Identification and validation of a novel anoikis-related signature for predicting prognosis and immune landscape in ovarian serous cystadenocarcinoma
Yu-Ting Zhu,
Shuang-Yue Wu,
Song Yang,
Jie Ying,
Lu Tian,
Hong-Liang Xu,
He-Ping Zhang,
Hui Yao,
Wei-Yu Zhang,
Qin-Qin Jin,
Yin-Ting Yang,
Xi-Ya Jiang,
Nan Zhang,
Shun Yao,
Shu-Guang Zhou,
Guo Chen
Affiliations
Yu-Ting Zhu
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Shuang-Yue Wu
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Song Yang
Department of Pain Treatment, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230032, China
Jie Ying
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Lu Tian
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Hong-Liang Xu
Department of Pathology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
He-Ping Zhang
Department of Pathology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Hui Yao
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Wei-Yu Zhang
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Qin-Qin Jin
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Yin-Ting Yang
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Xi-Ya Jiang
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Nan Zhang
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Shun Yao
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China
Shu-Guang Zhou
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China; Corresponding author. Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China.
Guo Chen
Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China; Department of Gynecology, Anhui Province Maternity and Child Healthcare Hospital, Hefei, Anhui 230001, China; Corresponding author. Department of Gynecology, Maternal and Child Health Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230001, China.
Background: Ovarian serous cystadenocarcinoma (OSC) is the most prevalent histological subtype of ovarian cancer (OV) and presents a serious threat to women's health. Anoikis is an essential component of metastasis, and tumor cells can get beyond it to become viable. The impact of anoikis on OSC, however, has only been the topic of a few studies. Methods: The mRNA sequencing and clinical information of OSC came from The Cancer Genome Atlas Target Genotype-Tissue Expression (TCGA TARGET GTEx) dataset. Anoikis-related genes (ARGs) were collected by Harmonizome and GeneCards websites. Centered on these ARGs, we used unsupervised consensus clustering to explore potential tumor typing and filtered hub ARGs to create a model of predictive signature for OSC patients. Furthermore, we presented clinical specialists with a novel nomogram based on ARGs, revealing the underlying clinical relevance of this signature. Finally, we explored the immune microenvironment among various risk groups. Results: We identified 24 ARGs associated with the prognosis of OSC and classified OSC patients into three subtypes, and the subtype with the best prognosis was more enriched in immune-related pathways. Seven ARGs (ARHGEF7, NOTCH4, CASP2, SKP2, PAK4, LCK, CCDC80) were chosen to establish a risk model and a nomogram that can provide practical clinical decision support. Risk scores were found to be an independent and significant prognostic factor in OSC patients. The CIBERSORTx result revealed an inflammatory microenvironment is different for risk groups, and the proportion of immune infiltrates of Macrophages M1 is negatively correlated with risk score (rs = −0.21, P < 0.05). Ultimately, quantitative reverse transcription polymerase chain reaction (RT-PCR) was utilized to validate the expression of the seven pivotal ARGs. Conclusion: In this study, based on seven ARGs, a risk model and nomogram established can be used for risk stratification and prediction of survival outcomes in patients with OSC, providing a reliable reference for individualized therapy of OSC patients.
