Yi Zheng

The relationship of C-Reactive Protein to Albumin Ratio and interval debulking surgery outcome after neoadjuvant chemotherapy in ovarian cancer patients

To investigate the relationship between the changes of C-reactive protein to Albumin Ratio (CAR) levels and Interval Debulking Surgery (IDS) outcome after Neoadjuvant Chemotherapy (NAC) in ovarian cancer patients. A nested case-control study for 209 patients with ovarian cancer who received NAC-IDS therapy from the First Affiliated Hospital of Bengbu Medical College between 2015‒2021 was conducted. Demographic data, laboratory indicators, and imaging examinations were collected. The outcome was regarded as optimal IDS in this study. Univariate and multivariate logistic regression analyses were performed to assess the relationship of CAR before NAC, CAR after NAC and ∆CAR with optimal IDS. The authors also performed the subgroup analysis based on menopausal state. The end time of follow-up was January 24, 2022. A total of 156 patients had been treated with optimal IDS, and 53 with suboptimal IDS. After adjusting age, body mass index, menopausal state, NAC drug, peritoneal perfusion and CAR before NAC, the result showed that CAR after NAC (Odds Ratio [OR = 3.48], 95% Confidence Interval [95% CI 1.28‒9.48], p = 0.015) and ∆CAR (OR = 0.29, 95% CI 0.11‒0.78, p = 0.015) were associated with optimal IDS, respectively. Additionally, the authors found a significant correlation between CAR after NAC and optimal IDS (OR = 3.16, 95% CI 1.07‒9.35, p = 0.038), and ∆CAR and optimal IDS (OR = 0.32, 95% CI 0.11‒0.94, p = 0.038) among ovarian cancer patients with menopause. CAR after NAC and ∆CAR were independent prognostic markers of optimal interval debulking surgery for ovarian cancer patients.

PHF6 promotes the progression of endometrial carcinoma by increasing cancer cells growth and decreasing T‐cell infiltration

AbstractUterine corpus endometrial carcinoma (UCEC) is the most common cancer of the female reproductive tract. The overall survival of advanced and recurrent UCEC patients is still unfavourable nowadays. It is urgent to find a predictive biomarker and block tumorgenesis at an early stage. Plant homeodomain finger protein 6 (PHF6) is a key player in epigenetic regulation, and its alterations lead to various diseases, including tumours. Here, we found that PHF6 expression was upregulated in UCEC tissues compared with normal tissues. The UCEC patients with high PHF6 expression had poor survival than UCEC patients with low PHF6 expression. PHF6 mutation occurred in 12% of UCEC patients, and PHF6 mutation predicted favourable clinical outcome in UCEC patients. Depletion of PHF6 effectively inhibited HEC‐1‐A and KLE cell proliferation in vitro and decreased HEC‐1‐A cell growth in vivo. Furthermore, high PHF6 level indicated a subtype of UCECs characterized by low immune infiltration, such as CD3+ T‐cell infiltration. While knockdown of PHF6 in endometrial carcinoma cells increased T‐cell migration by promoting IL32 production and secretion. Taken together, our findings suggested that PHF6 might play an oncogenic role in UCEC patients. Thus, PHF6 could be a potential biomarker in predicting the prognosis of UCEC patients. Depletion of PHF6 may be a novel therapeutic strategy for UCEC patients.

Predictive role of HPGD gene in carcinogenesis and immune environment monitoring in human cervical cancer

Background 15-Hydroxyprostaglandin dehydrogenase (15-PGDH, gene symbol HPGD) is considered a tumor suppressor, and its expression is often proportional to the anticancer response. However, the clinical significance of HPGD/15-PGDH in predicting immune response and its diagnosis and prognosis value in cervical cancer remains unclear. Objective This study aims to explore the clinical significance of HPGD/15-PGDH in predicting carcinogenesis, prognosis, and sensitivity to immuno- and chemotherapy in cervical cancer. Methods A comprehensive evaluation of the diagnostic, treatment-sensitive, and prognostic value of HPGD/15-PGDH in cervical cancer was conducted by bioinformatics analysis of public databases and validation of real cohort data. Results Bioinformatics analysis showed that HPGD expression was decreased in cervical cancer and did not independently predict patient prognosis. Low HPGD expression was linked to resistance to certain chemotherapies, potentially due to immunosuppression triggered by low HPGD levels. Validation in clinical samples from the local hospital confirmed the decreased 15-PGDH expression and increased COX-2 expression in HPV16-positive cervical cancer patients and increased immune suppression during cancer progression. Conclusions HPGD/15-PGDH is a potential biomarker for predicting the progression, immune response, and chemotherapy sensitivity of cervical cancer, with implications that it is of great value for the diagnosis and individual-based treatment of cervical cancer.

Identification of a glycolysis‐related gene signature for survival prediction of ovarian cancer patients

Abstract Background Ovarian cancer (OV) is deemed the most lethal gynecological cancer in women. The aim of this study was to construct an effective gene prognostic model for predicting overall survival (OS) in patients with OV. Methods The expression profiles of glycolysis‐related genes (GRGs) and clinical data of patients with OV were extracted from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analyses were conducted, and a prognostic signature based on GRGs was constructed. The predictive ability of the signature was analyzed using training and test sets. Results A gene risk signature based on nine GRGs ( ISG20 , CITED2 , PYGB , IRS2 , ANGPTL4 , TGFBI , LHX9 , PC , and DDIT4 ) was identified to predict the survival outcome of patients with OV. The signature showed a good prognostic ability for OV, particularly high‐grade OV, in the TCGA dataset, with areas under the curve (AUC) of 0.709 and 0.762 for 3‐ and 5‐year survival, respectively. Similar results were found in the test sets, and the AUCs of 3‐, 5‐year OS were 0.714 and 0.772 in the combined test set. And our signature was an independent prognostic factor. Moreover, a nomogram combining the prediction model and clinical factors was developed. Conclusion Our study established a nine‐GRG risk model and nomogram to better predict OS in patients with OV. The risk model represents a promising and independent prognostic predictor for patients with OV. Moreover, our study on GRGs could offer guidance for the elucidation of underlying mechanisms in future studies.