• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Identification of stage I/IIA melanoma patients at high risk for disease relapse using a clinicopathologic and gene expression model.利用临床病理和基因表达模型识别 I/IIA 期黑色素瘤患者中疾病复发的高危人群。
Eur J Cancer. 2020 Nov;140:11-18. doi: 10.1016/j.ejca.2020.08.029. Epub 2020 Oct 5.
2
Identification of stage I/II melanoma patients at high risk for recurrence using a model combining clinicopathologic factors with gene expression profiling (CP-GEP).使用一种将临床病理因素与基因表达谱分析(CP-GEP)相结合的模型来识别具有高复发风险的I/II期黑色素瘤患者。
Eur J Cancer. 2023 Mar;182:155-162. doi: 10.1016/j.ejca.2022.12.021. Epub 2022 Dec 30.
3
Validation of a clinicopathological and gene expression profile model to identify patients with cutaneous melanoma where sentinel lymph node biopsy is unnecessary.验证一种临床病理和基因表达谱模型,以识别无需进行前哨淋巴结活检的皮肤黑色素瘤患者。
Eur J Surg Oncol. 2022 Feb;48(2):320-325. doi: 10.1016/j.ejso.2021.11.010. Epub 2021 Nov 10.
4
Performance of a prognostic 31-gene expression profile in an independent cohort of 523 cutaneous melanoma patients.在 523 例皮肤黑素瘤患者的独立队列中评估预后 31 基因表达谱的性能。
BMC Cancer. 2018 Feb 5;18(1):130. doi: 10.1186/s12885-018-4016-3.
5
Interim analysis of survival in a prospective, multi-center registry cohort of cutaneous melanoma tested with a prognostic 31-gene expression profile test.一项针对皮肤黑色素瘤进行的前瞻性、多中心注册队列研究的生存分析,该队列使用了一种预后 31 基因表达谱检测方法。
J Hematol Oncol. 2017 Aug 29;10(1):152. doi: 10.1186/s13045-017-0520-1.
6
Long-Term Outcomes in a Multicenter, Prospective Cohort Evaluating the Prognostic 31-Gene Expression Profile for Cutaneous Melanoma.多中心、前瞻性队列评估用于预测皮肤黑色素瘤的 31 个基因表达谱的长期结果。
JCO Precis Oncol. 2021 Apr 6;5. doi: 10.1200/PO.20.00119. eCollection 2021.
7
Using a Clinicopathologic and Gene Expression (CP-GEP) Model to Identify Stage I-II Melanoma Patients at Risk of Disease Relapse.使用临床病理和基因表达(CP-GEP)模型来识别有疾病复发风险的Ⅰ-Ⅱ期黑色素瘤患者。
Cancers (Basel). 2022 Jun 9;14(12):2854. doi: 10.3390/cancers14122854.
8
Identification of high-risk cutaneous melanoma tumors is improved when combining the online American Joint Committee on Cancer Individualized Melanoma Patient Outcome Prediction Tool with a 31-gene expression profile-based classification.当将在线美国联合癌症委员会个体化黑色素瘤患者预后预测工具与基于 31 个基因表达谱的分类相结合时,可以提高高危皮肤黑色素瘤肿瘤的识别能力。
J Am Acad Dermatol. 2017 May;76(5):818-825.e3. doi: 10.1016/j.jaad.2016.11.051. Epub 2017 Jan 19.
9
Adjuvant dabrafenib plus trametinib versus placebo in patients with resected, BRAF-mutant, stage III melanoma (COMBI-AD): exploratory biomarker analyses from a randomised, phase 3 trial.辅助达布拉非尼联合曲美替尼对比安慰剂治疗 BRAF 突变型 III 期黑色素瘤患者(COMBI-AD):一项随机、III 期临床试验的探索性生物标志物分析。
Lancet Oncol. 2020 Mar;21(3):358-372. doi: 10.1016/S1470-2045(20)30062-0. Epub 2020 Jan 30.
10
Prospective validation of the prognostic 31-gene expression profiling test in primary cutaneous melanoma.原发皮肤黑色素瘤中预后 31 基因表达谱检测的前瞻性验证。
Cancer Med. 2019 May;8(5):2205-2212. doi: 10.1002/cam4.2128. Epub 2019 Apr 5.

引用本文的文献

1
Comparing Two Gene Expression Profile Tests to Standard of Care for Identifying Patients With Cutaneous Melanoma at Low Risk of Sentinel Lymph Node Positivity.比较两种基因表达谱检测与识别前哨淋巴结阳性低风险皮肤黑色素瘤患者的标准治疗方法。
Cancer Diagn Progn. 2025 May 3;5(3):261-267. doi: 10.21873/cdp.10438. eCollection 2025 May-Jun.
2
Abscopal Effects and Immunomodulation in Skin Cancer Therapy.皮肤癌治疗中的远隔效应与免疫调节
Am J Clin Dermatol. 2025 Apr 3. doi: 10.1007/s40257-025-00943-x.
3
Risk Prediction Models for Sentinel Node Positivity in Melanoma: A Systematic Review and Meta-Analysis.黑色素瘤前哨淋巴结阳性的风险预测模型:系统评价与荟萃分析
JAMA Dermatol. 2025 May 1;161(5):523-532. doi: 10.1001/jamadermatol.2025.0113.
4
The Dutch Early-Stage Melanoma (D-ESMEL) study: a discovery set and validation cohort to predict the absolute risk of distant metastases in stage I/II cutaneous melanoma.荷兰早期黑色素瘤(D-ESMEL)研究:一个用于预测I/II期皮肤黑色素瘤远处转移绝对风险的发现集和验证队列。
Eur J Epidemiol. 2025 Jan;40(1):27-42. doi: 10.1007/s10654-024-01188-4. Epub 2025 Jan 9.
5
Enhanced Risk Stratification for Sentinel Lymph Node Biopsy in Head and Neck Melanoma Using the Merlin Assay (CP-GEP).使用Merlin检测(CP-GEP)对头颈部黑色素瘤前哨淋巴结活检进行强化风险分层。
Ann Surg Oncol. 2025 Apr;32(4):2748-2755. doi: 10.1245/s10434-024-16551-8. Epub 2024 Nov 23.
6
Attenuated mutants of Typhimurium mediate melanoma regression via an immune response.减毒鼠伤寒沙门氏菌突变体能通过免疫反应介导黑素瘤消退。
Exp Biol Med (Maywood). 2024 Jun 21;249:10081. doi: 10.3389/ebm.2024.10081. eCollection 2024.
7
The Use of Gene Expression Profiling and Biomarkers in Melanoma Diagnosis and Predicting Recurrence: Implications for Surveillance and Treatment.基因表达谱分析和生物标志物在黑色素瘤诊断及复发预测中的应用:对监测和治疗的意义
Cancers (Basel). 2024 Jan 30;16(3):583. doi: 10.3390/cancers16030583.
8
The "Great Debate" at Melanoma Bridge 2022, Naples, December 1st-3rd, 2022.2022 年 12 月 1 日至 3 日,在那不勒斯举行的黑色素瘤桥 2022 年“大辩论”。
J Transl Med. 2023 Apr 18;21(1):265. doi: 10.1186/s12967-023-04100-y.
9
Cancer immunity and immunotherapy beyond COVID-19.新冠疫情之外的癌症免疫与免疫疗法。
Cancer Immunol Immunother. 2023 Jul;72(7):2541-2548. doi: 10.1007/s00262-023-03411-9. Epub 2023 Mar 30.
10
Cost evaluation of the Merlin assay for predicting melanoma sentinel lymph node biopsy metastasis.Merlin 检测预测黑色素瘤前哨淋巴结活检转移的成本评估。
Int J Dermatol. 2023 Jan;62(1):56-61. doi: 10.1111/ijd.16515. Epub 2022 Nov 28.

本文引用的文献

1
Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma.结合肿瘤分子和临床病理危险因素的模型可预测原发性皮肤黑色素瘤前哨淋巴结转移情况。
JCO Precis Oncol. 2020;4:319-334. doi: 10.1200/po.19.00206. Epub 2020 Apr 14.
2
KEYNOTE-716: Phase III study of adjuvant pembrolizumab versus placebo in resected high-risk stage II melanoma.KEYNOTE-716:帕博利珠单抗辅助治疗与安慰剂用于 II 期高危黑色素瘤切除术后的 III 期研究。
Future Oncol. 2020 Jan;16(3):4429-4438. doi: 10.2217/fon-2019-0666. Epub 2019 Dec 24.
3
Clinical validation of a prognostic 11-gene expression profiling score in prospectively collected FFPE tissue of patients with AJCC v8 stage II cutaneous melanoma.临床验证 AJCC v8 分期 II 期皮肤黑色素瘤患者前瞻性收集 FFPE 组织中 11 基因表达谱评分的预后价值。
Eur J Cancer. 2020 Jan;125:38-45. doi: 10.1016/j.ejca.2019.10.027. Epub 2019 Dec 12.
4
Recurrence of Melanoma After a Negative Sentinel Node Biopsy: Predictors and Impact of Recurrence Site on Survival.黑色素瘤前哨淋巴结活检阴性后的复发:复发部位对生存的预测作用及影响。
Ann Surg Oncol. 2019 Jul;26(7):2254-2262. doi: 10.1245/s10434-019-07369-w. Epub 2019 Apr 22.
5
The new era of adjuvant therapies for melanoma.黑色素瘤辅助治疗的新时代。
Nat Rev Clin Oncol. 2018 Sep;15(9):535-536. doi: 10.1038/s41571-018-0048-5.
6
Adjuvant Pembrolizumab versus Placebo in Resected Stage III Melanoma.帕博利珠单抗辅助治疗与安慰剂对照用于 III 期黑色素瘤完全切除术后患者的随机、双盲、III 期临床试验
N Engl J Med. 2018 May 10;378(19):1789-1801. doi: 10.1056/NEJMoa1802357. Epub 2018 Apr 15.
7
Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.在线工具预测的变异性:基于互联网的黑色素瘤预测器的演示。
Ann Surg Oncol. 2018 Aug;25(8):2172-2177. doi: 10.1245/s10434-018-6370-4. Epub 2018 Feb 22.
8
Melanoma staging: Evidence-based changes in the American Joint Committee on Cancer eighth edition cancer staging manual.黑色素瘤分期:美国癌症联合委员会第八版癌症分期手册中基于证据的变化。
CA Cancer J Clin. 2017 Nov;67(6):472-492. doi: 10.3322/caac.21409. Epub 2017 Oct 13.
9
Adjuvant Nivolumab versus Ipilimumab in Resected Stage III or IV Melanoma.纳武利尤单抗辅助治疗与伊匹单抗用于切除的 III 期或 IV 期黑色素瘤。
N Engl J Med. 2017 Nov 9;377(19):1824-1835. doi: 10.1056/NEJMoa1709030. Epub 2017 Sep 10.
10
Adjuvant Dabrafenib plus Trametinib in Stage III BRAF-Mutated Melanoma.辅助达拉非尼联合曲美替尼治疗 BRAF 突变型 III 期黑色素瘤。
N Engl J Med. 2017 Nov 9;377(19):1813-1823. doi: 10.1056/NEJMoa1708539. Epub 2017 Sep 10.

利用临床病理和基因表达模型识别 I/IIA 期黑色素瘤患者中疾病复发的高危人群。

Identification of stage I/IIA melanoma patients at high risk for disease relapse using a clinicopathologic and gene expression model.

机构信息

Princess Máxima Center, Utrecht, the Netherlands.

SkylineDx B.V., Rotterdam, the Netherlands.

出版信息

Eur J Cancer. 2020 Nov;140:11-18. doi: 10.1016/j.ejca.2020.08.029. Epub 2020 Oct 5.

DOI:10.1016/j.ejca.2020.08.029
PMID:33032086
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7655519/
Abstract

PURPOSE

Patients with stage I/IIA cutaneous melanoma (CM) are currently not eligible for adjuvant therapies despite uncertainty in relapse risk. Here, we studied the ability of a recently developed model which combines clinicopathologic and gene expression variables (CP-GEP) to identify stage I/IIA melanoma patients who have a high risk for disease relapse.

PATIENTS AND METHODS

Archival specimens from a cohort of 837 consecutive primary CMs were used for assessing the prognostic performance of CP-GEP. The CP-GEP model combines Breslow thickness and patient age, with the expression of eight genes in the primary tumour. Our specific patient group, represented by 580 stage I/IIA patients, was stratified based on their risk of relapse: CP-GEP High Risk and CP-GEP Low Risk. The main clinical end-point of this study was five-year relapse-free survival (RFS).

RESULTS

Within the stage I/IIA melanoma group, CP-GEP identified a high-risk patient group (47% of total stage I/IIA patients) which had a considerably worse five-year RFS than the low-risk patient group; 74% (95% confidence interval [CI]: 67%-80%) versus 89% (95% CI: 84%-93%); hazard ratio [HR] = 2.98 (95% CI: 1.78-4.98); P < 0.0001. Of patients in the high-risk group, those who relapsed were most likely to do so within the first 3 years.

CONCLUSION

The CP-GEP model can be used to identify stage I/IIA patients who have a high risk for disease relapse. These patients may benefit from adjuvant therapy.

摘要

目的

尽管复发风险存在不确定性,但目前 I 期/IIA 期皮肤黑色素瘤 (CM) 患者不符合辅助治疗条件。在这里,我们研究了一种新开发的模型的能力,该模型结合了临床病理和基因表达变量 (CP-GEP),以确定具有高疾病复发风险的 I 期/IIA 期黑色素瘤患者。

患者和方法

使用来自 837 例连续原发性 CM 队列的存档标本来评估 CP-GEP 的预后表现。CP-GEP 模型结合了 Breslow 厚度和患者年龄,以及原发性肿瘤中八个基因的表达。我们的特定患者群体,由 580 名 I 期/IIA 期患者组成,根据其复发风险进行分层:CP-GEP 高风险和 CP-GEP 低风险。本研究的主要临床终点是五年无复发生存率 (RFS)。

结果

在 I 期/IIA 期黑色素瘤组中,CP-GEP 确定了一个高风险患者组(占总 I 期/IIA 期患者的 47%),其五年 RFS 明显低于低风险患者组;74%(95%置信区间 [CI]:67%-80%)与 89%(95% CI:84%-93%);危险比 [HR] = 2.98(95% CI:1.78-4.98);P<0.0001。在高风险组中,复发的患者最有可能在头 3 年内复发。

结论

CP-GEP 模型可用于识别具有高疾病复发风险的 I 期/IIA 期患者。这些患者可能受益于辅助治疗。