A novel defined risk signature of endoplasmic reticulum stress-related genes for predicting the prognosis and immune infiltration status of ovarian cancer

A novel defined risk signature of endoplasmic reticulum stress-related genes for predicting the prognosis and immune infiltration status of ovarian cancer 基于内质网应激相关基因构建新型风险模型用于卵巢癌预后及免疫浸润状态的预测 1 2 equal first-author https://orcid.org/0000-0002-2418-1745 3 equal https://orcid.org/0000-0003-0974-4463 4 1 2 5 1 1 2 corresp Hua JIANG, jianghua_fckyy@126.com Hua JIANG, jianghua_fckyy@126.com jianghua_fckyy@126.com https://orcid.org/0000-0002-5235-341X 复旦大学附属妇产科医院， 中国上海， 200011 复旦大学附属妇产科医院， 中国上海， 200011 Obstetrics and Gynecology Hospital, Fudan University, Shanghai 200011, China Obstetrics and Gynecology Hospital, Fudan University, Shanghai 200011, China 复旦大学附属妇产科医院上海市女性生殖内分泌相关疾病重点实验室， 中国上海， 200011 复旦大学附属妇产科医院上海市女性生殖内分泌相关疾病重点实验室， 中国上海， 200011 Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital, Fudan University, Shanghai 200011, China Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital, Fudan University, Shanghai 200011, China 上海交通大学医学院附属第六人民医院肿瘤科， 上海交通大学医学院， 中国上海， 200233 上海交通大学医学院附属第六人民医院肿瘤科， 上海交通大学医学院， 中国上海， 200233 Department of Oncology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China Department of Oncology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China 嘉兴学院附属妇幼保健院妇产科， 中国嘉兴， 314050 嘉兴学院附属妇幼保健院妇产科， 中国嘉兴， 314050 Department of Gynecology, Jiaxing University Affiliated Women and Children Hospital, Jiaxing 314050, China Department of Gynecology, Jiaxing University Affiliated Women and Children Hospital, Jiaxing 314050, China 浙江大学医学院附属妇科医院病理科， 中国杭州， 310006 浙江大学医学院附属妇科医院病理科， 中国杭州， 310006 Department of Pathology, Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310006, China Department of Pathology, Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310006, China Endoplasmic reticulum (ER) stress, as an emerging hallmark feature of cancer, has a considerable impact on cell proliferation, metastasis, invasion, and chemotherapy resistance. Ovarian cancer (OvCa) is one of the leading causes of cancer-related mortality across the world due to the late stage of disease at diagnosis. Studies have explored the influence of ER stress on OvCa in recent years, while the predictive role of ER stress-related genes in OvCa prognosis remains unexplored. Here, we enrolled 552 cases of ER stress-related genes involved in OvCa from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts for the screening of prognosis-related genes. The least absolute shrinkage and selection operator (LASSO) regression was applied to establish an ER stress-related risk signature based on the TCGA cohort. A seven-gene signature revealed a favorable predictive efficacy for the TCGA, International Cancer Genome Consortium (ICGC), and another GEO cohort ( P < 0.001, P < 0.001, and P =0.04, respectively). Moreover, functional annotation indicated that this signature was enriched in cellular response and senescence, cytokines interaction, as well as multiple immune-associated terms. The immune infiltration profiles further delineated an immunologic unresponsive status in the high-risk group. In conclusion, ER stress-related genes are vital factors predicting the prognosis of OvCa, and possess great application potential in the clinic. 目的 2 开发一种基于内质网应激相关基因的预后模型，可有效预测卵巢癌（OvCa）患者的总生存期和免疫浸润状态。创新点: OvCa是一种致死率极高的妇科恶性肿瘤，具有高度的侵袭性及肿瘤异质性。大量临床研究显示OvCa对免疫治疗的应答率极低，提示瘤内免疫浸润状态不佳。因此，需要开发更为可靠的基因标志物用于预测患者的预后和免疫浸润状态。研究显示内质网应激相关通路与卵巢癌预后密切相关，但尚缺乏基于该通路相关基因的模型用以预测患者的临床预后。本研究基于内质网应激相关基因构建了一种新型风险模型，用于患者的预后风险分层和总体生存率预测。同时，基于对肿瘤免疫浸润状态评估，该风险模型提示内质网应激的选择性激活或可改善免疫治疗在OvCa中的疗效。 方法 2 首先从TCGA和GEO数据库下载了552例含有RNA测序及临床信息的OvCa病例数据；并从GeneCards中提取了785个被定义为内质网应激相关的基因。然后结合单因素Cox回归分析和LASSO回归分析建立基于内质网应激基因的预后模型。在TCGA队列训练后，我们又纳入两个外部数据集进行Kaplan-Meier生存分析和时间依赖性受试者工作特征曲线（ROC）分析验证了其预后预测的性能。此外，我们还进行了GO、KEGG和GSEA功能富集分析；应用CIBERSORT算法描绘了风险分组中免疫浸润状态差异。 结论 2 本研究构建了由7个内质网应激相关基因构成的预后模型，可在训练集和验证集中有效区分高风险OvCa患者，并被证明是总生存期的独立预后因子。利用诺谟图进行基于该风险特征的生存率预测。后续分析显示高低风险人群存在内质网应激通路激活的分支差异。功能富集和免疫浸润分析表明该风险特征与肿瘤免疫应答状态密切相关。综上，基于内质网应激相关基因的预后模型是一种很有前景的工具，可进行风险分层、生存预测和免疫浸润状态的评估。 卵巢癌（OvCa） 内质网应激 风险模型 预后 免疫浸润 Ovarian cancer (OvCa) Endoplasmic reticulum (ER) stress Risk signature Prognosis Immune infiltration 1 Introduction 1 Ovarian cancer (OvCa) is the most lethal malignancy occurring in the female reproductive system, globally ranked as the eighth leading cause of female cancer-related deaths ( Sung et al., 2021 Sung et al., 2021 ; Tian et al., 2022 Tian et al., 2022 ). According to the global cancer statistics, the number of new OvCa cases reached 313 959 in 2020 with 207 252 deaths ( Sung et al., 2021 Sung et al., 2021 ). Therapeutic advancements, including the application of targeted drugs, such as poly adenosine diphosphate (ADP)‍-ribose polymerase (PARP) inhibitors ( González-Martín et al., 2019 González-Martín et al., 2019 ; Poveda et al., 2021 Poveda et al., 2021 ) or anti-angiogenesis agents ( Pujade-Lauraine et al., 2014 Pujade-Lauraine et al., 2014 ), and reinspection of secondary cytoreduction ( Harter et al., 2021 Harter et al., 2021 ), have improved the outcomes of OvCa patients to some extent, with an overall five-year survival rate of 47% ( Lheureux et al., 2019 Lheureux et al., 2019 ). In this scenario, prognosis prediction is crucial for patients to obtain meaningful treatment, but is hindered by the high heterogeneity of OvCa. Strikingly, numerous risk models, including the ferroptosis-based ( Ye et al., 2021 Ye et al., 2021 ), autophagy-based ( Fei et al., 2021 Fei et al., 2021 ), and immune-related ( Zhang B et al., 2021 Zhang B et al., 2021 ) approaches, have been developed to predict OvCa patients’ prognosis along with the application of bioinformatics. Despite that commonalities may be present, the gene signatures derived from the variety of phenotypes highlight the different aspects of disease. Thus, novel gene signatures based on the core processes of cell fate and interaction with the surroundings need to be constantly explored to improve the accessibility of prognostic prediction for OvCa. Protein handling, modification, and assembly in the endoplasmic reticulum (ER) are tightly regulated processes that determine cell function and fate ( Chen and Cubillos-Ruiz, 2021 Chen and Cubillos-Ruiz, 2021 ). ER stress occurs when mammalian cells encounter exogenous cell stress, such as hypoxia, nutrient deprivation, and the accumulation of reactive oxygen species (ROS), causing a burden of misfolded proteins in the ER lumen ( Andrews et al., 2021 Andrews et al., 2021 ). Three sensors that detect ER stress, including inositol-requiring enzyme 1α (IRE1α)/X-box-binding protein 1 (XBP1), protein kinase RNA-like ER kinase (PERK), and activating transcription factor 6 (ATF6), then ensue to restore homeostasis ( Cubillos-Ruiz et al., 2016 Cubillos-Ruiz et al., 2016 ). Meanwhile, under the unremitting stress, cells are inclined to undergo apoptosis through effector proteins such as CCAAT/enhancer binding protein (C/EBP)‍-homologous protein (CHOP) ( Lin et al., 2021 Lin et al., 2021 ). The critical role of ER stress orchestrating adaptive programs to modulate cancer cell fate has recently been highlighted in the realm of OvCa research. By targeting the IRE1α/XBP1 pathway, Lin et al. (2021) Lin et al. (2021) found that B-I09, an IRE1α inhibitor, can suppress the growth of OvCa cells with certain mutations in vitro and in xenograft models. Surprisingly, the IRE1α/XBP1 pathway was also involved in the regulation of OvCa stemness according to an eminent work by Zhang et al. (2022) Zhang et al. (2022) . A newly defined stem-related transcription factor (TF), forkhead box K2 (FOXK2), directly upregulates the IRE1α expression, leading to the formation of XBP1 and the initiation of stemness pathways ( Zhang et al., 2022 Zhang et al., 2022 ). In contrast, activation of PERK branch together with the ATF4-mediated transcriptional induction of CHOP is greatly regarded as a symbol of pro-apoptosis. A study conducted by Lee et al. (2020) Lee et al. (2020) ascertained the pro-apoptotic role of PERK arm, in which the application of apomorphine induced mitochondrion-associated apoptosis and triggered ER stress accompanied by phosphorylation of PERK in OvCa. However, the role of ATF6 arm in OvCa remains to be explored. The ER stress-related apoptosis is deemed to be a kind of immunogenic cell death (ICD), which is characterized by the exposure of damage-associated molecular patterns (DAMPs), such as calreticulin (CRT) and heat shock proteins (HSPs) ( Galluzzi et al., 2017 Galluzzi et al., 2017 ). Studies have indicated that CRT exposure was able to provide a robust innate and adaptive antitumor immune response, leading to favorable prognosis in OvCa patients ( Kasikova et al., 2019 Kasikova et al., 2019 ). The tumor microenvironment (TME) is replete with factors that cause stress to intratumoral immune cells ( Andrews et al., 2021 Andrews et al., 2021 ); thus, the ER stress pathway is also implicated in infiltrating immune cells ( Lin et al., 2021 Lin et al., 2021 ). Unlike its pro-survival role in OvCa cells, IRE1α/XBP1 arm activation in dendritic cells (DCs) impaired the function of antigen presentation under the OvCa milieu, further driving disease progression ( Cubillos-Ruiz et al., 2015 Cubillos-Ruiz et al., 2015 ). Based on these findings, investigations are necessary to ascertain the ambiguous role of ER stress in the TME. In this study, we enrolled 552 cases of OvCa-involved ER stress-related genes from two datasets to form a seven-gene risk signature. By employing two external cohorts, we validated the accuracy and credibility of our model, and ascertained that the gene signature was an independent predictive factor for OvCa patients. Overall, our study successfully constructed an ER stress-related risk model that can be potentially applied in the clinic. 2 Results 1 2.1 Development of a risk model using seven identified ER stress-related genes 2 We identified the prognosis-related genes from The Cancer Genome Atlas (TCGA)‍-ovarian cancer (OV) cohort ( n =368) and the Gene Expression Omnibus (GEO) dataset (accession number: GSE26712; n =184) by univariate Cox regression analyses (Tables S1 and S2). The gene numbers were shown in the workflow diagram ( Fig. 1 Fig. 1 a). After intersection, eight possible prognosis-related genes were screened out ( P < 0.05), namely, transient receptor potential cation channel subfamily Ⅴ member 4 ( TRPV4 ), insulin-like growth factor 2 receptor ( IGF2R ), forkhead box O1 ( FOXO1 ; absent in GSE49997 dataset), retinoblastoma 1 ( RB1 ) gene, heat shock protein (HSP) family A (HSP70) member 2 ( HSPA2 ), paxillin ( PXN ), transporter 1 adenosine triphosphate (ATP)‍-binding cassette subfamily B member ( TAP1 ), and ATPase sarcoplasmic/endoplasmic reticulum Ca 2+ transporting 3 ( ATP2A3 ). The least absolute shrinkage and selection operator (LASSO) regression analysis was then performed to select the most robust prognostic genes from the eight ER stress-related genes. Finally, seven of the eight genes and their coefficients were retained according to the optimal λ value decided by the minimum criteria (Figs. 1 1 b and 1 1 c). Among these genes, ATP2A3 and TAP1 were protective factors for OvCa survival, with hazard ratio (HR) < 1; while FOXO1 , HSPA2 , RB1 , TRPV4 , and IGF2R were risk factors with HR > 1 ( Fig. 1 Fig. 1 d). A correlation network based on the expression profiles of seven genes was constructed to identify the relationships among them ( Fig. 1 Fig. 1 e). 2.2 Development of an ER stress-related risk signature in the TCGA-OV cohort 2 Given the privilege of sufficient sample size, the TCGA-OV cohort was designated for building the risk signature. The formula for calculating the risk score was as follows: risk score=(-0.3963× ATP2A3 expression)‍+‍(0.2318× FOXO1 ‍expression)‍+‍(0.0795× HSPA2 expression)‍+‍(0.1691× RB1 expression)‍+‍(0.4853× TRPV4 expression)‍+‍(0.3016× IGF2R expression)‍+‍(‍-‍0.2078× TAP1 expression). According to the median risk score, 184 patients were classified as the low-risk group, while the remaining 184 were classified as the high-risk group ( Fig. 2 Fig. 2 a). Principal component analysis (PCA) and t -distributed stochastic neighbor embedding ( t -SNE) analysis were conducted to assign the patients in these clusters (Figs. S1a and S1b). The overall survival (OS)-related prediction model distribution of patients was illustrated in Fig. 2 Fig. 2 b, implying that patients in the high-risk group had a higher possibility of death and shorter survival time. The expression level of each ER stress-related signature was obviously changed between the two groups ( Fig. 2 Fig. 2 c). The Kaplan-Meier (K-M) curves showed that patients in the low-risk group had a more favorable survival outcome than those in the high-risk group ( P < 0.0001; Fig. 2 Fig. 2 d). Time-dependent receiver operating characteristic (ROC) curves were conducted for assessing the predictive role of ER stress-related risk signature on OS. As presented in Fig. 2 Fig. 2 e, the area under the curve (AUC) was 0.689 for one year, 0.657 for two years, and 0.619 for three years. The K-M curves of seven single genes were further extended to validate the predictive value of this signature in the TCGA-OV cohort (Fig. S2). 2.3 Independent prognostic value of ER stress-related risk signature in the TCGA-OV cohort 2 Univariate and multivariate Cox analyses were subsequently applied to explore whether the risk score could be an independent risk factor in the TCGA-OV training cohort. As illustrated in Figs. 3 3 a and 3 3 b, the ER stress-related risk signature was significantly correlated with the OS of OvCa patients (HR, 2.99; 95% confidence interval (CI), 2.08‍–4.29; P < 0.001; refer to multivariate Cox analyses), indicating that the ER stress-related risk signature constructed by the TCGA-OV cohort was an independent prognostic factor for OvCa patients. The multi-indicator ROC curves ( Fig. 3 Fig. 3 c) showed the predictive value of the risk signature and the clinical features, which indicated that the predictive accuracy of the ER stress-related risk model was superior in terms of age, grade, and stage. Furthermore, a nomogram integrating ER stress risk signature, grade, age, and stage was produced to predict 1-, 3-, and 5-year OSs in the TCGA-OV cohort ( Fig. 3 Fig. 3 d). In the nomogram, each item was assigned to point according to its risk contribution to OS. Calibration curves were used for internal verification of the nomogram ( Fig. 3 Fig. 3 e). Collectively, these data suggested that the ER stress-related risk signature could serve as an independent risk factor in the TCGA-OV cohort. 2.4 Validation of ER stress-related risk signature in the International Cancer Genome Consortium (ICGC) and GEO cohorts 2 A total of 117 cases from the ICGC and 193 cases from the GEO dataset (accession number: GSE49997) were treated as the external validation sets. Seven or six ( FOXO1 is absent in GSE49997) survival-related genes were extracted from the expression profiling array. The risk score of each sample in the two validation sets was calculated, using the same formula as that in the TCGA-OV cohort. PCA and t -SNE analyses were used to visualize the distribution of risk amongst different populations in line with the risk gene sets (Figs. S1c–S1f). Figs. 4 4 a and 4 4 b showed the OS-related risk model distribution of populations in the ICGC and GEO datasets, respectively. The heatmaps representing the expression level of each risk signature related to ER stress, showed the tendency of changes between the low- and high-risk populations in the validation sets (Figs. 4 4 c and 4 4 d). Interestingly, we further found that the high-risk group had a significantly lower survival possibility than that of the low-risk group in both validation sets ( P =0.0032 in ICGC cohort and P =0.04 in GSE49997 cohort; Figs. 4 4 e and 4 4 f). And then, time-dependent ROC curves were drawn to evaluate the predictive value of ER stress-related risk signature in the validation sets. As shown in Figs. 4 4 g and 4 4 h, the AUC was 0.623 for two years and three years in the ICGC cohort, and it was 0.673 for one year, 0.654 for two years, and 0.612 for three years in the GSE49997 cohort, indicating the robust predictive role of our model in the validation cohorts. The forest plots of univariate and multivariate Cox analyses were applied again for the purpose of identifying the independent prognostic role of our risk model (Figs. S1g and S1h). Nomograms integrated by ER stress risk signature and accessible clinical parameters were also constructed to predict the OS in both validation cohorts (Figs. S1i and S1j). Calibration curves were used for internal verification of the nomogram (Figs. S1k and S1l). The above data tested in two external cohorts demonstrated the robustness of this risk model. 2.5 Correlation of the risk signature with canonical ER stress pathways and its functional annotation 2 Three canonical ER stress pathways have been previously identified that may determine the cell fate through different orientations. The correlation between our risk signature and the hub genes of these canonical ER stress pathways was analyzed to identify ER stress status in different OvCa groups. In the high-risk group, the levels of IRE1α and PERK were higher than those in the low-risk group, though with a smaller statistical significance in the GSE49997 dataset. Interestingly, the pro-apoptosis arm ( ATF4 and CHOP ) was upregulated in the low-risk group, demonstrating the cell fate-related role of our signature ( Figs. 5 Figs. 5 a‍–‍5c). To estimate the function of these prognosis-related genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. The top five enrichment terms of GO are shown in Fig. 5 Fig. 5 d, and the top four enrichments of KEGG are shown in Fig. 5 Fig. 5 e. The gene set enrichment analysis (GSEA) approach was further employed to replenish the function annotation of these genes. The results demonstrated that these genes were enriched in multiple cytokines interaction and immune-associated terms (Fig. S3). 2.6 Immune infiltrating profiles of ER stress-related risk signature 2 Considering the accumulating evidence that immune cells infiltrated into the OvCa environment play a pivotal role in disease progression, a heatmap was performed to display the distribution profile of immune cells of each case in the TCGA-OV cohort according to the risk score ( Fig. 6 Fig. 6 a). The CIBERSORT algorithm was further applied to clarify the correlation between ER stress-related risk signature and immune infiltration. Fig. 6 Fig. 6 b revealed that the fraction of immune cells varied among the cases and groups; Fig. 6 Fig. 6 c presented the significant differences of immune cell infiltration between the low- and high-risk groups. For the innate immunity cluster, the proportions of dendritic cells (DCs), M1 macrophages, and activated natural killer (NK) cells were significantly decreased in the high-risk group; conversely, the proportions of M0 macrophages, M2 macrophages, activated mast cells, and neutrophils were elevated in the high-risk group. For the other part of the immune system, that is, the adaptive immunity, there were lower gatherings of memory B cells, activated memory cluster of differentiation 4-positive (CD4 + ) T cells, CD8 + T cells, and follicular helper T cells (Tfh) in the high-risk group, which indicated a potentially decreased anti-tumor efficiency. The immune-related molecules expressed in the OvCa milieu were subsequently analyzed. As shown in Fig. 6 Fig. 6 d, the expression levels of both immune-activated and immunosuppressive molecules were declined in the high-risk group vs. the low-risk group. Interestingly, among the seven genes, TAP1 was identified as the most typical player related to immune function, which was implicated in the assembly of antigen peptide-major histocompatibility complex-Ⅰ (pMHC-Ⅰ) ( Han et al., 2008 Han et al., 2008 ). Given the knowledge that the activation of CD8 + T cells relies on the recognition of pMHC-Ⅰ, correlation analysis was conducted in three cohorts (Figs. 6 6 e– 6 6 g). The expression level of TAP1 was significantly positively correlated with CD8 , which might imply the infiltrating state of the anti-tumor component. Taken together, these results support the hypothesis that the ER stress-related risk signature might influence the disease progression by interacting with the immune microenvironment in OvCa. 3 Discussion 1 In this study, a seven-gene risk model related to ER stress was established for predicting the prognosis of OvCa patients. Particularly, we enrolled two datasets, with a total of 552 cases for the screening of prognostic genes, and applied the TCGA-OV cohort for risk model training based on sample size. Another two external datasets containing 304 cases were subsequently employed for validation. The K-M plots and nomograms showed a reliable characteristic, and the ROC curves of each cohort demonstrated the excellent robustness of our model. A close correlation between canonical ER stress pathway and our risk signature was further established. Finally, functional annotation and immune infiltration were performed to evaluate the profiles of the seven-gene panel in detail. Although numerous studies have explored the influence of ER stress on OvCa in recent years ( Barez et al., 2020 Barez et al., 2020 ; Lin et al., 2021 Lin et al., 2021 ; Zundell et al., 2021 Zundell et al., 2021 ; Cheng et al., 2022 Cheng et al., 2022 ), there is a surprising lack of reviews and bioinformatics based on this phenotype. We involved seven genes in our proposed model, and these genes could be divided into two groups: pernicious factors ( FOXO1 , RB1 , HSPA2 , IGF2R , and TRPV4 ) and protective factors ( ATP2A3 and TAP1 ). FOXO1 protein, a TF encoded by FOXO1 , has been reported to be critical in many cell processes, such as cell cycle modulation and oxidative stress regulation ( Gao et al., 2012 Gao et al., 2012 ). According to Liu et al. (2020) Liu et al. (2020) , the overexpression of FOXO1 was correlated with poor prognosis in OvCa. More recently, the role of FOXO proteins in cellular response to antitumor agents was reviewed by Beretta et al. (2019) Beretta et al. (2019) . Remarkably, many studies have depicted the chemo-resistant role of FOXO1 in the realm of OvCa research ( Goto et al., 2008 Goto et al., 2008 ; Wang et al., 2015 Wang et al., 2015 ), while additional studies, as one performed by Tang et al. (2021) Tang et al. (2021) , took a view to illustrate the relations between FOXO1-related pathway and ER stress; such studies are urgently needed. RB1 , a tumor suppressor, was reported as commonly inactivated along with defective DNA repair in high-grade serous carcinoma (HGSC) ( Patch et al., 2015 Patch et al., 2015 ; Shi et al., 2020 Shi et al., 2020 ). In line with our findings, Garsed et al. (2018) Garsed et al. (2018) has shown that OvCa patients with RB1 loss were associated with favorable outcomes. The underlying mechanism of this phenomenon may be attributable to dysfunction of mitochondria, which rendered vulnerabilities to stress conditions ( Nicolay et al., 2015 Nicolay et al., 2015 ). Meanwhile, the detailed functions of RB1 in OvCa related to ER stress remain to be uncovered. Known as a stress-related gene, HSPA2 belongs to the HSP70 subfamily of heat shock genes (Ścieglińska et al., 2008). Its overexpression is an ominous symbol associated with aggressive progression and poor prognosis in cancers, including esophageal carcinoma ( Zhang et al., 2013 Zhang et al., 2013 ), pancreatic adenocarcinoma ( Zhai et al., 2021 Zhai et al., 2021 ), lung cancer ( Sojka et al., 2019 Sojka et al., 2019 ), breast cancer ( Yang et al., 2020 Yang et al., 2020 ), and epithelial OvCa ( Zhao et al., 2021 Zhao et al., 2021 ). Cao et al. (2019) Cao et al. (2019) aimed to reveal the relationship between HSPA2 and ER stress, and found that HSPA2 knockdown in lung adenocarcinoma cell lines upregulated the levels of IRE1α and PERK proteins, resulting in G1/S phase arrest via regulation of the extracellular-signal-regulated kinase 1/2 (Erk1/2) pathway. This critical role of HSPA2 contained in our risk model may evoke additional researches in this field. IGF2R , also known as mannose-6-phosphate receptor ( M6P ), is generally considered as a tumor suppressor gene for its antagonistic activity to IGF1R signals ( Leksa et al., 2017 Leksa et al., 2017 ). A loss of heterozygosity (LOH) proximal to the IGF2R / M6P locus has been proved to be significantly correlated with the presence of disseminated tumor cells (DTCs) and shorter survival time in OvCa patients ( Kuhlmann et al., 2011 Kuhlmann et al., 2011 ). Focusing on the detailed mechanism of trafficking, Wahba et al. (2018) Wahba et al. (2018) found that the synergistic effect of chemo-immunotherapy was partly dependent on the shuttling of M6P to the OvCa cell surface. The reversed scenario that IGF2R serves as a hallmark of cancer has been recently demonstrated in a variety of cancers ( Takeda et al., 2019 Takeda et al., 2019 ; Zhang ZY et al., 2021 Zhang ZY et al., 2021 ). By disrupting the Golgi-to-lysosome transport of M6P-tagged cathepsins, the loss of IGF2R decreased lysosomal activity, with the dysfunction of both autophagy and mitophagy, resulting in the accumulation of misfolded proteins and the production of ROS ( Takeda et al., 2019 Takeda et al., 2019 ), which may interact with ER stress-induced apoptosis. TRPV4 is ubiquitously expressed in the central nervous system and mediates a lot of neuropathological processes ( Wang et al., 2019 Wang et al., 2019 ; Liu et al., 2022 Liu et al., 2022 ). Meanwhile, in glioma, eminent work by Huang et al. (2021) Huang et al. (2021) showed that the TRPV4 level is positively correlated with both tumor grade and poor survival. Therein, the application of cannabidiol (CBD) induced lethal mitophagy through activating TRPV4 in human glioma cells. Later transcriptome analysis demonstrated that ER stress and the downstream of TRPV4 were involved in CBD-induced mitophagy in glioma cells ( Huang et al., 2021 Huang et al., 2021 ). Meanwhile, TRPV4 was reported as highly expressed and associated with poor prognosis in OvCa patients. Further bioinformatics suggested that TRPV4 might act as an oncogene through an immunosuppressive effect along with the underlying mechanism of resistance to platinum ( Wang et al., 2021 Wang et al., 2021 ). As a member of sarco/endoplasmic reticulum (SR/ER) Ca 2+ ATPase pump (SERCA) family ( Chemaly et al., 2018 Chemaly et al., 2018 ), ATP2A3 has recently been shown to be a potential target of salinomycin through the inhibition of Ca 2+ release and the induction of ER stress in prostate cancer ( Zhang et al., 2019 Zhang et al., 2019 ). Coincidentally, thapsigargin (TG) was widely used as an irreversible inhibitor of the ER Ca 2+ ATPase ( Lei et al., 2015 Lei et al., 2015 ), which can synergize with many anti-cancer agents by triggering ER stress-related apoptosis in OvCa ( Seo et al., 2016 Seo et al., 2016 ; Kim and Ko, 2021 Kim and Ko, 2021 ). However, ATP2A3 in our risk model delivered a protective role for survival extension in accordance with the pro-apoptotic effect of ATP2A3 defined by Chemaly et al. (2018) Chemaly et al. (2018) . The seemingly debatable evidence might be attributed to the non-specific blocking effect of TG. Therefore, to further clarify the role of ATP2A3 in OvCa, more specific agents or genetic tools targeting ATP2A3 need to be applied. Among the seven genes in our risk signature, TAP1 is the most charming one that connects the immune profile with ER stress for its special role in antigen presentation. Closely related to the dysregulation of MHC-Ⅰ antigen molecules, TAP1 deficiency was frequently reported as a signature of tumor immune escape ( Sabapathy and Nam, 2008 Sabapathy and Nam, 2008 ; Chow et al., 2021 Chow et al., 2021 ). A growing body of evidence derived from clinical data firmly supports our findings that lower expression of TAP1 might correlate with poor prognosis in OvCa patients ( Millstein et al., 2020 Millstein et al., 2020 ). In addition to the immune-related perspective, the fact that TAP1 serves as a prognostic factor may be due to its mechanism of activation of ER stress according to Sabapathy and Nam (2008) Sabapathy and Nam (2008) . Specifically, a study by Bartoszewski et al. (2011) Bartoszewski et al. (2011) uncovered that unfolded protein response (UPR)-activated XBP1 was involved in the upregulation of microRNA-346, which further interfered in the expression of TAP1 by targeting a 6-mer canonical seeding site. Given the multiple characteristics of each gene, we analyzed the comprehensive effect of the risk signature to clarify the correlation with canonical ER stress pathways. Impressively, among the three cohorts, high-risk group showed a higher level of IRE1α/XBP1 and PERK arm activation, indicating a non-lethal role ER stress response that promotes cell adaptation to stress. By contrast, higher levels of ATF4 and CHOP were found in the low-risk group, representing an unresolved status of ER homeostasis ( Chen and Cubillos-Ruiz, 2021 Chen and Cubillos-Ruiz, 2021 ). Functional annotation further illustrated that the ER stress-related signature was closely associated with cellular response and senescence, Ca 2+ transport, domain binding disorder, and T cell activation. In line with the findings above, immune infiltration analysis also demonstrated differences in anti-tumor efficiency between the two groups. For the innate immunity cluster, macrophage polarization was highlighted in the results. Consistently, Soto-Pantoja et al. (2017) Soto-Pantoja et al. (2017) reported that tumoral IRE1α inhibition could enhance macrophage-mediated cancer cell clearance, indicating M1 polarization. Meanwhile, ICD induced by unresolved ER stress may account for the higher level of activated DCs in the low-risk group as well as the activation of adaptive immunity ( Kasikova et al., 2019 Kasikova et al., 2019 ). Surprisingly, the levels of immunosuppressive molecules such as programmed death-1 (PD-1) and cytotoxic T lymphocyte associated antigen-4 (CTLA4) were also raised in the low-risk group, suggesting an innovative approach to apply the immunotherapy in a certain population of OvCa. An eminent study unveiled that CD8 + tumor-infiltrating lymphocytes influenced the OvCa patients’ survival in a dose-response manner (Ovarian Tumor Tissue Analysis (OTTA) Consortium, 2017). Given the special role of TAP1 in pMHC-Ⅰ formation, the correlation between CD8 and TAP1 expression was analyzed ( Figs. 6 Figs. 6 e‍–‍6g), while further studies are required to clarify the subtle influence of ER stress on tumor-associated antigen processing. Struggling in an execrable TME, intratumoral immune cells are always confronted with various stress factors. Recent studies have ascertained that the activation of IRE1α/XBP1 arm in DCs and T cells could impair their anti-tumor functions in OvCa ( Cubillos-Ruiz et al., 2015 Cubillos-Ruiz et al., 2015 ; Song et al., 2018 Song et al., 2018 ), highlighting the prospect of targeting the ER stress-related pathway in intratumoral immune cells to enhance their anti-tumor capacity. 4 Conclusions 1 In summary, our work identified an ER stress-related risk signature, providing a novel annotation for OvCa prognosis prediction. The robustness of this signature was demonstrated by double validations. 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Mol Ther Oncolytics , 20 : 545 - 555 . https://doi.org/10.1016/j.omto.2021.02.012 https://doi.org/10.1016/j.omto.2021.02.012 A polygenic methylation prediction model associated with response to chemotherapy in epithelial ovarian cancer Zundell JA , Fukumoto T , Lin JH , et al. , 2021 . Targeting the IRE1α/XBP1 endoplasmic reticulum stress response pathway in ARID1A -mutant ovarian cancers . Cancer Res , 81 ( 20 ): 5325 - 5335 . https://doi.org/10.1158/0008-5472.CAN-21-1545 https://doi.org/10.1158/0008-5472.CAN-21-1545 Targeting the IRE1α/XBP1 endoplasmic reticulum stress response pathway in ARID1A-mutant ovarian cancers Jiahang MO and Hua JIANG were responsible for the research design and conceptualization. Jiahang MO, Shunyi RUAN, and Baicai YANG collected the data. Shunyi RUAN and Yunfeng JIN performed the computational analyses. Jiahang MO and Baicai YANG drafted the manuscript. Yunfeng JIN and Xukai LUO revised the manuscript. Keyi LIU was consulted for molecular pathology of ovarian cancer. Hua JIANG supervised and supported this research. All authors have read and approved the final manuscript, and therefore, have full access to all the data in the study and take responsibility for the integrity and security of the data. This work was supported by the Shanghai Shenkang Hospital Development Center’s Shenkang Promotion of Clinical Skills and Clinical Innovation in Municipal Hospitals Three-Year Action Plan (No. 2020‒2023), the Major Clinical Research Project (No. SHDC2020CR1048B), and the Pilot Construction Project of High-Level Universities in Shanghai (No. DGF501017-06), China. 10.1631/jzus.B2200272 1673-1581（2023）01-0064-14 莫佳航,阮顺毅,杨柏财等.基于内质网应激相关基因构建新型风险模型用于卵巢癌预后及免疫浸润状态的预测[J].浙江大学学报（英文版）（B辑：生物医学和生物技术）,2023,24(01):64-77. 莫佳航,阮顺毅,杨柏财等.基于内质网应激相关基因构建新型风险模型用于卵巢癌预后及免疫浸润状态的预测[J].浙江大学学报（英文版）（B辑：生物医学和生物技术）,2023,24(01):64-77. This work was supported by the Shanghai Shenkang Hospital Development Center’s Shenkang Promotion of Clinical Skills and Clinical Innovation in Municipal Hospitals Three-Year Action Plan (No. 2020‒2023), the Major Clinical Research Project (No. SHDC2020CR1048B), and the Pilot Construction Project of High-Level Universities in Shanghai (No. DGF501017-06), China. 2022-05-09 2022-08-30 2023-01-15 2023-02-06 2023-01-11 Copyright © Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2022 2023 浙江大学出版社 Jiahang MO, Shunyi RUAN, Baicai YANG, Yunfeng JIN, Keyi LIU, Xukai LUO, and Hua JIANG declare that they have no conflict of interest. This article does not contain any studies with human or animal subjects performed by any of the authors. Compliance with ethics guidelines Supplementary information 1 Materials and methods; Tables S1 and S2; Figs. S1‒S3 浙江大学学报（英文版）（B辑：生物医学和生物技术） 1 24