Jiaxing Lin1, Xiao Xu2, Dan Sun1, Tianren Li3. 1. Department of Urology, The First Hospital of China Medical University, Shenyang, China. 2. Department of Pediatric Intensive Care Unit, The Shengjing Hospital of China Medical University, Shenyang, China. 3. Department of Gynaecology, The First Hospital of China Medical University, Shenyang, China.
Abstract
BACKGROUND: High-grade serous ovarian cancer (HGSOC) is a common cause of death from gynecological cancer, with an overall survival rate that has not significantly improved in decades. Reliable bio-markers are needed to identify high-risk HGSOC to assist in the selection and development of treatment options. METHOD: The study included ten HGSOC cohorts, which were merged into four separate cohorts including a total of 1,526 samples. We used the relative expression of immune genes to construct the gene-pair matrix, and the least absolute shrinkage and selection operator regression was performed to build the prognosis model using the training set. The prognosis of the model was verified in the training set (363 cases) and three validation sets (of 251, 354, and 558 cases). Finally, the differences in immune cell infiltration and gene enrichment pathways between high and low score groups were identified. RESULTS: A prognosis model of HGSOC overall survival rate was constructed in the training set, and included data for 35 immune gene-related gene pairs and the regression coefficients. The risk stratification of HGSOC patients was successfully performed using the training set, with a p-value of Kaplan-Meier of < 0.001. A score from this model is an independent prognostic factor of HGSOC, and prognosis was evaluated in different clinical subgroups. This model was also successful for the other three validation sets, and the results of Kaplan-Meier analysis were statistically significant (p < 0.05). The model can also predict patient progression-free survival with HGSOC to reflect tumor growth status. There was a lower infiltration level of M1 macrophages in the high-risk group compared to that in the low-risk group (p < 0.001). Finally, the immune-related pathways were enriched in the low-risk group. CONCLUSION: The prognostic model based on immune-related gene pairs developed is a potential prognostic marker for high-grade serous ovarian cancer treated with platinum. The model has robust prognostic ability and wide applicability. More prospective studies will be needed to assess the practical application of this model for precision therapy.
BACKGROUND: High-grade serous ovarian cancer (HGSOC) is a common cause of death from gynecological cancer, with an overall survival rate that has not significantly improved in decades. Reliable bio-markers are needed to identify high-risk HGSOC to assist in the selection and development of treatment options. METHOD: The study included ten HGSOC cohorts, which were merged into four separate cohorts including a total of 1,526 samples. We used the relative expression of immune genes to construct the gene-pair matrix, and the least absolute shrinkage and selection operator regression was performed to build the prognosis model using the training set. The prognosis of the model was verified in the training set (363 cases) and three validation sets (of 251, 354, and 558 cases). Finally, the differences in immune cell infiltration and gene enrichment pathways between high and low score groups were identified. RESULTS: A prognosis model of HGSOC overall survival rate was constructed in the training set, and included data for 35 immune gene-related gene pairs and the regression coefficients. The risk stratification of HGSOC patients was successfully performed using the training set, with a p-value of Kaplan-Meier of < 0.001. A score from this model is an independent prognostic factor of HGSOC, and prognosis was evaluated in different clinical subgroups. This model was also successful for the other three validation sets, and the results of Kaplan-Meier analysis were statistically significant (p < 0.05). The model can also predict patient progression-free survival with HGSOC to reflect tumor growth status. There was a lower infiltration level of M1 macrophages in the high-risk group compared to that in the low-risk group (p < 0.001). Finally, the immune-related pathways were enriched in the low-risk group. CONCLUSION: The prognostic model based on immune-related gene pairs developed is a potential prognostic marker for high-grade serous ovarian cancer treated with platinum. The model has robust prognostic ability and wide applicability. More prospective studies will be needed to assess the practical application of this model for precision therapy.
Authors: Lindsey A Torre; Britton Trabert; Carol E DeSantis; Kimberly D Miller; Goli Samimi; Carolyn D Runowicz; Mia M Gaudet; Ahmedin Jemal; Rebecca L Siegel Journal: CA Cancer J Clin Date: 2018-05-29 Impact factor: 508.702
Authors: Charlotte Rolny; Massimiliano Mazzone; Sònia Tugues; Damya Laoui; Irja Johansson; Cathy Coulon; Mario Leonardo Squadrito; Inmaculada Segura; Xiujuan Li; Ellen Knevels; Sandra Costa; Stefan Vinckier; Tom Dresselaer; Peter Åkerud; Maria De Mol; Henriikka Salomäki; Mia Phillipson; Sabine Wyns; Erik Larsson; Ian Buysschaert; Johan Botling; Uwe Himmelreich; Jo A Van Ginderachter; Michele De Palma; Mieke Dewerchin; Lena Claesson-Welsh; Peter Carmeliet Journal: Cancer Cell Date: 2011-01-06 Impact factor: 31.743