Sui Qihai, Hu Zhengyang, Jin Xing, Bian Yunyi, Liang Jiaqi, Zhang Huan, Yang Huiqiang, Lin Zongwu, Wang Qun, Zhan Cheng, Chen Zhencong
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Cell Biosci. 2023 Jun 8;13(1):103. doi: 10.1186/s13578-023-01061-z.
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.
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.
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.
NCS scores and related predictive models for CDDP-NACT were developed and validated to assist in selecting patients who might benefit from it.
新辅助化疗(NACT)成为晚期肿瘤的一线治疗选择,但对其不敏感的患者可能无法从中获益。因此,筛选适合NACT的患者很重要。
分析含顺铂(CDDP)的NACT前后肺腺癌(LUAD)和食管鳞状细胞癌(ESCC)的单细胞数据以及肿瘤细胞系的顺铂IC50数据,以建立CDDP新辅助化疗评分(NCS)。通过R软件进行差异分析、GO、KEGG、GSVA和逻辑回归模型分析。将生存分析应用于公共数据库。在A549、PC9、TE1细胞系中进行siRNA敲低,并通过qRT-PCR、western-blot、cck8和EdU实验进行体外进一步验证。
在LUAD和ESCC新辅助治疗前后,肿瘤细胞中有485个基因表达存在差异。结合与CDDP相关的基因后,获得了12个基因,即CAV2、PHLDA1、DUSP23、VDAC3、DSG2、SPINT2、SPATS2L、IGFBP3、CD9、ALCAM、PRSS23、PERP,并形成了NCS评分。评分越高,患者对CDDP-NACT越敏感。NCS将LUAD和ESCC分为两组。基于差异表达基因构建了一个预测高NCS和低NCS的模型。CAV2、PHLDA1、ALCAM、CD9、IGBP3和VDAC3与预后显著相关。最后,我们证明在A549、PC9和TE1中敲低CAV2、PHLDA1和VDAC3可显著增加对顺铂的敏感性。
开发并验证了CDDP-NACT的NCS评分及相关预测模型,以协助选择可能从中获益的患者。