Institutions(5)
Ruijin HospitalInternational Peace M…Obstetrics and Gyneco…Dalian Jiaotong Unive…West China Second Uni…

Papers

Modification‐Driven Nanocarriers: Ovarian Cancer Cell Membrane– Camouflaged Indoximod/Doxorubicin Co‐Delivery Systems for Synergistic Immunochemotherapy

ABSTRACT Among the three primary gynecological malignancies, ovarian cancer has the highest mortality rate, and its onset is often insidious. Despite standard treatments, relapse and drug resistance remain major challenges. Doxorubicin (DOX) is known to induce immunogenic cell death (ICD); however, some patients still experience tumor resistance and recurrence owing to tumor‐driven immunosuppression. Indoleamine 2,3‐dioxygenase (IDO), which is highly expressed in tumor tissues, impairs T‐cell function and differentiation, thereby promoting immunosuppression. Consequently, combining the IDO inhibitor indoximod (IND) with DOX may reverse immunosuppression and enhance both T‐cell–mediated and ICD‐driven anticancer effects. However, both drugs are limited by high systemic toxicity and poor tumor targeting, necessitating the use of nanocarriers to improve delivery efficiency and minimize toxicity. This study aims to develop novel cell membrane–camouflaged liposomes capable of co‐delivering IND and DOX (DOX/IND@cmLPs) for ovarian cancer therapy and to evaluate its anticancer effects in vitro and in vivo. The particle size of DOX/IND@cmLPs is measured as 111.7 ± 2.7 nm using a Malvern Zetasizer Pro, with a zeta potential of −22.4 ± 4.00 mV. Entrapment efficiency (EE) is assessed using ultra‐high performance liquid chromatography and ultraviolet spectrophotometry, yielding EE values of 85.1% ± 3.4% for DOX and 23.9% ± 1.3% for IND. At both pH 7.4 and pH 5.5, DOX release from DOX/IND@cmLPs is rapid during the first 24 hours, followed by a slower, more sustained release. Coomassie Brilliant Blue staining and Western Blot analysis confirmed successful encapsulation of the cell membrane in the liposomes. The potent antitumor effect of DOX/IND@cmLPs is demonstrated via CellTiter‐Glo assays in vitro. Flow cytometry and immunofluorescence staining revealed an increased ratio of CD8 + T cells to Treg cells in tumor tissues, suggesting that DOX/IND@cmLPs may partially reverse local tumor‐induced immunosuppression. Reduced Ki‐67 expression and increased TdT‐mediated dUTP nick‐end labeling positive cell ratios in tumor sections indicated that DOX/IND@cmLPs treatment suppressed tumor proliferation and promoted apoptosis. Immunohistochemistry showed alterations in mammalian target of rapamycin (mTOR)‐related pathway proteins in tumors. Furthermore, DOX/IND@cmLPs could induce an abscopal effect and provide long‐lasting tumor suppression in a subcutaneous mouse model. In this study, a formulation of DOX/IND‐loaded liposomes camouflaged with ovarian cancer cell membranes is successfully developed, and their stable physicochemical properties are confirmed. As an effective nanodrug delivery system, DOX/IND@cmLPs exhibited enhanced tumor‐targeting and immune‐mediated anticancer activity both in vitro and in vivo, indicating their potential as a platform for future combined chemotherapy and immunotherapy.

Circulating tumor DNA as a prognostic marker in high-risk endometrial cancer

Abstract Background Currently, there is no reliable blood-based marker to track tumor recurrence in endometrial cancer (EC) patients. Liquid biopsies, specifically, circulating tumor DNA (ctDNA) analysis emerged as a way to monitor tumor metastasis. The objective of this study was to examine the feasibility of ctDNA in recurrence surveillance and prognostic evaluation of high-risk EC. Methods Tumor tissues from nine high-risk EC patients were collected during primary surgery and tumor DNA was subjected to next generation sequencing to obtain the initial mutation spectrum using a 78 cancer-associated gene panel. Baseline and serial post-operative plasma samples were collected and droplet digital PCR (ddPCR) assays for patient-specific mutations were developed to track the mutations in the ctDNA in serial plasma samples. Log-rank test was used to assess the association between detection of ctDNA before or after surgery and disease-free survival. Results Somatic mutations were identified in all of the cases. The most frequent mutated genes were PTEN , FAT4 , ARID1A , TP53 , ZFHX3 , ATM , and FBXW7 . For each patient, personalized ddPCR assays were designed for one-to-three high-frequent mutations. DdPCR analysis and tumor panel sequencing had a high level of agreement in the assessment of the mutant allele fractions in baseline tumor tissue DNA. CtDNA was detected in 67% (6 of 9) of baseline plasma samples, which was not predictive of disease-free survival (DFS). CtDNA was detected in serial post-operative plasma samples (ctDNA tracking) of 44% (4 of 9) of the patients, which predicted tumor relapse. The DFS was a median of 9 months (ctDNA detected) versus median DFS undefined (ctDNA not detected), with a hazard ratio of 17.43 (95% CI, 1.616–188.3). The sensitivity of post-operative ctDNA detection in estimating tumor relapse was 100% and specificity was 83.3%, which was superior to CA125 or HE4. Conclusions Personalized ctDNA detection was effective and stable for high-risk EC. CtDNA tracking in post-operative plasma is valuable for predicting tumor recurrence.

Identification and Validation of NK Marker Genes in Ovarian Cancer by scRNA-seq Combined with WGCNA Algorithm

Background. As an innate immune system effector, natural killer cells (NK cells) play a significant role in tumor immunotherapy response and clinical outcomes. Methods. In our investigation, we collected ovarian cancer samples from TCGA and GEO cohorts, and a total of 1793 samples were included. In addition, four high-grade serous ovarian cancer scRNA-seq data were included for screening NK cell marker genes. Weighted gene coexpression network analysis (WGCNA) identified core modules and central genes associated with NK cells. The “TIMER,” “CIBERSORT,” “MCPcounter,” “xCell,” and “EPIC” algorithms were performed to predict the infiltration characteristics of different immune cell types in each sample. The LASSO-COX algorithm was employed to build risk models to predict prognosis. Finally, drug sensitivity screening was performed. Results. We first scored the NK cell infiltration of each sample and found that the level of NK cell infiltration affected the clinical outcome of ovarian cancer patients. Therefore, we analyzed four high-grade serous ovarian cancer scRNA-seq data, screening NK cell marker genes at the single-cell level. The WGCNA algorithm screens NK cell marker genes based on bulk RNA transcriptome patterns. Finally, a total of 42 NK cell marker genes were included in our investigation. Among which, 14 NK cell marker genes were then used to develop a 14-gene prognostic model for the meta-GPL570 cohort, dividing patients into high-risk and low-risk subgroups. The predictive performance of this model has been well-verified in different external cohorts. Tumor immune microenvironment analysis showed that the high-risk score of the prognostic model was positively correlated with M2 macrophages, cancer-associated fibroblast, hematopoietic stem cell, stromal score, and negatively correlated with NK cell, cytotoxicity score, B cell, and T cell CD4+Th1. In addition, we found that bleomycin, cisplatin, docetaxel, doxorubicin, gemcitabine, and etoposide were more effective in the high-risk group, while paclitaxel had a better therapeutic effect on patients in the low-risk group. Conclusion. By utilizing NK cell marker genes in our investigation, we developed a new feature that is capable of predicting patients’ clinical outcomes and treatment strategies.

Can surgery boost the survival benefit of chemoradiotherapy in T1b1-T2a1 stage cervical cancer with lymph node metastasis? A population-based study

This study aimed to determine whether surgery followed by adjuvant chemoradiotherapy has superior survival outcomes for node-positive patients with T1b1-T2a1 stage cervical cancer compared with those who undergo chemoradiation. We investigated the Surveillance, Epidemiology, and End Results database for 12,701 patients diagnosed between 2000 and 2018. Patients were stratified according to different T stages and different treatment strategies. Surgery included radical hysterectomy (RH) or total hysterectomy (TH). Radiotherapy (RT) included adjuvant chemoradiation or chemoradiation alone. Cox analyses were performed to select the clinically important factors of survival outcomes. Survival analysis was used to compare those who received different treatment methods. A total of 12,701 International Federation of Gynecology and Obstetrics 2018 stage IIIC cervical cancer patients were identified. The risk of overall survival (OS) was significantly different between patients who received and did not receive chemoradiotherapy in the T categories. In the propensity-score matched dataset, early-T stage (T1b1 and T1b2) and node-positive patients in the "RH+RT" and "TH+RT" groups had better disease-specific survival (DSS) than those in the RT group. No difference in DSS was observed between the "surgery following RT" group and the RT group in locally advanced stage (T1b3 and T2a1, node positive) patients. Regarding T1b1-T2a1 node-positive patients, the RH+RT group had a similar survival outcome to that in the TH+RT group. We showed that surgery following RT benefits early-T stage (T1b1 and T1b2) cervical cancer patients with lymph node metastasis. For locally advanced stages (T1b3 and T2a1), surgery and RT had similar survival outcomes.

Development and validation of real-time recombinase polymerase amplification-based assays for detecting HPV16 and HPV18 DNA

ABSTRACT Cervical cancer is the fourth leading cause of cancer-related death among women worldwide. Persistent human papillomavirus (HPV) infection is the principal cause of cervical cancer, with HPV16 and HPV18 accounting for about 70% of cases worldwide. Cervical screening is an effective secondary measure for preventing cervical cancer. Testing for HPV DNA is becoming increasingly important in cervical cancer screening. The existing PCR-based HPV detection technology has several disadvantages: the assays are time-consuming, and sophisticated equipment is required to control the temperature cycles. These drawbacks have led to the development of detection technologies based on isothermal amplification. Here, we present real-time recombinase polymerase amplification (RPA-exo)-based assays for single genotyping of either the E7 or the L1 segment of HPV16 or HPV18. These assays were highly sensitive, able to detect HPV in all clinical samples with Ct values below 34, and yielded results within 25 min. A dual-detection system capable of detecting both HPV16 and HPV18 in a single reaction was also developed based on the L1 gene. It has a limit of detection of approximately 10,000 copies of each genotype per reaction. The assays were validated with DNA extracted from 36 biopsy specimens and 42 exfoliated cell samples from 43 patients with cervical lesions at different stages. The RPA-exo system is a promising clinical detection platform with the advantages of yielding results rapidly and operating at a constant temperature, while being cost-effective and easy to use. IMPORTANCE HPV DNA screening is an effective approach for the prevention of cervical cancer. The novel real-time recombinase polymerase amplification-based HPV detection systems we developed constitute an improvement over the HPV detection methods currently used in clinical practice and should help to extend cervical cancer screening in the future, particularly in point-of-care test settings.

1Works
8Papers
29Collaborators
1Trials
Ovarian NeoplasmsNeoplasm StagingPrognosisCell Line, TumorPapillomavirus InfectionsEarly Detection of CancerTumor Microenvironment