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Yan Z, Luan Y, Wang Y, Ren Y, Li Z, Zhao L, Shen L, Yang X, Liu T, Gao Y, Sun W. Constructing a Novel Amino Acid Metabolism Signature: A New Perspective on Pheochromocytoma Diagnosis, Immune Landscape, and Immunotherapy. Biochem Genet 2024:10.1007/s10528-024-10733-5. [PMID: 38526709 DOI: 10.1007/s10528-024-10733-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 02/05/2024] [Indexed: 03/27/2024]
Abstract
Pheochromocytoma/paraganglioma (PGPG) is a rare neuroendocrine tumor. Amino acid metabolism is crucial for energy production, redox balance, and metabolic pathways in tumor cell proliferation. This study aimed to build a risk model using amino acid metabolism-related genes, enhancing PGPG diagnosis and treatment decisions. We analyzed RNA-sequencing data from the PCPG cohort in the GEO dataset as our training set and validated our findings using the TCGA dataset and an additional clinical cohort. WGCNA and LASSO were utilized to identify hub genes and develop risk prediction models. The single-sample gene set enrichment analysis, MCPCOUNTER, and ESTIMATE algorithm calculated the relationship between amino acid metabolism and immune cell infiltration in PCPG. The TIDE algorithm predicted the immunotherapy efficacy for PCPG patients. The analysis identified 292 genes with differential expression, which are involved in amino acid metabolism and immune pathways. Six genes (DDC, SYT11, GCLM, PSMB7, TYRO3, AGMAT) were identified as crucial for the risk prediction model. Patients with a high-risk profile demonstrated reduced immune infiltration but potentially higher benefits from immunotherapy. Notably, DDC and SYT11 showed strong diagnostic and prognostic potential. Validation through quantitative Real-Time Polymerase Chain Reaction and immunohistochemistry confirmed their differential expression, underscoring their significance in PCPG diagnosis and in predicting immunotherapy response. This study's integration of amino acid metabolism-related genes into a risk prediction model offers critical clinical insights for PCPG risk stratification, potential immunotherapy responses, drug development, and treatment planning, marking a significant step forward in the management of this complex condition.
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Affiliation(s)
- Zechen Yan
- BGI College and Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Henan Engineering Research Center of Tumor Molecular Diagnosis and Treatment, Zhengzhou, 450001, Henan, People's Republic of China
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Yongkun Luan
- BGI College and Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Henan Engineering Research Center of Tumor Molecular Diagnosis and Treatment, Zhengzhou, 450001, Henan, People's Republic of China
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Yu Wang
- BGI College and Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Yilin Ren
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Henan Engineering Research Center of Tumor Molecular Diagnosis and Treatment, Zhengzhou, 450001, Henan, People's Republic of China
| | - Zhiyuan Li
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Henan Engineering Research Center of Tumor Molecular Diagnosis and Treatment, Zhengzhou, 450001, Henan, People's Republic of China
| | - Luyang Zhao
- BGI College and Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Henan Engineering Research Center of Tumor Molecular Diagnosis and Treatment, Zhengzhou, 450001, Henan, People's Republic of China
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Linnuo Shen
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Henan Engineering Research Center of Tumor Molecular Diagnosis and Treatment, Zhengzhou, 450001, Henan, People's Republic of China
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Xiaojie Yang
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Henan Engineering Research Center of Tumor Molecular Diagnosis and Treatment, Zhengzhou, 450001, Henan, People's Republic of China
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Tonghu Liu
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
- Henan Engineering Research Center of Tumor Molecular Diagnosis and Treatment, Zhengzhou, 450001, Henan, People's Republic of China.
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
| | - Yukui Gao
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
| | - Weibo Sun
- Department of Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
- Institute of Molecular Cancer Surgery, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
- Department of Radiation Oncology and Oncology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, 450000, China.
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2
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Peng W, Yu X, Yang R, Nie S, Jian X, Zeng P. Construction and validation of a nomogram for cancer specific survival of postoperative pancreatic cancer based on the SEER and China database. BMC Gastroenterol 2024; 24:104. [PMID: 38481160 PMCID: PMC10938672 DOI: 10.1186/s12876-024-03180-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 02/19/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND The recurrence rate and mortality rate among postoperative pancreatic cancer patients remain elevated. This study aims to develop and validate the cancer-specific survival period for individuals who have undergone pancreatic cancer surgery. METHODS We extracted eligible data from the Surveillance, Epidemiology, and End Results database and randomly divided all patients into a training cohort and an internal validation cohort. External validation was performed using a separate Chinese cohort. The nomogram was developed using significant risk factors identified through univariate and multivariate Cox proportional hazards regression. The effectiveness of the nomogram was assessed using the area under the time-dependent curve, calibration plots, and decision curve analysis. Kaplan-Meier survival curves were utilized to visualize the risk stratification of nomogram and AJCC stage. RESULTS Seven variables were identified through univariate and multivariate analysis to construct the nomogram. The consistency index of the nomogram for predicting overall survival was 0.683 (95% CI: 0.675-0.690), 0.689 (95% CI: 0.677-0.701), and 0.823 (95% CI: 0.786-0.860). The AUC values for the 1- and 2-year time-ROC curves were 0.751 and 0.721 for the training cohort, 0.731 and 0.7554 for the internal validation cohort, and 0.901 and 0.830 for the external validation cohorts, respectively. Calibration plots demonstrated favorable consistency between the predictions of the nomogram and actual observations. Moreover, the decision curve analysis indicated the clinical utility of the nomogram, and the risk stratification of the nomogram effectively identified high-risk patients. CONCLUSION The nomogram guides clinicians in assessing the survival period of postoperative pancreatic cancer patients, identifying high-risk groups, and devising tailored follow-up strategies.
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Affiliation(s)
- Wei Peng
- Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine, Changsha, 410006, People's Republic of China
- School of Integrated Chinese and Western Medicine, Hunan University of Traditional Chinese Medicine, Changsha, 410006, People's Republic of China
| | - Xiaopeng Yu
- Hunan University of Chinese Medicine, Changsha, Hunan, 410208, People's Republic of China
| | - Renyi Yang
- Hunan University of Chinese Medicine, Changsha, Hunan, 410208, People's Republic of China
| | - Sha Nie
- The Fourth Hospital of Changsha, Changsha, Hunan, 410006, People's Republic of China
| | - Xiaolan Jian
- Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine, Changsha, 410006, People's Republic of China.
| | - Puhua Zeng
- Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine, Changsha, 410006, People's Republic of China.
- Cancer Research Institute of Hunan Academy of Traditional Chinese Medicine, Changsha, Hunan, People's Republic of China.
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3
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Treleaven L, Komesaroff P, La Brooy C, Olver I, Kerridge I, Philip J. A review of the utility of prognostic tools in predicting 6-month mortality in cancer patients, conducted in the context of voluntary assisted dying. Intern Med J 2023; 53:2180-2197. [PMID: 37029711 DOI: 10.1111/imj.16081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 03/07/2023] [Indexed: 04/09/2023]
Abstract
BACKGROUND Eligibility to access the Victorian voluntary assisted dying (VAD) legislation requires that people have a prognosis of 6 months or less (or 12 months or less in the setting of a neurodegenerative diagnosis). Yet prognostic determination is frequently inaccurate and prompts clinician discomfort. Based on functional capacity and clinical and biochemical markers, prognostic tools have been developed to increase the accuracy of life expectancy predictions. AIMS This review of prognostic tools explores their accuracy to determine 6-month mortality in adults when treated under palliative care with a primary diagnosis of cancer (the diagnosis of a large proportion of people who are requesting VAD). METHODS A systematic search of the literature was performed on electronic databases Medline, Embase and Cinahl. RESULTS Limitations of prognostication identified include the following: (i) prognostic tools still provide uncertain prognoses; (ii) prognostic tools have greater accuracy predicting shorter prognoses, such as weeks to months, rather than 6 months; and (iii) functionality was often weighted significantly when calculating prognoses. Challenges of prognostication identified include the following: (i) the area under the curve (a value that represents how well a model can distinguish between two outcomes) cannot be directly interpreted clinically and (ii) difficulties exist related to determining appropriate thresholds of accuracy in this context. CONCLUSIONS Prognostication is a significant aspect of VAD, and the utility of the currently available prognostic tools appears limited but may prompt discussions about prognosis and alternative means (other than prognostic estimates) to identify those eligible for VAD.
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Affiliation(s)
- Lydia Treleaven
- Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia
| | - Paul Komesaroff
- School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
- Department of Medicine, Alfred Hospital, Melbourne, Victoria, Australia
| | - Camille La Brooy
- School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Ian Olver
- School of Psychology, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Ian Kerridge
- Department of Medicine, Royal North Shore Hospital, St Leonards, New South Wales, Australia
- Sydney Health Ethics, The University of Sydney, Camperdown, New South Wales, Australia
| | - Jennifer Philip
- Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia
- Palliative Care Service, St Vincent's Hospital, Melbourne, Victoria, Australia
- Palliative Care Service, Peter MacCallum Cancer Centre, Royal Melbourne Hospital, Melbourne, Victoria, Australia
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4
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Keyl J, Kasper S, Wiesweg M, Götze J, Schönrock M, Sinn M, Berger A, Nasca E, Kostbade K, Schumacher B, Markus P, Albers D, Treckmann J, Schmid KW, Schildhaus HU, Siveke JT, Schuler M, Kleesiek J. Multimodal survival prediction in advanced pancreatic cancer using machine learning. ESMO Open 2022; 7:100555. [PMID: 35988455 PMCID: PMC9588888 DOI: 10.1016/j.esmoop.2022.100555] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 07/04/2022] [Accepted: 07/05/2022] [Indexed: 11/23/2022] Open
Abstract
Background Existing risk scores appear insufficient to assess the individual survival risk of patients with advanced pancreatic ductal adenocarcinoma (PDAC) and do not take advantage of the variety of parameters that are collected during clinical care. Methods In this retrospective study, we built a random survival forest model from clinical data of 203 patients with advanced PDAC. The parameters were assessed before initiation of systemic treatment and included age, CA19-9, C-reactive protein, metastatic status, neutrophil-to-lymphocyte ratio and total serum protein level. Separate models including imaging and molecular parameters were built for subgroups. Results Over the entire cohort, a model based on clinical parameters achieved a c-index of 0.71. Our approach outperformed the American Joint Committee on Cancer (AJCC) staging system and the modified Glasgow Prognostic Score (mGPS) in the identification of high- and low-risk subgroups. Inclusion of the KRAS p.G12D mutational status could further improve the prediction, whereas radiomics data of the primary tumor only showed little benefit. In an external validation cohort of PDAC patients with liver metastases, our model achieved a c-index of 0.67 (mGPS: 0.59). Conclusions The combination of multimodal data and machine-learning algorithms holds potential for personalized prognostication in advanced PDAC already at diagnosis. We developed a machine-learning-based prediction model that outperforms the AJCC staging system and mGPS. Applying our model to an external validation cohort demonstrates generalizability. Explainable machine learning enables to understand the decision making of our model and identifies relevant parameters. Combining clinical, imaging and genetic data holds potential for personalized prognostication in advanced PDAC.
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Affiliation(s)
- J Keyl
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Germany; Institute for AI in Medicine (IKIM), University Hospital Essen (AöR), Essen, Germany; German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany.
| | - S Kasper
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - M Wiesweg
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - J Götze
- Department of Internal Medicine II, Oncology, Hematology, BMT and Pneumology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - M Schönrock
- Department of Internal Medicine II, Oncology, Hematology, BMT and Pneumology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - M Sinn
- Department of Internal Medicine II, Oncology, Hematology, BMT and Pneumology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - A Berger
- Institute for AI in Medicine (IKIM), University Hospital Essen (AöR), Essen, Germany
| | - E Nasca
- Institute for AI in Medicine (IKIM), University Hospital Essen (AöR), Essen, Germany
| | - K Kostbade
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - B Schumacher
- Department of Gastroenterology, Elisabeth Hospital Essen, Essen, Germany
| | - P Markus
- Department of General Surgery and Traumatology, Elisabeth Hospital Essen, Essen, Germany
| | - D Albers
- Department of Gastroenterology, Elisabeth Hospital Essen, Essen, Germany
| | - J Treckmann
- Department of General, Visceral and Transplant Surgery, West German Cancer Center, University Hospital Essen (AöR), Essen, Germany
| | - K W Schmid
- Medical Faculty, University of Duisburg-Essen, Essen, Germany; Institute of Pathology, West German Cancer Center, University Hospital Essen (AöR), Essen, Germany
| | - H-U Schildhaus
- Medical Faculty, University of Duisburg-Essen, Essen, Germany; Institute of Pathology, West German Cancer Center, University Hospital Essen (AöR), Essen, Germany
| | - J T Siveke
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany; Bridge Institute of Experimental Tumor Therapy (BIT), West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK) Partner site Essen, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - M Schuler
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - J Kleesiek
- Institute for AI in Medicine (IKIM), University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
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5
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Shibuki T, Mizuta T, Shimokawa M, Koga F, Ueda Y, Nakazawa J, Komori A, Otsu S, Arima S, Fukahori M, Makiyama A, Taguchi H, Honda T, Mitsugi K, Nio K, Ide Y, Ureshino N, Shirakawa T, Otsuka T. Prognostic nomogram for patients with unresectable pancreatic cancer treated with gemcitabine plus nab-paclitaxel or FOLFIRINOX: A post-hoc analysis of a multicenter retrospective study in Japan (NAPOLEON study). BMC Cancer 2022; 22:19. [PMID: 34980029 PMCID: PMC8722136 DOI: 10.1186/s12885-021-09139-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 12/22/2021] [Indexed: 01/04/2023] Open
Abstract
Background No reliable nomogram has been developed until date for predicting the survival in patients with unresectable pancreatic cancer undergoing treatment with gemcitabine plus nab–paclitaxel (GnP) or FOLFIRINOX. Methods This analysis was conducted using clinical data of Japanese patients with unresectable pancreatic cancer undergoing GnP or FOLFIRINOX treatment obtained from a multicenter study (NAPOLEON study). A Cox proportional hazards model was used to identify the independent prognostic factors. A nomogram to predict 6–, 12–, and 18–month survival probabilities was generated, validated by using the concordance index (C–index), and calibrated by the bootstrapping method. And then, we attempted risk stratification for survival by classifying the patients according to the sum of the scores on the nomogram (total nomogram points). Results A total of 318 patients were enrolled. A prognostic nomogram was generated using data on the Eastern Cooperative Oncology Group performance status, liver metastasis, serum LDH, serum CRP, and serum CA19–9. The C–indexes of the nomogram were 0.77, 0.72 and 0.70 for 6–, 12–, and 18–month survival, respectively. The calibration plot showed optimal agreement at all points. Risk stratification based on tertiles of the total nomogram points yielded clear separations of the survival curves. The median survival times in the low–, moderate–, and high–risk groups were 15.8, 12.8 and 7.8 months (P<0.05), respectively. Conclusions Our nomogram might be a convenient and inexpensive tool to accurately predict survival in Japanese patients with unresectable pancreatic cancer undergoing treatment with GnP or FOLFIRINOX, and will help clinicians in selecting appropriate therapeutic strategies for individualized management. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-09139-y.
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Affiliation(s)
- Taro Shibuki
- Department of Internal Medicine, Imari Arita Kyoritsu Hospital, 860 Ninose-ko, Arita-cho, Nishi-matsuura-gun, Saga, 849-4193, Japan.,Department of Hepatobiliary and Pancreatic Oncology, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa-shi, Chiba, 277-8577, Japan
| | - Toshihiko Mizuta
- Department of Internal Medicine, Imari Arita Kyoritsu Hospital, 860 Ninose-ko, Arita-cho, Nishi-matsuura-gun, Saga, 849-4193, Japan.,Department of Internal Medicine, Fujikawa Hospital, 1-2-6 Matsubara, Saga-shi, Saga, 840-0831, Japan
| | - Mototsugu Shimokawa
- Clinical Research Institute, National Hospital Organization Kyushu Cancer Center, 3-1-1 Notame, Minami-ku, Fukuoka-shi, Fukuoka, 811-1395, Japan.,Department of Biostatistics, Yamaguchi University Graduate School of Medicine, 1-1-1 Minamikogushi, Ube, Yamaguchi, 755-8505, Japan
| | - Futa Koga
- Department of Hepatobiliary and Pancreatology, Saga Medical Center Koseikan, 400 Kase-machi, Saga-shi, Saga, 840-8571, Japan
| | - Yujiro Ueda
- Department of Hematology and Oncology, Japanese Red Cross Kumamoto Hospital, 2-1-1 Nagamine-minami, Higashi-ku, Kumamoto-shi, Kumamoto, 861-8520, Japan
| | - Junichi Nakazawa
- Department of Medical Oncology, Kagoshima City Hospital, 37-1 Uearata-cho, Kagoshima-shi, Kagoshima, 890-8760, Japan
| | - Azusa Komori
- Department of Medical Oncology and Hematology, Oita University Faculty of Medicine, 1-1 Idaigaoka, Hasama-machi, Yufu-shi, Oita, 879-5593, Japan
| | - Satoshi Otsu
- Department of Medical Oncology and Hematology, Oita University Faculty of Medicine, 1-1 Idaigaoka, Hasama-machi, Yufu-shi, Oita, 879-5593, Japan
| | - Shiho Arima
- Digestive and Lifestyle Diseases, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima-shi, Kagoshima, 890-8520, Japan
| | - Masaru Fukahori
- Division of Gastroenterology, Department of Medicine, Kurume University School of Medicine, 67 Asahi-machi, Kurume-shi, Fukuoka, 830-0011, Japan
| | - Akitaka Makiyama
- Department of Hematology/Oncology, Japan Community Healthcare Organization Kyushu Hospital, 1-8-1 Kishinoura, Yahatanishi-ku, Kitakyushu-shi, Fukuoka, 806-8501, Japan.,Cancer Center, Gifu University Hospital, 1-1 Yanagido, Gifu-shi, Gifu, 501-1194, Japan
| | - Hiroki Taguchi
- Department of Gastroenterology, Saiseikai Sendai Hospital, 2-46 Harada-machi, Satsumasendai-shi, Kagoshima, 895-0074, Japan.,Department of Gastroenterology, Izumi General Medical Center, 520 Myojincho, Izumi-shi, Kagoshima, 899-0131, Japan
| | - Takuya Honda
- Department of Gastroenterology and Hepatology, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki-shi, Nagasaki, 852-8501, Japan
| | - Kenji Mitsugi
- Department of Medical Oncology, Hamanomachi Hospital, 3-3-1 Nagahama, Chuo-ku, Fukuoka-shi, Fukuoka, 810-8539, Japan.,Department of Medical Oncology, Sasebo Kyosai Hospital, 10-17 Shimanji-cho, Sasebo-shi, Nagasaki, 857-8575, Japan
| | - Kenta Nio
- Department of Medical Oncology, Hamanomachi Hospital, 3-3-1 Nagahama, Chuo-ku, Fukuoka-shi, Fukuoka, 810-8539, Japan.,Department of Medical Oncology, Sasebo Kyosai Hospital, 10-17 Shimanji-cho, Sasebo-shi, Nagasaki, 857-8575, Japan
| | - Yasushi Ide
- Department of Internal Medicine, Karatsu Red Cross Hospital, 2430 Watada, Karatsu-shi, Saga, 847-8588, Japan
| | - Norio Ureshino
- Department of Medical Oncology, Saga Medical Center Koseikan, 400 Kase-machi, Saga-shi, Saga, 840-8571, Japan.,Department of Medical Oncology, Kimitsu Chuo Hospital, 1010 Sakurai, Kisarazu-shi, Chiba, 292-8535, Japan
| | - Tsuyoshi Shirakawa
- Department of Medical Oncology, Fukuoka Wajiro Hospital, 2-2-75 Wajirogaoka, Higashi-ku, Fukuoka-shi, Fukuoka, 811-0213, Japan. .,Karatsu Higashi-matsuura Medical Association Center, 2566-11 Chiyoda-machi, Karatsu-shi, Saga, 847-0041, Japan.
| | - Taiga Otsuka
- Department of Medical Oncology, Saga Medical Center Koseikan, 400 Kase-machi, Saga-shi, Saga, 840-8571, Japan.,Department of Internal Medicine, Minato Medical Clinic, 3-11-3 Nagahama, Chuo-ku, Fukuoka-shi, Fukuoka, 810-0072, Japan
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6
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Deng GC, Lv Y, Yan H, Sun DC, Qu TT, Pan YT, Han QL, Dai GH. Nomogram to predict survival of patients with advanced and metastatic pancreatic Cancer. BMC Cancer 2021; 21:1227. [PMID: 34781928 PMCID: PMC8594118 DOI: 10.1186/s12885-021-08943-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 10/28/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Nomograms are rarely employed to estimate the survival of patients with advanced and metastatic pancreatic cancer (PC). Herein, we developed a comprehensive approach to using a nomogram to predict survival probability in patients with advanced and metastatic PC. METHODS A total of 323 patients with advanced and metastatic PC were identified from the Chinese People's Liberation Army (PLA) General Hospital. A baseline nomogram was constructed using baseline variables of 323 patients. Additionally, 233 patients, whose tumors showed initial responses to first-line chemotherapy, were enrolled in the chemotherapy response-based model. 128 patients and 108 patients with advanced and metastatic PC from January 2019 to April 2021 were selected for external validating baseline model and chemotherapy response-based model. The 1-year and 2-year survival probability was evaluated using multivariate COX regression models. The discrimination and calibration capacity of the nomograms were assessed using C-statistic and calibration plots. The predictive accuracy and net benefit of the nomograms were evaluated using ROC curve and DCA, respectively. RESULTS In the baseline model, six variables (gender, KPS, baseline TB, baseline N, baseline WBC and baseline CA19-9) were used in the final model. In the chemotherapy response-based model, nine variables (KPS, gender, ascites, baseline N, baseline CA 19-9, baseline CEA, change in CA 19-9 level at week, change in CEA level at week and initial response to chemotherapy) were included in the final model. The C-statistics of the baseline nomogram and the chemotherapy response-based nomogram were 0.67 (95% CI, 0.62-0.71) and 0.74 (95% CI, 0.69-0.77), respectively. CONCLUSION These nomograms were constructed to predict the survival probability of patients of advanced and metastatic PC. The baseline model and chemotherapy response-based model performed well in survival prediction.
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Affiliation(s)
- G C Deng
- School of Medicine, Nankai University, Tianjin, China
- Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Y Lv
- School of Medicine, Nankai University, Tianjin, China
| | - H Yan
- School of Medicine, Nankai University, Tianjin, China
| | - D C Sun
- School of Medicine, Nankai University, Tianjin, China
| | - T T Qu
- School of Medicine, Nankai University, Tianjin, China
- Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Y T Pan
- School of Medicine, Nankai University, Tianjin, China
| | - Q L Han
- School of Medicine, Nankai University, Tianjin, China.
| | - G H Dai
- School of Medicine, Nankai University, Tianjin, China.
- Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
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7
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Vary A, Lebellec L, Di Fiore F, Penel N, Cheymol C, Rad E, El Hajbi F, Lièvre A, Edeline J, Bimbai AM, Le Deley MC, Turpin A. FOLFIRINOX relative dose intensity and disease control in advanced pancreatic adenocarcinoma. Ther Adv Med Oncol 2021; 13:17588359211029825. [PMID: 34349842 PMCID: PMC8287268 DOI: 10.1177/17588359211029825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 06/14/2021] [Indexed: 01/05/2023] Open
Abstract
Background: Most patients with advanced pancreatic adenocarcinoma (PA) treated with FOLFIRINOX experience adverse events requiring dose reduction. We aimed to assess the association between relative dose intensity (RDI) and disease control in a European setting. Methods: We retrospectively included patients with advanced PA treated with three or more cycles of FOLFIRINOX between 2011 and 2018 in six French centers. We computed the cumulative single-agent RDI (csRDI) before the first reassessment for each FOLFIRINOX agent (oxaliplatin, irinotecan, 5FU bolus, and 5FU intravenous infusion) and the cumulative multi-drug RDI (cmRDI) of their combination. The association between RDI and disease control or objective response at first reassessment was evaluated using multivariable logistic regression models controlling for performance status, liver metastases, and center. Results: We included 243 patients. Median csRDIs were 81%, 79%, 75%, and 85% for oxaliplatin, irinotecan, 5FU bolus, and 5FU intravenous infusion, respectively. Median cmRDI was 80%. None of the RDIs was significantly associated with disease control or objective response. Including RDI in a clinical model did not improve its ability to predict disease control; the area under the curve was 0.79 (95% CI: 0.73–0.85) with RDI versus 0.78 (95% CI: 0.72–0.85) without. Similar results were observed for the objective response. Conclusion: Pragmatic dose adjustments of FOLFIRINOX should be made by oncologists without considering a loss of effect.
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Affiliation(s)
| | | | | | | | - Claire Cheymol
- Onco-Hematology Department, Saint Vincent de Paul Hospital, Lille, France
| | - Emilia Rad
- Medical Oncology Department, Victor Provo Hospital, Roubaix, France
| | - Farid El Hajbi
- Medical Oncology Department, Oscar Lambret Center, Lille, France
| | - Astrid Lièvre
- Department of Gastroenterology, CHU Pontchaillou, Rennes, France
| | - Julien Edeline
- Medical Oncology Department, Eugène Marquis Center, Rennes, France
| | | | | | - Anthony Turpin
- University of Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020 - UMR-S 1277 - Canther-Cancer Heterogeneity, Plasticity and Resistance to Therapies, Lille, France
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8
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Khomiak A, Brunner M, Kordes M, Lindblad S, Miksch RC, Öhlund D, Regel I. Recent Discoveries of Diagnostic, Prognostic and Predictive Biomarkers for Pancreatic Cancer. Cancers (Basel) 2020; 12:E3234. [PMID: 33147766 PMCID: PMC7692691 DOI: 10.3390/cancers12113234] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 10/26/2020] [Accepted: 10/28/2020] [Indexed: 12/11/2022] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with a dismal prognosis that is frequently diagnosed at an advanced stage. Although less common than other malignant diseases, it currently ranks as the fourth most common cause of cancer-related death in the European Union with a five-year survival rate of below 9%. Surgical resection, followed by adjuvant chemotherapy, remains the only potentially curative treatment but only a minority of patients is diagnosed with locally resectable, non-metastatic disease. Patients with advanced disease are treated with chemotherapy but high rates of treatment resistance and unfavorable side-effect profiles of some of the used regimens remain major challenges. Biomarkers reflect pathophysiological or physiological processes linked to a disease and can be used as diagnostic, prognostic and predictive tools. Thus, accurate biomarkers can allow for better patient stratification and guide therapy choices. Currently, the only broadly used biomarker for PDAC, CA 19-9, has multiple limitations and the need for novel biomarkers is urgent. In this review, we highlight the current situation, recent discoveries and developments in the field of biomarkers of PDAC and their potential clinical applications.
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Affiliation(s)
- Andrii Khomiak
- Shalimov National Institute of Surgery and Transplantology, 03058 Kyiv, Ukraine;
| | - Marius Brunner
- Department of Gastroenterology, Endocrinology and Gastrointestinal Oncology, University Medical Center, 37075 Goettingen, Germany;
| | - Maximilian Kordes
- Department of Upper Abdominal Diseases, Karolinska University Hospital, 14186 Stockholm, Sweden;
- Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, 17177 Stockholm, Sweden
| | - Stina Lindblad
- Department of Radiation Sciences, Sweden and Wallenberg Centre for Molecular Medicine, Umeå University, 90187 Umeå, Sweden;
| | - Rainer Christoph Miksch
- Department of General, Visceral and Transplantation Surgery, University Hospital, LMU Munich, 81377 Munich, Germany;
| | - Daniel Öhlund
- Department of Radiation Sciences, Sweden and Wallenberg Centre for Molecular Medicine, Umeå University, 90187 Umeå, Sweden;
| | - Ivonne Regel
- Department of Medicine II, University Hospital, LMU Munich, 81377 Munich, Germany
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9
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Reactive oxygen species mediate anlotinib-induced apoptosis via activation of endoplasmic reticulum stress in pancreatic cancer. Cell Death Dis 2020; 11:766. [PMID: 32943607 PMCID: PMC7499216 DOI: 10.1038/s41419-020-02938-4] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 08/09/2020] [Accepted: 08/25/2020] [Indexed: 01/01/2023]
Abstract
Anlotinib (AL3818), a novel multi-targeted receptor tyrosine kinase inhibitor, has recently been proven to be an antitumour drug. This study aimed to explore the antitumour effect of anlotinib and its underlying molecular mechanisms in human pancreatic cancer (PC) cells. The anti-proliferative effect of anlotinib for three PC cell lines was validated using CCK-8, colony formation and EdU detection assays. Cell cycle, cell apoptosis, and reactive oxygen species (ROS) detection assays, a PC xenograft model and immunohistochemistry were performed to elucidate the mechanisms by which anlotinib induced tumour lethality in vitro and in vivo. These results demonstrated that anlotinib inhibited proliferation, induced G2/M phase arrest and triggered apoptosis in PC cell lines. Anlotinib induced PC’s apoptosis through the accumulation of ROS which activated the endoplasmic reticulum (ER) stress via PERK/p-eIF2α/ATF4 pathway. Furthermore, we demonstrated that the expression level of Nrf2, an antioxidant protein, increased with anlotinib treatment. Nrf2 knockdown enhanced the pro-apoptotic effect of anlotinib and the expression of the PERK/p-eIF2α/ATF4 pathway. The in vivo results suggested that suppressing Nrf2 improved the antitumour effect of anlotinib on PC cells. These data indicated that the apoptotic effect of anlotinib on PC cells was induced by ER stress via the accumulation of ROS. In the future, anlotinib combined with an Nrf2 inhibitor may provide a new therapeutic strategy for the treatment of human PC.
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10
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Qingwei Z, Dongsheng H, Duo L, Youlei W, Songxia Y, Ziqi Y, Lanjuan L. Fluorouracil Supplemented With Oxaliplatin or Irinotecan for Solid Tumors: Indications From Clinical Characteristics and Health Outcomes of Patients. Front Oncol 2020; 10:1542. [PMID: 32984012 PMCID: PMC7492525 DOI: 10.3389/fonc.2020.01542] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 07/20/2020] [Indexed: 12/12/2022] Open
Abstract
Fluorouracil combined with oxaliplatin (FOLFOX) and fluorouracil combined with irinotecan (FOLFIRI) are both first-line clinical chemotherapy regimens. However, clinicians' selection of FOLFIRI or FOLFOX medication regimens and their effects on patients' health outcomes are not clear. The aim of this study was to evaluate the impacts on patient characteristics of FOLFIRI or FOLFOX medication regimen selection and the effects of each regimen on patients' health outcomes in a real-world setting. Three thousand seven hundred and twenty-five patients were retrieved and 610 of them were eventually included in this study based on the inclusion and exclusion criteria. The percentages of the TNM stage, cetuximab, bevacizumab, and tumor metastases between the FOLFIRI and FOLFOX groups were different (P < 0.001). In the multivariate Cox proportional hazards model, a significantly higher non-convalescent incidence of the FOLFOX group was found as compared with the FOLFIRI group (HR = 2.211, 95% CI = 1.257–3.888, P = 0.006). In conclusion, the TNM stage, whether combined with cetuximab or bevacizumab, and whether there was tumor metastasis presented as the key factors affecting medication selection between the FOLFIRI and FOLFOX regimens. The FOLFIRI regimen exhibited better effects on patients' long-term health outcomes than did the FOLFOX regimen. This study was registered on the World Health Organization International Clinical Trials Registry Platform (ChiCTR2000029201). Trial registration: ChiCTR2000029201.
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Affiliation(s)
- Zhao Qingwei
- Key Laboratory for Drug Evaluation and Clinical Research of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Hong Dongsheng
- Key Laboratory for Drug Evaluation and Clinical Research of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lv Duo
- Key Laboratory for Drug Evaluation and Clinical Research of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Wang Youlei
- Key Laboratory for Drug Evaluation and Clinical Research of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yu Songxia
- Key Laboratory for Drug Evaluation and Clinical Research of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ye Ziqi
- Key Laboratory for Drug Evaluation and Clinical Research of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Li Lanjuan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
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11
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Vivaldi C, Salani F, Rovesti G, Pecora I, Catanese S, Casadei-Gardini A, Massa V, Bernardini L, Riggi L, Andrikou K, Rapposelli GI, Formica V, Lencioni M, Falcone A, Vasile E, Fornaro L. First-line gemcitabine plus nab-paclitaxel for elderly patients with metastatic pancreatic cancer: Crossing the frontier of age? Eur J Cancer 2020; 137:108-116. [PMID: 32750500 DOI: 10.1016/j.ejca.2020.06.031] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 06/12/2020] [Accepted: 06/26/2020] [Indexed: 01/05/2023]
Abstract
BACKGROUND Gemcitabine plus nab-paclitaxel (Gem-Nab) represents a standard first-line treatment for metastatic pancreatic cancer (mPC), but few data are available for elderly patients. We aimed to add evidence about safety and efficacy of Gem-Nab in this population. METHODS We collected data of 156 patients with mPC aged ≥65 years receiving Gem-Nab. Patients were stratified according to age: <70 (group 1: 65 patients) and ≥70 years (group 2: 91 patients). RESULTS The median age was 71 years (range: 65-87 years). The toxicity profile was similar between group 1 and 2, except for all-grade anaemia (92.1% vs. 78.7%, respectively; p = 0.04) and neurotoxicity (61.9% vs. 40.4%, respectively; p = 0.02), also as a result of a lower dose intensity of nab-paclitaxel (83.3% vs. 90.5%, respectively; p = 0.04) administered to oldest patients. The response rate was 25.6% (group 1 vs. 2: 20.0% vs. 29.7%; p = 0.12). After a median follow-up of 26.5 months, median overall survival (OS) and progression-free survival (PFS) were similar between the groups (p > 0.05). The starting dose of Gem-Nab did not affect PFS and OS (p > 0.05). CONCLUSION Gem-Nab is active and effective in older patients with mPC, with the results in line with the general mPC population enrolled in clinical trials. Mild dose modifications for elderly patients might be considered to improve safety without impairing efficacy.
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Affiliation(s)
- Caterina Vivaldi
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy; Department of Translational Research and New Surgical and Medical Technologies, University of Pisa, Via Savi 6, Pisa, 56126, Italy
| | - Francesca Salani
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy
| | - Giulia Rovesti
- Department of Oncology and Hematology, Division of Oncology, University of Modena and Reggio Emilia, Via del Pozzo 71, Modena, 41100, Italy
| | - Irene Pecora
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy
| | - Silvia Catanese
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy
| | - Andrea Casadei-Gardini
- Department of Medical Oncology, Istituto Scientifico Romagnolo per Lo Studio e La Cura Dei Tumori (IRST) IRCCS, Via P. Maroncelli N. 40, Meldola, 47014, Italy
| | - Valentina Massa
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy
| | - Laura Bernardini
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy
| | - Laura Riggi
- Department of Oncology and Hematology, Division of Oncology, University of Modena and Reggio Emilia, Via del Pozzo 71, Modena, 41100, Italy
| | - Kalliopi Andrikou
- Department of Oncology and Hematology, Division of Oncology, University of Modena and Reggio Emilia, Via del Pozzo 71, Modena, 41100, Italy
| | - Giovanni I Rapposelli
- Department of Medical Oncology, Istituto Scientifico Romagnolo per Lo Studio e La Cura Dei Tumori (IRST) IRCCS, Via P. Maroncelli N. 40, Meldola, 47014, Italy
| | - Vincenzo Formica
- Medical Oncology Unit, Tor Vergata University, Viale Oxford 81, Rome, 00133, Italy
| | - Monica Lencioni
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy
| | - Alfredo Falcone
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy; Department of Translational Research and New Surgical and Medical Technologies, University of Pisa, Via Savi 6, Pisa, 56126, Italy
| | - Enrico Vasile
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy
| | - Lorenzo Fornaro
- Unit of Medical Oncology, Azienda Ospedaliero-Universitaria Pisana, Via Roma 67, Pisa, 56126, Italy.
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