Abstract B53: Molecular network analysis identifies GRN as a key regulator of chemotherapy resistance in small cell lung cancer

Seungyeul Yoo, Ayushi Patel, Yi Zhong, Feng Jiang,Wenhui Wang,Hideo Watanabe,Jun Zhu

Cancer Immunology Research(2022)

引用 0|浏览11
暂无评分
摘要
Abstract Small cell lung cancer (SCLC), which comprises about 15% of lung cancer cases, is the most aggressive and deadliest type of lung cancer with extremely poor clinical outcomes (about 6% of 5-year overall survival). For about the last three decades, combinatory chemotherapy of etoposide and platinum (EP) treatment has been used as the standard first-line treatment for SCCL. While tumors are generally responsive to the EP treatment, in most cases, they rapidly relapse and acquire resistance after the treatment. However, detailed mechanisms underlying the acquired chemoresistance are not well understood. In this study, we constructed a SCLC comprehensive regulatory network using 135 SCLC tumors, projected chemo-resistant signature genes derived from patient-derived xenografts and genetically engineered mouse models on the network, and identified Granulin (GRN) as a key regulator of the chemo-resistant genes. In multiple independent SCLC datasets, expression levels of GRN and its associated genes increase with the EP treatment and show anti-correlation with neuroendocrine (NE) features of SCLC. Yap activation in a SCLC mouse model increases Grn expression suggesting Yap1 as a potential upstream regulator of Grn. But, on the other hand, the expression levels of GRN and its associated genes are up-regulated in EP treated patient-derived CDX models compared to treatment naïve ones, in which YAP1 expression is depleted in both groups, suggesting YAP1 independent GRN functions associated with chemoresistance. Our observations were validated using 4 SCLC cell lines having different GRN expressions (GRNhigh: SHP77 and H841 and GRNlow: H524 and H2081). The GRNlow showed better responses to the EP treatment compared to the GRNhigh cells (IC50: GRNhigh > 1𝜇M; GRNlow ≈ 1nM). Furthermore, the GRNlow cells with GRN over-expression acquired resistance to the treatment suggesting that GRN expression in SCLC is sufficient for chemo-resistance regardless of YAP1 activation. When we stratified SCLC patients using GRN and its associated genes, the patients in the GRN low group received clear benefits of the chemotherapy with better survival than ones without the treatment (LRT p=0.004) while there were no survival differences among patients regardless of the treatment in the GRN high group. Interestingly, immune checkpoint blockade marker genes were significantly up-regulated in patients from the GRN high group (p= 1.8×10-5, 4.8×10-5, 3.5×10-5, and 0.0002 for PDCD1, CD274, PDCD1LG2, and CTLA4, respectively). Combining this with an observation of that GRN and its associated genes were associated with high PDL1 expression in non-NE SCLC mouse models, immunotherapies might be a potentially effective treatment option for the GRN high group. Our study suggests GRN as a novel key regulator modulating chemo-resistance as well as a potential biomarker for immunotherapy response in SCLC and, hence, provide valuable information in the clinical decisions for better diagnosis, prognosis, and treatment for the purpose of precision medicine. Citation Format: Seungyeul Yoo, Ayushi Patel, Yi Zhong, Feng Jiang, Wenhui Wang, Hideo Watanabe, Jun Zhu. Molecular network analysis identifies GRN as a key regulator of chemotherapy resistance in small cell lung cancer [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy; 2022 Oct 21-24; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(12 Suppl):Abstract nr B53.
更多
查看译文
关键词
abstract b53,chemotherapy resistance,molecular network analysis,lung cancer
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要