背景：肺腺癌患者数量不断增加，但是在提高预后结果和改善患者生存率方面仍取得有限进展。基因组不稳定性被认为是一个促进因素，因为它使得癌症的其他标记可以获得功能能力，使癌细胞得以存活、增殖和传播。尽管基因组不稳定性在癌症发展中的重要性，但对于肺腺癌的基因组不稳定性相关的预后标记的研究仍然很少。方法：在本研究中，我们将来自癌症基因组图谱数据库的397例肺腺癌患者随机分为一个训练组（n = 199）和一个测试组（n = 198）。通过计算训练组每个患者的基因组变异累积计数，我们将患者的前25％和后25％进行区分。然后，我们比较了他们的基因表达以确定与基因组不稳定性相关的基因。接下来，我们使用单变量和多变量Cox回归分析来确定预后标记。我们还进行了Kaplan-Meier生存分析和log-rank检验来评估所确定预后标记的表现。预后标记的性能在测试组、癌症基因组图谱数据库以及外部数据库中进行了进一步验证。我们还进行了时间相关的接受者操作特征分析，将我们的标记与已建立的预后标记进行比较，以展示其潜在临床价值。结果：我们从42个与基因组不稳定性相关的基因中确定了GULPsig作为肺腺癌患者的预后标记，其中包括IGF2BP1、IGF2BP3、SMC1B、CLDN6和LY6K。根据GULPsig风险模型的风险评分，我们成功地将患者分为高风险组和低风险组，这与Kaplan-Meier生存分析和log-rank检验的结果一致。我们进一步验证了GULPsig作为独立预后标记的性能，并观察到它优于已建立的预后标记。结论：我们为探索基因组不稳定性的临床应用提供了新的见解，并将GULPsig确定为肺腺癌患者的潜在预后标记。版权所有 © 2023 Zhang、Lam和Ting。

Background: An increasing number of patients are being diagnosed with lung adenocarcinoma, but there remains limited progress in enhancing prognostic outcomes and improving survival rates for these patients. Genome instability is considered a contributing factor, as it enables other hallmarks of cancer to acquire functional capabilities, thus allowing cancer cells to survive, proliferate, and disseminate. Despite the importance of genome instability in cancer development, few studies have explored the prognostic signature associated with genome instability for lung adenocarcinoma. Methods: In the study, we randomly divided 397 lung adenocarcinoma patients from The Cancer Genome Atlas database into a training group (n = 199) and a testing group (n = 198). By calculating the cumulative counts of genomic alterations for each patient in the training group, we distinguished the top 25% and bottom 25% of patients. We then compared their gene expressions to identify genome instability-related genes. Next, we used univariate and multivariate Cox regression analyses to identify the prognostic signature. We also performed the Kaplan-Meier survival analysis and the log-rank test to evaluate the performance of the identified prognostic signature. The performance of the signature was further validated in the testing group, in The Cancer Genome Atlas dataset, and in external datasets. We also conducted a time-dependent receiver operating characteristic analysis to compare our signature with established prognostic signatures to demonstrate its potential clinical value. Results: We identified GULPsig, which includes IGF2BP1, IGF2BP3, SMC1B, CLDN6, and LY6K, as a prognostic signature for lung adenocarcinoma patients from 42 genome instability-related genes. Based on the risk score of the risk model with GULPsig, we successfully stratified the patients into high- and low-risk groups according to the results of the Kaplan-Meier survival analysis and the log-rank test. We further validated the performance of GULPsig as an independent prognostic signature and observed that it outperformed established prognostic signatures. Conclusion: We provided new insights to explore the clinical application of genome instability and identified GULPsig as a potential prognostic signature for lung adenocarcinoma patients.Copyright © 2023 Zhang, Lam and Ting.