第一部分 GSDME通过JAK/STAT3通路调控非小细胞肺癌恶性生物学行为

研究背景：Gasdermins（GSDMs）家族因介导促炎性细胞程序性死亡—细胞焦亡而备受关注。目前关于GSDMs家族的研究大多聚焦于细胞焦亡在抗肿瘤免疫过程中的作用，而关于GSDMs家族基因本身对肿瘤细胞特性的影响研究较少，GSDME在非小细胞肺癌中的作用及机制并不明确。

研究方法：本研究收集非小细胞肺癌患者的肿瘤组织标本及临床信息，通过免疫组织化学染色的方法对肿瘤组织中GSDME的表达水平进行评估，并分析GSDME表达水平与化疗疗效及预后的相关性。在细胞模型中，探索GSDME对肿瘤恶性行为及化疗敏感性的影响，并通过二代测序技术探索其潜在的机制，同时利用通路抑制剂在细胞层面和裸鼠皮下肿瘤模型层面进行验证。最后，在免疫健全小鼠皮下肿瘤模型中，探索GSDME对肿瘤免疫微环境以及化疗和抗PD-1单克隆抗体治疗敏感性的影响。

研究结果：在43例非小细胞肺癌患者中，9例患者GSDME处于高表达水平，34例患者GSDME处于低表达状态。相关性分析显示，与GSDME低表达的患者相比，GSDME高表达的患者对化疗的疗效反应更好（p值=0.023）；Kaplan-Meier生存分析显示，GSDME高表达的患者，术后无病生存期更长（中位生存时间33.3个月vs. 21.5个月，p值=0.035）。在细胞模型中，过表达GSDME能够显著抑制非小细胞肺癌的增殖、迁移、侵袭和促血管形成等恶性生物学行为，并且能提高肿瘤细胞对顺铂的敏感性；而敲低GSDME表达则可显著促进非小细胞肺癌的恶性生物学行为，并降低其对顺铂的敏感性。在裸鼠皮下肿瘤模型中，与对照组（shNC）相比，稳定敲低GSDME组（shGSDME）的肿瘤生长更快，对化疗的敏感性更差，尾静脉注射两组细胞后也发现，shGSDME组的肿瘤细胞更容易发生肺转移。二代测序结果显示，4株细胞系的GSDME干预组和对照组的差异基因均可富集到JAK-STAT通路。蛋白质免疫印迹实验发现，过表达GSDME可抑制非小细胞肺癌JAK-STAT3通路的激活，敲低GSDME则可激活JAK-STAT3通路。而p-STAT3抑制剂SH-4-54可显著逆转GSDME敲低对肿瘤细胞及裸鼠皮下肿瘤恶性行为的促进作用。在免疫健全小鼠皮下肿瘤模型中，与shNC组相比，shGSDME组肿瘤的生长速度更快，对顺铂、抗PD-1单克隆抗体的治疗敏感性也更差。二代测序结果显示，shNC组和shGSDME组的差异基因可显著富集到JAK-STAT3通路、肿瘤PD-L1表达和PD-1免疫检查点通路。通过ImmuCellAI-mouse平台对肿瘤组织中的免疫细胞组分进行估算，结果发现，与shNC组的肿瘤相比，shGSDME组的肿瘤组织中浸润的CD8⁺ T细胞减少（p值=0.01），而免疫负性调控相关的肥大细胞、Treg细胞和中性粒细胞在shGSDME组富集丰度高于shNC组，但未达到统计学意义（p值分别为0.116，0.375，0.073）。

研究结论：在非小细胞肺癌中，GSDME可能通过JAK-STAT3通路抑制肿瘤细胞的增殖、迁移、侵袭和促血管形成等恶性生物学行为，提高肿瘤对化疗的敏感性。在肿瘤微环境方面，GSDME可能通过JAK-STAT3通路介导活跃的免疫微环境，从而抑制肿瘤进展，提高肿瘤对化疗及免疫治疗的敏感性。GSDME有望成为非小细胞肺癌患者预后及疗效预测的生物标志物。

第二部分：MGA突变作为肺腺癌免疫检查点抑制剂治疗生物标志物的研究

研究背景：以抗PD-1/PD-L1单克隆抗体为代表的免疫检查点抑制剂治疗在肿瘤治疗中已经取得革命性突破，显著延长了肿瘤患者的生存期，但获益人群仍十分有限。通过探寻预测性生物标志物来更精准地识别和筛选出获益人群是目前研究的热点，也是提高肿瘤患者生存质量、延长肿瘤患者生存期的关键。

研究方法：基于MSKCC队列，我们在接受免疫检查点抑制剂（immune checkpoint inhibitors，ICIs）治疗的多种肿瘤患者中分析了Max关联蛋白（Max’s giant associated protein，MGA）突变对免疫治疗疗效和预后的预测作用，并在验证队列中进行了验证。另外，我们针对TCGA数据库中的肺腺癌转录组测序数据进行了基因集富集分析（gene set enrichment analysis，GSEA）和免疫细胞浸润分析，旨在探索MGA突变作为ICIs疗效和预后标志物的潜在机制。

研究结果：在MSKCC发现队列中，MGA突变可预测肺腺癌患者接受ICIs治疗的疗效，也可作为接受ICIs治疗的肺腺癌患者的预后标志物，但在其他肿瘤中未观察到这一现象。另外，我们也发现MGA突变与TMB评分呈正相关。验证队列的结果与发现队列中肺腺癌的结果一致。并且，在低TMB或高PD-L1表达亚组中，MGA突变的患者有更长的生存期。多因素分析结果表明，MGA突变是接受ICIs治疗的肺腺癌患者的独立预后标志物。在机制上，我们发现PTPRD等与MGA共突变的基因并不影响MGA突变对免疫检查点抑制剂预后的预测作用。此外，GSEA分析结果显示，原发性免疫缺陷通路相关基因在MGA野生型组中显著富集。免疫细胞浸润分析结果表明，MGA突变型的肺腺癌患者中活化的NK细胞含量更多。

研究结论：肿瘤组织MGA突变是肺腺癌免疫检查点抑制剂治疗的疗效和预后的预测标志物，并且该预测作用可独立于PD-L1表达和TMB。这些结果可能为筛选ICIs治疗的潜在获益人群提供了新的参考。

Part 1：GSDME regulate malignant behavior of non-small cell lung cancer through JAK/STAT3 signaling pathway 

Background: The gasdermins (GSDMs) family has attracted much attention for its role in mediating proinflammatory programmed cell death­­–pyroptosis. At present, most of the studies on GSDMs family focus on their role in antitumor immunity, but little attention has been paid to the effect of GSDMs family on the characteristics of tumor cells. The role and mechanism of GSDME in non-small cell lung cancer (NSCLC) are unclear.

Methods: Tumor tissue specimens and clinical information of NSCLC patients were collected in this study. The expression level of GSDME in tumor tissues was evaluated by immunohistochemical staining, and the correlation between GSDME expression level and chemotherapy efficacy and prognosis was analyzed. In the cell model, the effect of GSDME on the malignant behavior and chemosensitivity of NSCLC was explored, and the underlying mechanism was explored by the next-generation sequencing analysis. The pathway inhibitors were used to verify the effect of GSDME on NSCLC at the cell level and subcutaneous tumor model level in nude mice. Finally, the effects of GSDME on tumor immune microenvironment and sensitivity to chemotherapy and anti-PD-1 monoclonal antibody treatment were explored in the subcutaneous tumor models of immunocompetent mouse.

Results: Among the 43 NSCLC patients, GSDME was highly expressed in 9 patients and low or no expression in 34 patients. Correlation analysis showed that patients with high expression of GSDME had a better response to chemotherapy than those with low expression of GSDME (p value=0.023). Kaplan-Meier survival analysis showed that patients with high expression of GSDME had a longer disease-free survival (median survival times: 33.3 months vs. 21.5 months, p value=0.035). In the cell model, overexpression of GSDME significantly inhibited the proliferation, migration, invasion, angiogenesis and other malignant biological behaviors of NSCLC cells, and increased the sensitivity of tumor cells to cisplatin. Knockdown of GSDME expression can significantly promote the malignant biological behavior of NSCLC and reduce its sensitivity to cisplatin. In the nude mice experiment, compared with the control group (shNC), the tumor in the stable knockdown of GSDME group (shGSDME) grew faster, the tumor cells injected into the tail vein were more likely to develop lung metastasis, and the sensitivity of the tumor to cisplatin was decreased, and the response to chemotherapy was worse. The results of next-generation sequencing showed that the JAK-STAT pathway was enriched by functional enrichment analysis of differential genes in the four cell lines of GSDME intervention group and control group. Western blot showed that overexpression of GSDME inhibited the activation of JAK-STAT3 pathway in NSCLC cells, while knockdown of GSDME activated the JAK-STAT3 pathway in NSCLC cells. The p-STAT3 inhibitor SH-4-54 could significantly reverse the promoting effect of GSDME knockdown in tumor cells and subcutaneous model of nude mice. In the subcutaneous model of immunocompetent mice, the tumors expressed in the shGSDME group grew faster and were less sensitive to cisplatin and anti-PD-1 monoclonal antibody than those in the shNC group. The next-generation sequencing results showed that functional enrichment analysis of the differential genes in the shNC group and the shGSDME group showed that JAK-STAT3 pathway, PD-L1 expression and PD-1 checkpoint pathway were significantly enriched. The ImmuCellAI-mouse platform was used to calculate the abundance of immune cells in tumor tissues. The results showed that the infiltrating CD8⁺ T cells in tumor tissues of shGSDME group were significantly decreased compared with those of shNC group (p value=0.01). The enrichment and abundance of immune-negative regulation cells, such as mast cells, Treg cells and neutrophils in the shGSDME group were higher than those in the shNC group, but the difference was not statistically significant (p value= 0.116, 0.375, 0.073, respectively).

Conclusions: In NSCLC, GSDME may inhibit the proliferation, migration, invasion, angiogenesis and other malignant biological behaviors of tumor cells by inhibiting the JAK-STAT3 pathway, and it could improve the sensitivity of the tumor to chemotherapy. In terms of tumor microenvironment, GSDME may mediate active immune microenvironment by inhibiting the JAK-STAT3 pathway, thereby inhibiting tumor progression and improving tumor response to chemotherapy and immunotherapy. GSDME is expected to be a biomarker for the prognosis and efficacy prediction of patients with NSCLC.

Part 2：MGA mutation as a biomarker for immunotherapy for patients with lung adenocarcinoma

Abstract

Background: With the continuous revolutionary breakthrough of immune checkpoint inhibitors (ICIs) therapy represented by anti-PD-1/PD-L1 monoclonal antibody in tumor treatment, which significantly prolongs the survival of tumor patients, how to find better predictive biomarkers to identify and screen patients who are effective to ICIs therapy has become the current problem to improve the quality of life of cancer patients. It is one of the most important research hotspots to prolong the survival of cancer patients.

Methods: The predictive effect of Max’s giant associated protein (MGA) mutations on the response and prognosis of ICIs treatment in multiple tumor types was analyzed in the MSKCC cohort and validated in a validation cohort. In addition, gene set enrichment analysis (GSEA) and immune cell infiltration analysis were performed on lung adenocarcinoma transcriptome sequencing data of the TCGA database to explore the potential mechanism of MGA mutation as a potential biomarker for ICIs efficacy and prognosis.

Results: In the MSKCC discovery cohort, MGA mutation was a marker of ICIs efficacy and prognostic in patients with lung adenocarcinoma (LUAD), while was not in patients with other tumor types. MGA mutation was positively correlated with TMB score. The results of the validation cohort were consistent with those of the discovery cohort in LUAD patients. Moreover, patients with MGA mutations had longer survival in the low TMB or high PD-L1 expression subgroups. Multivariate analysis showed that MGA mutation was an independent prognostic marker in LUAD patients treated with ICIs. Mechanistically, we found that MGA’s co-mutated genes (PTRPD et al.) did not affect the predictive role of MGA mutation on the prognosis of immune checkpoint inhibitors. In addition, GSEA showed that primary immunodeficiency pathway was enriched in the MGA wild-type group. Immune cell infiltration analysis showed that activated NK cells were more abundant in MGA-mutant LUAD patients.

Conclusion: Tumor tissue MGA mutation could be a predictive biomarker for the response and prognosis of ICIs therapy in patients with LUAD, independent of PD-L1 expression and TMB. These results may provide a new insight for identifying patients with LUAD who may potentially benefit from ICIs.