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Khumukcham SS, Manavathi B. Two decades of a protooncogene HPIP/PBXIP1: Uncovering the tale from germ cell to cancer. Biochim Biophys Acta Rev Cancer 2021; 1876:188576. [PMID: 34090932 DOI: 10.1016/j.bbcan.2021.188576] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 05/25/2021] [Accepted: 05/28/2021] [Indexed: 01/17/2023]
Abstract
Hematopoietic PBX interacting protein (HPIP or pre-B-cell leukemia transcription factor interacting protein (PBXIP1) was discovered two decades ago as a corepressor of pre-B-cell leukemia homeobox (PBX) 1 with a vital functional role in hematopoiesis. Later it emerged as a potential biomarker of poor prognosis and tumorigenesis for more than a dozen different cancers. It regulates aggressive cancer phenotypes, cell proliferation, metastasis, EMT, etc. The anomaly in the regulation of HPIP is linked with physiological disorders like renal fibrosis, chronic kidney disease and osteoarthritis. Scientists have unraveled more than twenty interacting proteins of HPIP and its functional role in various physiological and cellular processes that involves normal neuronal development, embryogenesis, endometrium decidualization, and germ cell proliferation. Over the past 20 years, we have witnessed the emerging role of HPIP and its association with a myriad of cellular activities ranging from germ cell proliferation to cancer aggressiveness, modulating multitude of signaling cascades like TGF-β1, PI3K/AKT, Wnt, mTOR, and Sonic hedgehog signaling pathways. This review will give the current understanding of HPIP, in terms of its diverse functions, theoretical ideas, and further explore cellular links and promising areas that need to be investigated. We also provide a comprehensive overview of the transcript variants of HPIP and distinct sets of transcription factors regulating their expression, which may help to understand the role of HPIP in various cellular or physiological conditions.
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Affiliation(s)
- Saratchandra Singh Khumukcham
- Molecular and Cellular Oncology Laboratory, Department of Biochemistry, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana, India
| | - Bramanandam Manavathi
- Molecular and Cellular Oncology Laboratory, Department of Biochemistry, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana, India.
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2
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Yang Z, Hou Y, Lyu J, Liu D, Chen Z. Dynamic prediction and prognostic analysis of patients with cervical cancer: a landmarking analysis approach. Ann Epidemiol 2020; 44:45-51. [PMID: 32220511 DOI: 10.1016/j.annepidem.2020.01.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Revised: 01/20/2020] [Accepted: 01/22/2020] [Indexed: 01/21/2023]
Abstract
PURPOSE Providing up-to-date information on patient prognosis is important in determining the optimal treatment strategies. The currently available prediction models, such as the Cox model, are limited to making predictions from baseline and do not consider the time-varying effects of covariates. METHODS A total of 1501 cervical cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database were included. We introduced three landmark dynamic prediction models (models 1-3) that explore the dynamic effects of prognostic factors to obtain 5-year dynamic survival rate predictions at different prediction times. The performances of these models were evaluated by Harrell's C-index and the Brier score using cross-validation. RESULTS Some variables did not meet the proportional hazards assumption, indicating that the constant hazard ratios were unreliable. Model 3, which showed the best performance for prediction, was selected as the final model. Significant time-varying effects were observed for age at diagnosis, International Federation of Gynecology and Obstetrics (FIGO) stage, lymph node metastasis, and histological subtypes. Three patients were as examples used to illustrate how the predicted probabilities change at different prediction times during follow-up. CONCLUSIONS Model 3 can effectively incorporate covariates with time-varying effects and update the probability of surviving an additional 5 years at different prediction times. The use of the landmark approach may provide evidence for clinical decision making by updating personalized information for patients.
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Affiliation(s)
- Zijing Yang
- Department of Biostatistics, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, P.R. China
| | - Yawen Hou
- Department of Statistics, Jinan University, Guangzhou, P.R. China
| | - Jingjing Lyu
- Department of Biostatistics, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, P.R. China
| | - Di Liu
- Department of Oncology, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P.R. China
| | - Zheng Chen
- Department of Biostatistics, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, P.R. China.
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Yang J, Tian G, Pan Z, Zhao F, Feng X, Liu Q, Lyu J. Nomograms for predicting the survival rate for cervical cancer patients who undergo radiation therapy: a SEER analysis. Future Oncol 2019; 15:3033-3045. [PMID: 31452393 DOI: 10.2217/fon-2019-0029] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Aim: To integrate multiple independent risk factors to establish prognostic nomograms for better predicting overall survival and disease-specific survival in patients with cervical cancer receiving radiation therapy. Materials & methods: Cox analysis used to construct nomograms. The C-index, time-dependent receiver operating characteristic and calibration plots were used to evaluate the performance. The discrimination abilities were compared using the decision curve analysis, net reclassification improvement and integrated discrimination improvement. Results: After randomization, 2869 and 1230 cervical cancer patients were included in the training and validation sets, respectively. Nomograms that incorporated all of the significant independent factors for predicting the 3- and 5-year overall survival and disease-specific survival in the training cohort were established. Conclusion: Compared with the International Federation of Gynecology and Obstetrics staging system, the proposed nomograms exhibit superior prognostic discrimination and survival prediction.
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Affiliation(s)
- Jin Yang
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China.,School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, PR China
| | - Guoxiang Tian
- Seventh Medical Center, PLA General Hospital, Beijing, 100853, PR China
| | - Zhenyu Pan
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China.,School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, PR China.,Department of Pharmacy, The Affiliated Children Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China
| | - Fanfan Zhao
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China.,School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, PR China
| | - Xiaojie Feng
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China.,School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, PR China
| | - Qingqing Liu
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China.,School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, PR China
| | - Jun Lyu
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, PR China.,School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, PR China
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Cheng L, Zhao T, Li S, Wang Y, Fei H, Meng F. Overexpression of HPIP as a biomarker for metastasis and prognosis prediction in endometrial cancer patients. J Clin Lab Anal 2019; 33:e22959. [PMID: 31241209 PMCID: PMC6805295 DOI: 10.1002/jcla.22959] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 05/26/2019] [Accepted: 06/03/2019] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Hematopoietic pre-B-cell leukemia transcription factor (PBX)-interacting protein (HPIP) has shown to be overexpressed in several human cancers. The purpose of this study was to explore the expression of HPIP in endometrial cancer (EC) and its associated effects on disease. METHODS A total of 113 EC patients at the Harbin Medical University Cancer Hospital between August 2011 and September 2012 were studied for immunohistochemistry analysis. HPIP expression was detected using real-time reverse transcription PCR, Western blotting, and immunohistochemistry. Prognostic value of HPIP expression was examined using multivariate Cox regression analysis and Kaplan-Meier method. RESULTS The result of Western blotting indicated that HPIP protein expression is significantly high in normal tissues compared to EC tissues (P < 0.001). The expression of HPIP was significantly associated with FIGO stage (P < 0.001), histological grade (P < 0.001), depth of myometrial invasion (P < 0.001), and lymph node metastasis (P = 0.033). Kaplan-Meier analysis demonstrated that there was a significant difference in overall survival and disease-free survival between the two groups of patients stratified by HPIP expression level (log-rank, both P = 0.002). Patients with HPIP high expression had significantly shorter median survival time than those with HPIP low expression. Moreover, results of the multivariate analysis revealed that HPIP expression was an independent prognostic factor for predicting overall survival (P = 0.015) and disease-free survival (P = 0.017) in patients with EC. CONCLUSION The present study provides evidence that HPIP predicts EC progression and poor survival, highlighting its potential as a therapeutic target for EC.
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Affiliation(s)
- Li Cheng
- Department of Obstetrics and Gynecology, The Seventh Affiliated Hospital, Sun-Yat sen University, Shenzhen, Guangdong Province, China
| | - Tingting Zhao
- Department of Obstetrics and Gynecology, The Seventh Affiliated Hospital, Sun-Yat sen University, Shenzhen, Guangdong Province, China
| | - Shiguo Li
- Department of Obstetrics and Gynecology, The Seventh Affiliated Hospital, Sun-Yat sen University, Shenzhen, Guangdong Province, China
| | - Yao Wang
- Department of Obstetrics and Gynecology, The Daqing Oilfield General Hospital, Daqing, Heilongjiang, China
| | - Hui Fei
- Department of Obstetrics and Gynecology, The Seventh Affiliated Hospital, Sun-Yat sen University, Shenzhen, Guangdong Province, China
| | - Fanling Meng
- Department of Gynaecology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
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Wang C, Yang C, Wang W, Xia B, Li K, Sun F, Hou Y. A Prognostic Nomogram for Cervical Cancer after Surgery from SEER Database. J Cancer 2018; 9:3923-3928. [PMID: 30410596 PMCID: PMC6218784 DOI: 10.7150/jca.26220] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Accepted: 08/01/2018] [Indexed: 12/11/2022] Open
Abstract
Background: To develop and validate a nomogram based on the conventional measurements and log of odds between the number of positive lymph node and the number of negative lymph node (LODDS) in predicting prognosis for cervical cancer patients after surgery. Methods: A total of 8202 cervical cancer patients with pathologically confirmed between 2004 and 2014 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. All the patients were divided into training (n=3603) and validation (n=4599) cohorts based on consecutive age of diagnosis. Demographic and clinical pathological factors were evaluated the association with overall survival (OS). Parameters significantly correlating with OS were used to create a nomogram. An independent external validation cohort was subsequently used to assess the predictive performance of the model. Results: In the training set, age at diagnosis, race, marital status, tumor grade, FIGO stage, histology, size and LODDS were correlated significantly with outcome and used to develop a nomogram. The calibration curve for probability of survival showed excellent agreement between prediction by nomogram and actual observation in the training cohort, with a bootstrap-corrected concordance index of 0.749(95% CI, 0.731-0.767). Importantly, our nomogram performed favorably compared to the currently utilized FIGO model, with concordance indices of 0.786 (95% CI, 0.764 to 0.808) vs 0.685 (95%CI, 0.660 to 0.710) for OS in the validation cohort, respectively. Conclusions: By incorporating LODDS, our nomogram may be superior to the currently utilized FIGO staging system in predicting OS in cervical cancer patients after surgery.
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Affiliation(s)
- Ce Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, China
| | - Chunyan Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, China
| | - Wenjie Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, China
| | - Bairong Xia
- Department of Gynecology Oncology, the Tumor Hospital, Harbin Medical University, Harbin 150086, China
| | - Kang Li
- Department of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, China
| | - Fengyu Sun
- Department of Cardiology, The First Affiliated Hospital of Harbin Medical University, Cardiovascular Institute, Harbin Medical University, Harbin, China
| | - Yan Hou
- Department of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, China
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Huang BX, Fang F. Progress in the Study of Lymph Node Metastasis in Early-stage Cervical Cancer. Curr Med Sci 2018; 38:567-574. [PMID: 30128863 DOI: 10.1007/s11596-018-1915-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2017] [Revised: 05/08/2018] [Indexed: 02/06/2023]
Abstract
Spread into regional lymph node is the major route of metastasis in cervical cancer. Although lymph node status is not involved in the International Federation of Gynecology and Obstetrics staging system of uterine cervical cancer, the presence or absence of lymph node metastasis provides important information for prognosis and treatment. In this review, we have attempted to focus on the incidence and patterns of lymph node metastasis, and the issues surrounding surgical assessment of lymph nodes. In addition, the preoperative prediction of lymph node status, as well as the intraoperative assessment by sentinel nodes will be reviewed. Finally, lymph node micrometastasis also will be discussed.
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Affiliation(s)
- Bang-Xing Huang
- Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Fang Fang
- Department of Gynecology and Obstetrics, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
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