背景:新辅助化疗(NACT)成为晚期肿瘤的一线选择,而对它不敏感的患者可能不会受益。因此,筛查适合NACT的患者非常重要。
方法:分析含顺铂(CDDP)前后肺腺癌(LUAD)和食管鳞癌(ESCC)的单细胞数据和肿瘤细胞系的顺铂IC50数据,以建立CDDP新辅助化疗评分(NCS)。差异分析,GO,KEGG,通过R进行GSVA和逻辑回归模型。将生存分析应用于公共数据库。siRNA在A549,PC9,TE1细胞系中的敲低,qRT-PCR,western-blot,cck8和EdU实验用于进一步的体外验证。
结果:485个基因在LUAD和ESCC新辅助治疗前后在肿瘤细胞中差异表达。结合CDDP相关基因后,12个基因,CAV2,PHLDA1,DUSP23,VDAC3,DSG2,SPINT2,SPATS2L,IGFBP3,CD9,ALCAM,PRSS23PERP,获得并形成NCS评分。分数越高,患者对CDDP-NACT越敏感.NCS将LUAD和ESCC分为两组。基于差异表达的基因,建立了一个模型来预测NCS的高低。CAV2,PHLDA1,ALCAM,CD9、IGBP3和VDAC3与预后显著相关。最后,我们证明A549、PC9和TE1中CAV2、PHLDA1和VDAC3的敲除显著增加了对顺铂的敏感性。
结论:开发并验证了CDDP-NACT的NCS评分和相关预测模型,以帮助选择可能从中受益的患者。
BACKGROUND: Neoadjuvant chemotherapy (NACT) becomes the first-line option for advanced tumors, while patients who are not sensitive to it may not benefit. Therefore, it is important to screen patients suitable for NACT.
METHODS: Single-cell data of lung adenocarcinoma (LUAD) and esophageal squamous carcinoma (ESCC) before and after cisplatin-containing (CDDP) NACT and cisplatin IC50 data of tumor cell lines were analyzed to establish a CDDP neoadjuvant chemotherapy score (NCS). Differential analysis, GO, KEGG, GSVA and logistic regression models were performed by R. Survival analysis were applied to public databases. siRNA knockdown in A549, PC9, TE1 cell lines, qRT-PCR, western-blot, cck8 and EdU experiments were used for further verification in vitro.
RESULTS: 485 genes were expressed differentially in tumor cells before and after neoadjuvant treatment for LUAD and ESCC. After combining the CDDP-associated genes, 12 genes, CAV2, PHLDA1, DUSP23, VDAC3, DSG2, SPINT2, SPATS2L, IGFBP3, CD9, ALCAM, PRSS23, PERP, were obtained and formed the NCS score. The higher the score, the more sensitive the patients were to CDDP-NACT. The NCS divided LUAD and ESCC into two groups. Based on differentially expressed genes, a model was constructed to predict the high and low NCS. CAV2, PHLDA1, ALCAM, CD9, IGBP3 and VDAC3 were significantly associated with prognosis. Finally, we demonstrated that the knockdown of CAV2, PHLDA1 and VDAC3 in A549, PC9 and TE1 significantly increased the sensitivity to cisplatin.
CONCLUSIONS: NCS scores and related predictive models for CDDP-NACT were developed and validated to assist in selecting patients who might benefit from it.