Lu Zhang

Targeting of Tumoral NAC1 Mitigates Myeloid-Derived Suppressor Cell–Mediated Immunosuppression and Potentiates Anti–PD-1 Therapy in Ovarian Cancer

Abstract Epithelial ovarian cancer is the most common type of ovarian cancer with a low rate of response to immunotherapy such as immune checkpoint blockade therapy. In this study, we report that nucleus accumbens–associated protein 1 (NAC1), a putative driver of epithelial ovarian cancer, has a critical role in immune evasion. We showed in murine ovarian cancer models that depleting or inhibiting tumoral NAC1 reduced the recruitment and immunosuppressive function of myeloid-derived suppressor cells (MDSC) in the tumor microenvironment, led to significant increases of cytotoxic tumor-infiltrating CD8+ T cells, and promoted antitumor immunity and suppressed tumor progression. We further showed that tumoral NAC1 directly enhanced the transcription of CXCL16 by binding to CXCR6, thereby promoting MDSC recruitment to the tumor. Moreover, lipid C20:1T produced by NAC1-expressing tumor cells fueled oxidative metabolism of MDSCs and promoted their immune-suppressive function. We also showed that NIC3, a small-molecule inhibitor of NAC1, was able to sensitize mice bearing NAC1-expressing ovarian tumors to anti–PD-1 therapy. Our study reveals a critical role for NAC1 in controlling tumor infiltration of MDSCs and in modulating the efficacy of immune checkpoint blockade therapy. Thus, targeting of NAC1 may be exploited to sensitize ovarian cancer to immunotherapy.

Risk‐stratified management of cervical high‐grade squamous intraepithelial lesion based on machine learning

AbstractThe concordance rate between conization and colposcopy‐directed biopsy (CDB) proven cervical high‐grade squamous intraepithelial lesion (HSIL) were 64−85%. We aimed to identify the risk factors associated with pathological upgrading or downgrading after conization in patients with cervical HSIL and to provide risk‐stratified management based on a machine learning predictive model.This retrospective study included patients who visited the Obstetrics and Gynecology Hospital of Fudan University from January 1 to December 31, 2019, were diagnosed with cervical HSIL by CDB, and subsequently underwent conization. A wide variety of data were collected from the medical records, including demographic data, laboratory findings, colposcopy descriptions, and pathological results. The patients were categorized into three groups according to their postconization pathological results: low‐grade squamous intraepithelial lesion (LSIL) or below (downgrading group), HSIL (HSIL group), and cervical cancer (upgrading group). Univariate and multivariate analyses were performed to identify the independent risk factors for pathological changes in patients with cervical HSIL. Machine learning prediction models were established, evaluated, and subsequently verified using external testing data.In total, 1585 patients were included, of whom 65 (4.1%) were upgraded to cervical cancer after conization, 1147 (72.4%) remained having HSIL, and 373 (23.5%) were downgraded to LSIL or below. Multivariate analysis showed a 2% decrease in the incidence of pathological downgrade for each additional year of age and a 1% increase in lesion size. Patients with cytology > LSIL (odds ratio [OR] = 0.33; 95% confidence interval [CI], 0.21–0.52), human papillomavirus (HPV) infection (OR = 0.33; 95% CI, 0.14–0.81), HPV 33 infection (OR = 0.37; 95% CI, 0.18–0.78), coarse punctate vessels on colposcopy examination (OR = 0.14; 95% CI, 0.06–0.32), HSIL lesions in the endocervical canal (OR = 0.48; 95% CI, 0.30–0.76), and HSIL impression (OR = 0.02; 95% CI, 0.01–0.03) were less likely to experience pathological downgrading after conization than their counterparts. The independent risk factors for pathological upgrading to cervical cancer after conization included the following: age (OR = 1.08; 95% CI, 1.04–1.12), HPV 16 infection (OR = 4.07; 95% CI, 1.70–9.78), the presence of coarse punctate vessels during colposcopy examination (OR = 2.21; 95% CI, 1.08–4.50), atypical vessels (OR = 6.87; 95% CI, 2.81–16.83), and HSIL lesions in the endocervical canal (OR = 2.91; 95% CI, 1.46–5.77). Among the six machine learning prediction models, the back propagation (BP) neural network model demonstrated the highest and most uniform predictive performance in the downgrading, HSIL, and upgrading groups, with areas under the curve (AUCs) of 0.90, 0.84, and 0.69; sensitivities of 0.74, 0.84, and 0.42; specificities of 0.90, 0.71, and 0.95; and accuracies of 0.74, 0.84, and 0.95, respectively. In the external testing set, the BP neural network model showed a higher predictive performance than the logistic regression model, with an overall AUC of 0.91. Therefore, a web‐based prediction tool was developed in this study.BP neural network prediction model has excellent predictive performance and can be used for the risk stratification of patients with CDB‐diagnosed HSIL.

SLAMF7 predicts prognosis and correlates with immune infiltration in serous ovarian carcinoma

Signaling lymphocytic activation molecule family members (SLAMFs) play a critical role in immune regulation of malignancies. This study aims to investigate the prognostic value and function of SLAMFs in ovarian cancer (OC). The expression analysis of SLAMFs was conducted based on The Cancer Genome Atlas Ovarian Cancer Collection (TCGA-OV) and Gene Expression Omnibus (GEO) databases. Immunohistochemistry (IHC) was further performed on tissue arrays (n=98) to determine the expression of SLAMF7. Kaplan-Meier plotter and multivariate Cox regression model were used to evaluate the correlation of SLAMF7 expression with survival outcomes of patients. The molecular function of SLAMF7 in OC was further investigated using Gene Set Enrichment Analysis (GSEA). SLAMF7 mRNA expression were significantly upregulated in OC tumor tissue compared to normal tissue. IHC revealed that SLAMF7 expression was located in the interstitial parts of tumor tissue, and higher SLAMF7 expression was associated with favorable survival outcomes. GSEA demonstrated that SLAMF7 is involved immune-related pathways. Further analysis showed that SLAMF7 had a strong correlation with the T cell-specific biomarker (CD3) but not with the B cell (CD19, CD22, and CD23) and natural killer cell-specific biomarkers (CD85C, CD336, and CD337). Furthermore, IHC analysis confirmed that SLAMF7 was expressed in tumor-infiltrating T cells, and the IHC score of SLAMF7 was positively correlated with CD3 (r=0.85, p<0.001). SLAMF7 is expressed in the interstitial components of clinical OC tissue, and higher SLAMF7 expression indicated a favorable prognosis for patients with OC. Additionally, SLAMF7 is involved in T-cell immune infiltration in OC.

Cervical metastasis of breast cancer: A case report and literature review

Rationale: Cervical metastasis of breast cancer is rare and its clinical manifestations are similar to those of primary cervical cancer. It is thus easy to misdiagnose, with diagnosis mainly depending on pathology and immunohistochemistry. There have been few studies on its treatment and there is thus no standard treatment plan. Patient concerns: This is a 64-year-old female patient presented with a 2-month history of abnormal postmenopausal vaginal discharge, who had previous history of breast cancer. Diagnoses: Based on the gynecological examination, imaging results, pathology, and immunohistochemical results, a diagnosis of metastatic carcinoma of the cervix and breast cancer was confirmed. Interventions: She received computed tomography-guided 3-dimensional high-dose-rate brachytherapy in combination with chemotherapy. Outcomes: She achieved complete response locally. This case provides a new local treatment option for patients with inoperable localized cervical metastases. Lessons: We hope that this report and the accompanying review help to enrich the literature pertaining to the treatment of rare cervical metastases, providing a foundation for the improved survival of affected patients.

Successful treatment of a rare giant accessory cavitated uterine mass: a case report

An accessory cavitated uterine mass (ACUM) is a very rare obstructive genital malformation characterized by pelvic pain and severe dysmenorrhea. It is easily mistaken for other obstructive genital malformations in women, such as cystic uterine adenomyosis or cystic degeneration of uterine fibroids. This case report describes a 30-year-old patient with a huge uterine cornual mass. Successful resection was performed by surgical excision, and the lesion was diagnosed as an ACUM. Given the rarity of a giant ACUM, this report also includes a brief review of the relevant literature.