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Yue P, Bie F, Zhu J, Gao LR, Zhou Z, Bai G, Wang X, Zhao Z, Xiao ZF, Li Y, Zhou A, Liu WY, Jiao Y, Gao S. Minimal residual disease profiling predicts pathological complete response in esophageal squamous cell carcinoma. Mol Cancer 2024; 23:96. [PMID: 38730415 DOI: 10.1186/s12943-024-02006-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 04/19/2024] [Indexed: 05/12/2024] Open
Abstract
Accurate presurgical prediction of pathological complete response (pCR) can guide treatment decisions, potentially avoiding unnecessary surgeries and improving the quality of life for cancer patients. We developed a minimal residual disease (MRD) profiling approach with enhanced sensitivity and specificity for detecting minimal tumor DNA from cell-free DNA (cfDNA). The approach was validated in two independent esophageal squamous cell carcinoma (ESCC) cohorts. In a cohort undergoing neoadjuvant, surgical, and adjuvant therapy (NAT cohort), presurgical MRD status precisely predicted pCR. All MRD-negative cases (10/10) were confirmed as pCR by pathological evaluation on the resected tissues. In contrast, MRD-positive cases included all the 27 non-pCR cases and only one pCR case (10/10 vs 1/28, P < 0.0001, Fisher's exact test). In a definitive radiotherapy cohort (dRT cohort), post-dRT MRD status was closely correlated with patient prognosis. All MRD-negative patients (25/25) remained progression-free during the follow-up period, while 23 of the 26 MRD-positive patients experienced disease progression (25/25 vs 3/26, P < 0.0001, Fisher's exact test; progression-free survival, P < 0.0001, log-rank test). The MRD profiling approach effectively predicted the ESCC patients who would achieve pCR with surgery and those likely to remain progression-free without surgery. This suggests that the cancer cells in these MRD-negative patients have been effectively eliminated and they could be suitable candidates for a watch-and-wait strategy, potentially avoiding unnecessary surgery.
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Affiliation(s)
- Pinli Yue
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China
| | - Fenglong Bie
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Jiarun Zhu
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China
| | - Lin-Rui Gao
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China
| | - Zhendiao Zhou
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China
| | - Guangyu Bai
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China
| | - Xiaobing Wang
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China
| | - Ziyi Zhao
- Harrow International School Shenzhen Qianhai, Shenzhen, China
| | - Ze-Fen Xiao
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China
| | - Yong Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China
| | - Aiping Zhou
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wen-Yang Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China.
| | - Yuchen Jiao
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China.
- Institute of Cancer Research, Henan Academy of Innovations in Medical Science, Zhengzhou, Henan, China.
| | - Shugeng Gao
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Ln, Chaoyang, District, Beijing, 100021, China.
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Fan XH, Zhang Y, Wang P, Song QQ, Wang M, Mejias-Luque R, Li ZX, Zhou T, Zhang JY, Liu WD, Zhang LF, Li WQ, You WC, Gerhard M, Jiao YC, Wang XB, Pan KF. A noninvasive multianalytical approach establishment for risk assessment and gastric cancer screening. Int J Cancer 2024; 154:1111-1123. [PMID: 37842828 DOI: 10.1002/ijc.34739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 10/17/2023]
Abstract
Effective screening and early detection are critical to improve the prognosis of gastric cancer (GC). Our study aims to explore noninvasive multianalytical biomarkers and construct integrative models for preliminary risk assessment and GC detection. Whole genomewide methylation marker discovery was conducted with CpG tandems target amplification (CTTA) in cfDNA from large asymptomatic screening participants in a high-risk area of GC. The methylation and mutation candidates were validated simultaneously using one plasma from patients at various gastric lesion stages by multiplex profiling with Mutation Capsule Plus (MCP). Helicobacter pylori specific antibodies were detected with a recomLine assay. Integrated models were constructed and validated by the combination of multianalytical biomarkers. A total of 146 and 120 novel methylation markers were found in CpG islands and promoter regions across the genome with CTTA. The methylation markers together with the candidate mutations were validated with MCP and used to establish a 133-methylation-marker panel for risk assessment of suspicious precancerous lesions and GC cases and a 49-methylation-marker panel as well as a 144-amplicon-mutation panel for GC detection. An integrated model comprising both methylation and specific antibody panels performed better for risk assessment than a traditional model (AUC, 0.83 and 0.63, P < .001). A second model for GC detection integrating methylation and mutation panels also outperformed the traditional model (AUC, 0.82 and 0.68, P = .005). Our study established methylation, mutation and H. pylori-specific antibody panels and constructed two integrated models for risk assessment and GC screening. Our findings provide new insights for a more precise GC screening strategy in the future.
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Affiliation(s)
- Xiao-Han Fan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yang Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Beijing, China
| | - Pei Wang
- State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qian-Qian Song
- State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mona Wang
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Beijing, China
- Technical University of Munich (TUM), School of Medicine, Institute for Medical Microbiology, Immunology and Hygiene, Munich, Germany
- German Center for Infection Research, Munich, Germany
| | - Raquel Mejias-Luque
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Beijing, China
- Technical University of Munich (TUM), School of Medicine, Institute for Medical Microbiology, Immunology and Hygiene, Munich, Germany
- German Center for Infection Research, Munich, Germany
| | - Zhe-Xuan Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Beijing, China
| | - Tong Zhou
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Jing-Ying Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China
| | | | | | - Wen-Qing Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Beijing, China
| | - Wei-Cheng You
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Beijing, China
| | - Markus Gerhard
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Beijing, China
- Technical University of Munich (TUM), School of Medicine, Institute for Medical Microbiology, Immunology and Hygiene, Munich, Germany
- German Center for Infection Research, Munich, Germany
| | - Yu-Chen Jiao
- State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiao-Bing Wang
- State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kai-Feng Pan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany
- PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Beijing, China
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Zhao JJ, Sun XY, Tian SN, Zhao ZZ, Yin MD, Zhao M, Zhang F, Li SA, Yang ZX, Wen W, Cheng T, Gong A, Zhang JP, Zhang XB. Decoding the complexity of on-target integration: characterizing DNA insertions at the CRISPR-Cas9 targeted locus using nanopore sequencing. BMC Genomics 2024; 25:189. [PMID: 38368357 PMCID: PMC10874558 DOI: 10.1186/s12864-024-10050-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 01/24/2024] [Indexed: 02/19/2024] Open
Abstract
BACKGROUND CRISPR-Cas9 technology has advanced in vivo gene therapy for disorders like hemophilia A, notably through the successful targeted incorporation of the F8 gene into the Alb locus in hepatocytes, effectively curing this disorder in mice. However, thoroughly evaluating the safety and specificity of this therapy is essential. Our study introduces a novel methodology to analyze complex insertion sequences at the on-target edited locus, utilizing barcoded long-range PCR, CRISPR RNP-mediated deletion of unedited alleles, magnetic bead-based long amplicon enrichment, and nanopore sequencing. RESULTS We identified the expected F8 insertions and various fragment combinations resulting from the in vivo linearization of the double-cut plasmid donor. Notably, our research is the first to document insertions exceeding ten kbp. We also found that a small proportion of these insertions were derived from sources other than donor plasmids, including Cas9-sgRNA plasmids, genomic DNA fragments, and LINE-1 elements. CONCLUSIONS Our study presents a robust method for analyzing the complexity of on-target editing, particularly for in vivo long insertions, where donor template integration can be challenging. This work offers a new tool for quality control in gene editing outcomes and underscores the importance of detailed characterization of edited genomic sequences. Our findings have significant implications for enhancing the safety and effectiveness of CRISPR-Cas9 gene therapy in treating various disorders, including hemophilia A.
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Affiliation(s)
- Juan-Juan Zhao
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Xin-Yu Sun
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | | | - Zong-Ze Zhao
- College of Computer Science and Technology, China University of Petroleum (East China), Qingdao, 266000, China
| | - Meng-Di Yin
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Mei Zhao
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Feng Zhang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Si-Ang Li
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Zhi-Xue Yang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Wei Wen
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - Tao Cheng
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
- Tianjin Institutes of Health Science, Tianjin, 301600, China
| | - An Gong
- College of Computer Science and Technology, China University of Petroleum (East China), Qingdao, 266000, China.
| | - Jian-Ping Zhang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Tianjin Institutes of Health Science, Tianjin, 301600, China.
| | - Xiao-Bing Zhang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, National Clinical Research Center for Blood Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Tianjin Institutes of Health Science, Tianjin, 301600, China.
- Tianjin Medical University, Tianjin, China.
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Pan B, Xu Y, Yao R, Cao X, Zhou X, Hao Z, Zhang Y, Wang C, Shen S, Luo Y, Zhu Q, Ren X, Kong L, Zhou Y, Sun Q. Nomogram prediction of the 70-gene signature (MammaPrint) binary and quartile categorized risk using medical history, imaging features and clinicopathological data among Chinese breast cancer patients. J Transl Med 2023; 21:798. [PMID: 37946210 PMCID: PMC10637017 DOI: 10.1186/s12967-023-04523-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 09/13/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND The 70-gene signature (70-GS, MammaPrint) test has been recommended by the main guidelines to evaluate prognosis and chemotherapy benefit of hormonal receptor positive human epidermal receptor 2 negative (HR + /Her2-) early breast cancer (BC). However, this expensive assay is not always accessible and affordable worldwide. Based on our previous study, we established nomogram models to predict the binary and quartile categorized risk of 70-GS. METHODS We retrospectively analyzed a consecutive cohort of 150 female patients with HR + /Her2- BC and eligible 70-GS test. Comparison of 40 parameters including the patients' medical history risk factors, imaging features and clinicopathological characteristics was performed between patients with high risk (N = 62) and low risk (N = 88) of 70-GS test, whereas risk calculations from established models including Clinical Treatment Score Post-5 years (CTS5), Immunohistochemistry 3 (IHC3) and Nottingham Prognostic Index (NPI) were also compared between high vs low binary risk of 70-GS and among ultra-high (N = 12), high (N = 50), low (N = 65) and ultra-low (N = 23) quartile categorized risk of 70-GS. The data of 150 patients were randomly split by 4:1 ratio with training set of 120 patients and testing set 30 patients. Univariate analyses and multivariate logistic regression were performed to establish the two nomogram models to predict the the binary and quartile categorized risk of 70-GS. RESULTS Compared to 70-GS low-risk patients, the high-risk patients had significantly less cardiovascular co-morbidity (p = 0.034), more grade 3 BC (p = 0.006), lower progesterone receptor (PR) positive percentage (p = 0.007), more Ki67 high BC (≥ 20%, p < 0.001) and no significant differences in all the imaging parameters of ultrasound and mammogram. The IHC3 risk and the NPI calculated score significantly correlated with both the binary and quartile categorized 70-GS risk classifications (both p < 0.001). The area under curve (AUC) of receiver-operating curve (ROC) of nomogram for binary risk prediction were 0.826 (C-index 0.903, 0.799-1.000) for training and 0.737 (C-index 0.785, 0.700-0.870) for validation dataset respectively. The AUC of ROC of nomogram for quartile risk prediction was 0.870 (C-index 0.854, 0.746-0.962) for training and 0.592 (C-index 0.769, 0.703-0.835) for testing set. The prediction accuracy of the nomogram for quartile categorized risk groups were 55.0% (likelihood ratio tests, p < 0.001) and 53.3% (p = 0.04) for training and validation, which more than double the baseline probability of 25%. CONCLUSIONS To our knowledge, we are the first to establish easy-to-use nomograms to predict the individualized binary (high vs low) and the quartile categorized (ultra-high, high, low and ultra-low) risk classification of 70-GS test with fair performance, which might provide information for treatment choice for those who have no access to the 70-GS testing.
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Affiliation(s)
- Bo Pan
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Ying Xu
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Ru Yao
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Xi Cao
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Xingtong Zhou
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Zhixin Hao
- Department of Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Yanna Zhang
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Changjun Wang
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Songjie Shen
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Yanwen Luo
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Qingli Zhu
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Xinyu Ren
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Lingyan Kong
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China
| | - Yidong Zhou
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China.
| | - Qiang Sun
- Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People's Republic of China.
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Gao J, Ji H. Association of body mass index with perioperative blood transfusion and short-term clinical outcomes in patients undergoing isolated coronary artery bypass grafting. BMC Anesthesiol 2023; 23:358. [PMID: 37923996 PMCID: PMC10623869 DOI: 10.1186/s12871-023-02329-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 10/29/2023] [Indexed: 11/06/2023] Open
Abstract
BACKGROUND Few studies have considered outcomes among low body mass index (BMI) cohorts undergoing coronary artery bypass grafting (CABG). This study aims to investigate the effects of low body weight on blood transfusion and perioperative outcomes in patients undergoing isolated CABG. METHODS This retrospective study enrolled consecutive cases from a single-center between January 2008 and December 2018. Low body weight/underweight was defined as a BMI < 18.5 kg/m², while normal BMI was defined as 18.5 ≤ BMI < 24.0 kg/m². The primary endpoint was the perioperative red blood cell (RBC) transfusion rate. Secondary endpoints include platelet and plasma transfusion rates, transfusion volume for all blood components, hospital length of stay, and the occurrence of adverse events including prolonged mechanical ventilation, re-intubation, re-operation, acute kidney injury, and 30-day all-cause mortality. RESULTS A total of 7,620 patients were included in this study. After 1:1 propensity score matching, 130 pairs were formed, with 61 pairs in the on-pump group and 69 pairs in the off-pump group. Baseline characteristics were comparable between the matched groups. Low body weight independently increased the risk of RBC transfusion (on-pump: OR = 3.837, 95% CI = 1.213-12.144, p = 0.022; off-pump: OR = 3.630, 95% CI = 1.875-5.313, p < 0.001). Moreover, within the on-pump group of the original cohort, BMI of < 18.5 kg/m² was independently correlated with increased risk of re-intubation (OR = 5.365, 95% CI = 1.159 to 24.833, p = 0.032), re-operation (OR = 4.650, 95% CI = 1.019 to 21.210, p = 0.047), and 30-day all-cause mortality (OR = 10.325, 95% CI = 2.011 to 53.020, p = 0.005). CONCLUSION BMI < 18.5 kg/m² was identified as an independent risk factor for increased perioperative RBC transfusion rate in patient underwent isolated CABG with or without CPB. Only on-pump underweight patients in the original cohort exhibited an increased risk for re-intubation, re-operation, and 30-day all-cause mortality. Physicians and healthcare systems should consider these findings to improve management for this population.
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Affiliation(s)
- Jie Gao
- Department of Anesthesiology, Fuwai Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Hongwen Ji
- Department of Anesthesiology, Fuwai Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
- Department of Transfusion Medicine, Fuwai Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
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Hu G, Huang N, Zhang J, Zhang D, Wang S, Zhang Y, Wang L, Du Y, Kuang S, Ma K, Zhu H, Xu N, Liu M. LKB1 loss promotes colorectal cancer cell metastasis through regulating TNIK expression and actin cytoskeleton remodeling. Mol Carcinog 2023; 62:1659-1672. [PMID: 37449799 DOI: 10.1002/mc.23606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 05/19/2023] [Accepted: 07/05/2023] [Indexed: 07/18/2023]
Abstract
Colorectal cancer (CRC) is one of the most common malignant tumors. Approximately 5%-6% of CRC cases are associated with hereditary CRC syndromes, including the Peutz-Jeghers syndrome (PJS). Liver kinase B1 (LKB1), also known as STK11, is the major gene responsible for PJS. LKB1 heterozygotic deficiency is involved in intestinal polyps in mice, while the mechanism of LKB1 in CRC remains elusive. In this study, we generated LKB1 knockout (KO) CRC cell lines by using CRISPR-Cas9. LKB1 KO promoted CRC cell motility in vitro and tumor metastases in vivo. LKB1 attenuated expression of TRAF2 and NCK-interacting protein kinase (TNIK) as accessed by RNA-seq and western blots, and similar suppression was also detected in the tumor tissues of azoxymethane/dextran sodium sulfate-induced intestinal-specific LKB1-KO mice. LKB1 repressed TNIK expression through its kinase activity. Moreover, attenuating TNIK by shRNA inhibited cell migration and invasion of CRC cells. LKB1 loss-induced high metastatic potential of CRC cells was depended on TNIK upregulation. Furthermore, TNIK interacted with ARHGAP29 and further affected actin cytoskeleton remodeling. Taken together, LKB1 deficiency promoted CRC cell metastasis via TNIK upregulation and subsequently mediated cytoskeleton remodeling. These results suggest that LKB1-TNIK axis may play a crucial role in CRC progression.
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Affiliation(s)
- Guanghui Hu
- Laboratory of Cell and Molecular Biology & State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ning Huang
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jing Zhang
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Die Zhang
- Laboratory of Cell and Molecular Biology & State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shuren Wang
- Laboratory of Cell and Molecular Biology & State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuanyuan Zhang
- Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Panjiayuan, Chaoyang District, Beijing, People's Republic of China
| | - Liming Wang
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yingxi Du
- Laboratory of Cell and Molecular Biology & State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shuwen Kuang
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kai Ma
- Laboratory of Cell and Molecular Biology & State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongxia Zhu
- Laboratory of Cell and Molecular Biology & State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ningzhi Xu
- Laboratory of Cell and Molecular Biology & State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mei Liu
- Laboratory of Cell and Molecular Biology & State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Wu D, Hu L, Wang X, Yu Y, Jia SP, Huang HY, Li ZW, Ma JF, Zhu HB, Tang Y, Li N. Clinical development of mRNA therapies against solid tumors. J Hematol Oncol 2023; 16:75. [PMID: 37464375 PMCID: PMC10354897 DOI: 10.1186/s13045-023-01457-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 05/18/2023] [Indexed: 07/20/2023] Open
Abstract
The mRNA-based therapeutics have become the hot spot of biopharmaceutical industries in recent years. The landscape of this area is expanding from infectious disease to cancer, which needs to be summarized to provide data supports for industries and research institutions. Based on the Trialtrove database, a total of 108 clinical trials from 1999 to 2021 were retrospectively analyzed. We have demonstrated that the clinical development of mRNA therapies against solid tumors is still at an early stage. There are evolutions in delivery systems from the dendritic cell to the lipid-based platform and in encoding strategies from the fixed tumor antigens to the personalized neoantigens. The adjuvant or maintenance therapy and the combination treatment with checkpoint inhibitors are becoming the major clinical development orientation.
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Affiliation(s)
- Dawei Wu
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lingfeng Hu
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, China
| | - Xin Wang
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Clinical Trials Center, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Yue Yu
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shuo-Peng Jia
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Hebei Cancer Hospital, Chinese Academy of Medical Sciences, Langfang, China
| | - Hui-Yao Huang
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zi-Wei Li
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Jin-Feng Ma
- Department of Clinical Trials Center, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Hai-Bo Zhu
- Department of Clinical Trials Center, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Yu Tang
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ning Li
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Wu L, Fan P, Zhou J, Li Y, Xu Z, Lin Y, Wang Y, Song J, Yao H. Gene Losses and Homology of the Chloroplast Genomes of Taxillus and Phacellaria Species. Genes (Basel) 2023; 14:genes14040943. [PMID: 37107701 PMCID: PMC10137875 DOI: 10.3390/genes14040943] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 04/29/2023] Open
Abstract
Research on the chloroplast genome of parasitic plants is limited. In particular, the homology between the chloroplast genomes of parasitic and hyperparasitic plants has not been reported yet. In this study, three chloroplast genomes of Taxillus (Taxillus chinensis, Taxillus delavayi, and Taxillus thibetensis) and one chloroplast genome of Phacellaria (Phacellaria rigidula) were sequenced and analyzed, among which T. chinensis is the host of P. rigidula. The chloroplast genomes of the four species were 119,941-138,492 bp in length. Compared with the chloroplast genome of the autotrophic plant Nicotiana tabacum, all of the ndh genes, three ribosomal protein genes, three tRNA genes and the infA gene were lost in the three Taxillus species. Meanwhile, in P. rigidula, the trnV-UAC gene and the ycf15 gene were lost, and only one ndh gene (ndhB) existed. The results of homology analysis showed that the homology between P. rigidula and its host T. chinensis was low, indicating that P. rigidula grows on its host T. chinensis but they do not share the chloroplast genome. In addition, horizontal gene transfer was not found between P. rigidula and its host T. chinensis. Several candidate highly variable regions in the chloroplast genomes of Taxillus and Phacellaria species were selected for species identification study. Phylogenetic analysis revealed that the species of Taxillus and Scurrula were closely related and supported that Scurrula and Taxillus should be treated as congeneric, while species in Phacellaria had a close relationship with that in Viscum.
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Affiliation(s)
- Liwei Wu
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People's Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Panhui Fan
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People's Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Jianguo Zhou
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People's Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Yonghua Li
- Faculty of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530004, China
| | - Zhichao Xu
- College of Life Science, Northeast Forestry University, Harbin 150040, China
| | - Yulin Lin
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People's Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Yu Wang
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People's Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Jingyuan Song
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People's Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Hui Yao
- Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of the People's Republic of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
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Zhang L, Xiao Y, Zhang G, Li H, Zhao J, Chen M, Chen F, Liu L, Li Y, Peng L, Zhao F, Yang D, Wen Z, Wu L, Wu S, Sun Y, Wang Y, Chen L, Wang X, Wang L, Li W, Qiu H, Chen Y, Gao Z, Ren L, Wang J. Identification of priority pathogens for aetiological diagnosis in adults with community-acquired pneumonia in China: a multicentre prospective study. BMC Infect Dis 2023; 23:231. [PMID: 37059987 PMCID: PMC10103676 DOI: 10.1186/s12879-023-08166-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/15/2023] [Indexed: 04/16/2023] Open
Abstract
BACKGROUND Community-acquired pneumonia (CAP) is a major public health challenge worldwide. However, the aetiological and disease severity-related pathogens associated with CAP in adults in China are not well established based on the detection of both viral and bacterial agents. METHODS A multicentre, prospective study was conducted involving 10 hospitals located in nine geographical regions in China from 2014 to 2019. Sputum or bronchoalveolar lavage fluid (BALF) samples were collected from each recruited CAP patient. Multiplex real-time PCR and bacteria culture methods were used to detect respiratory pathogens. The association between detected pathogens and CAP severity was evaluated. RESULTS Among the 3,403 recruited eligible patients, 462 (13.58%) had severe CAP, and the in-hospital mortality rate was 1.94% (66/3,403). At least one pathogen was detected in 2,054 (60.36%) patients, with two or more pathogens were co-detected in 725 patients. The ten major pathogens detected were Mycoplasma pneumoniae (11.05%), Haemophilus influenzae (10.67%), Klebsiella pneumoniae (10.43%), influenza A virus (9.49%), human rhinovirus (9.02%), Streptococcus pneumoniae (7.43%), Staphylococcus aureus (4.50%), adenovirus (2.94%), respiratory syncytial viruses (2.35%), and Legionella pneumophila (1.03%), which accounted for 76.06-92.52% of all positive detection results across sampling sites. Klebsiella pneumoniae (p < 0.001) and influenza viruses (p = 0.005) were more frequently detected in older patients, whereas Mycoplasma pneumoniae was more frequently detected in younger patients (p < 0.001). Infections with Klebsiella pneumoniae, Staphylococcus aureus, influenza viruses and respiratory syncytial viruses were risk factors for severe CAP. CONCLUSIONS The major respiratory pathogens causing CAP in adults in China were different from those in USA and European countries, which were consistent across different geographical regions over study years. Given the detection rate of pathogens and their association with severe CAP, we propose to include the ten major pathogens as priorities for clinical pathogen screening in China.
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Affiliation(s)
- Lulu Zhang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China
| | - Yan Xiao
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences, Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China
| | - Guoliang Zhang
- Shenzhen Third People's Hospital, Shenzhen, 518112, P.R. China
| | - Hongru Li
- Fujian Provincial Hospital, Fujian, 350001, P.R. China
| | - Jianping Zhao
- Tongji Hospital, Tongji Medical College of Hust, Wuhan, 430030, P.R. China
| | - Mingwei Chen
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, P.R. China
| | - Fuhui Chen
- The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, P.R. China
| | - Ling Liu
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, 210009, P.R. China
| | - Yalun Li
- Department of Respiratory and Critical Care Medicine, Lung Cancer Treatment Center, West China Hospital, Sichuan University, Chengdu, 610041, P.R. China
| | - Liping Peng
- Department of Respiratory Medicine, The First Hospital of Jilin University, Changchun, 130021, China
| | - Feng Zhao
- Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, P.R. China
| | - Donghong Yang
- Peking University People's Hospital, No.11 Xizhimen South Dajie, Xicheng District, Beijing, 100044, P.R. China
| | - Zhongmei Wen
- Department of Respiratory Medicine, The First Hospital of Jilin University, Changchun, 130021, China
| | - Lei Wu
- Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, P.R. China
| | - Shuo Wu
- Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, P.R. China
| | - Yajiao Sun
- The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, P.R. China
| | - Ying Wang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China
| | - Lan Chen
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China
| | - Xinming Wang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China
| | - Lihui Wang
- Department of Respiratory Medicine, The First Hospital of Jilin University, Changchun, 130021, China
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, Lung Cancer Treatment Center, West China Hospital, Sichuan University, Chengdu, 610041, P.R. China
| | - Haibo Qiu
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, 210009, P.R. China
| | - Yusheng Chen
- Fujian Provincial Hospital, Fujian, 350001, P.R. China
| | - Zhancheng Gao
- Peking University People's Hospital, No.11 Xizhimen South Dajie, Xicheng District, Beijing, 100044, P.R. China.
| | - Lili Ren
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China.
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences, Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China.
| | - Jianwei Wang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China.
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences, Peking Union Medical College, No.9 Dong Dan San Tiao, Dongcheng District, Beijing, 100730, P.R. China.
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Shen D, Yang X, Wang Y, He D, Sun X, Cai Z, Li J, Liu M, Cui L. The Gold Coast criteria increases the diagnostic sensitivity for amyotrophic lateral sclerosis in a Chinese population. Transl Neurodegener 2021; 10:28. [PMID: 34372918 PMCID: PMC8351337 DOI: 10.1186/s40035-021-00253-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 07/20/2021] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVES The aim of this study was to assess and compare the diagnostic utility of a new diagnostic criteria for amyotrophic lateral sclerosis (ALS), abbreviated as the 'Gold Coast Criteria', with the revised El Escorial (rEEC) and Awaji criteria. METHODS Clinical and electrophysiological data of 1185 patients from January 2014 to December 2019 in the Peking Union Medical College Hospital ALS database were reviewed. The sensitivity of the Gold Coast criteria was compared to that of the possible rEEC and Awaji criteria (defined by the proportion of patients categorized as definite, probable, or possible ALS). RESULTS A final diagnosis of ALS was recorded in 1162 patients. The sensitivity of the Gold Coast criteria (96.6%, 95% confidence interval [CI] = 95.3%-97.5%) was greater than that of the rEEC (85.1%, 95%CI = 82.9%-87.1%) and Awaji (85.3%, 95%CI = 83.2%-87.3%). In addition, the sensitivity of the novel criteria maintained robust across subgroups, and the advantage was more prominent in limb-onset ALS patients and those who completed electromyographic tests. In those who did not achieve any of the rEEC diagnostic categories, the sensitivity of Gold Coast criteria was 84.4%. CONCLUSIONS The current study demonstrated that the Gold Coast criteria exhibited greater diagnostic sensitivity than the rEEC and Awaji criteria in a Chinese ALS population. The application of the Gold Coast criteria should be considered in clinical practice and future therapeutic trials.
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Affiliation(s)
- Dongchao Shen
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Xunzhe Yang
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Yanying Wang
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Di He
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Xiaohan Sun
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Zhengyi Cai
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Jinyue Li
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Mingsheng Liu
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Liying Cui
- Department of Neurology, Peking Union Medical College Hospital, Beijing, 100730, China.
- Neuroscience Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
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Yin H, Yang L, Peng G, Yang K, Mi Y, Hu X, Hao X, Jiao Y, Wang X, Wang Y. The commensal consortium of the gut microbiome is associated with favorable responses to anti-programmed death protein 1 (PD-1) therapy in thoracic neoplasms. Cancer Biol Med 2021; 18:j.issn.2095-3941.2020.0450. [PMID: 33960176 PMCID: PMC8610161 DOI: 10.20892/j.issn.2095-3941.2020.0450] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 12/09/2020] [Indexed: 12/01/2022] Open
Abstract
OBJECTIVE Immune checkpoint inhibitors have revolutionized cancer therapy for multiple types of solid tumors, but as expected, a large percentage of patients do not show durable responses. Biomarkers that can predict clinical responses to immunotherapies at diagnosis are therefore urgently needed. Herein, we determined the associations between baseline gut commensal microbes and the clinical treatment efficiencies of patients with thoracic neoplasms during anti-programmed death protein 1 (PD-1) therapy. METHODS Forty-two patients with advanced thoracic carcinoma who received anti-PD-1 treatment were enrolled in the study. Baseline and time-serial stool samples were analyzed using 16S ribosomal RNA gene sequencing. Tumor responses, patient progression-free survival, and overall survival were used to measure clinical outcomes. RESULTS The diversities of the baseline gut microbiota were similar between responders (n = 23) and nonresponders (n = 19). The relative abundances of the Akkermansiaceae, Enterococcaceae, Enterobacteriaceae, Carnobacteriaceae and Clostridiales Family XI bacterial families were significantly higher in the responder group. These 5 bacterial families acted as a commensal consortium and better stratified patients according to clinical responses (P = 0.014). Patients with a higher abundance of commensal microbes had prolonged PFS (P = 0.00016). Using multivariable analysis, the abundance of the commensal consortium was identified as an independent predictor of anti-PD-1 immunotherapy in thoracic neoplasms (hazard ratio: 0.17; 95% confidence interval: 0.05-0.55; P = 0.003). CONCLUSIONS Baseline gut microbiota may have a critical impact on anti-PD-1 treatment in thoracic neoplasms. The abundance of gut commensal microbes at diagnosis might be useful for the early prediction of anti-PD-1 immunotherapy responses.
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Affiliation(s)
- Huihui Yin
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Lu Yang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Gongxin Peng
- Center for Bioinformatics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing 100021, China
| | - Ke Yang
- Department of Medical Oncology, Cancer Hospital of Huanxing Chaoyang District Beijing, Beijing 100122, China
| | - Yuling Mi
- Department of Medical Oncology, Chaoyang Sanhuan Cancer Hospital, Beijing 100021, China
| | - Xingsheng Hu
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xuezhi Hao
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yuchen Jiao
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiaobing Wang
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yan Wang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Abstract
Tyrosine kinases are implicated in tumorigenesis and progression, and have emerged as major targets for drug discovery. Tyrosine kinase inhibitors (TKIs) inhibit corresponding kinases from phosphorylating tyrosine residues of their substrates and then block the activation of downstream signaling pathways. Over the past 20 years, multiple robust and well-tolerated TKIs with single or multiple targets including EGFR, ALK, ROS1, HER2, NTRK, VEGFR, RET, MET, MEK, FGFR, PDGFR, and KIT have been developed, contributing to the realization of precision cancer medicine based on individual patient's genetic alteration features. TKIs have dramatically improved patients' survival and quality of life, and shifted treatment paradigm of various solid tumors. In this article, we summarized the developing history of TKIs for treatment of solid tumors, aiming to provide up-to-date evidence for clinical decision-making and insight for future studies.
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Affiliation(s)
- Liling Huang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Shiyu Jiang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Yuankai Shi
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
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