Edited by Xiao-Fan WangAutophagy is typically a prosurvival cellular process that promotes the turnover of long-lived proteins and damaged organelles, but it can also induce cell death. We have previously reported that the small molecule Z36 induces autophagy along with autophagic cell death in HeLa cells. In this study, we analyzed differential gene expression in Z36-treated HeLa cells and found that Z36-induced endoplasmic reticulum-specific autophagy (ER-phagy) results in ER stress and the unfolded protein response (UPR). This result is in contrast to the common notion that autophagy is generally activated in response to ER stress and the UPR. We demonstrate that Z36 up-regulates the expression levels of FAM134B, LC3, and Atg9, which together mediate excessive ER-phagy, characterized by forming increased numbers of autophagosomes with larger sizes. We noted that the excessive ER-phagy accelerates ER degradation and impairs ER homeostasis and thereby triggers ER stress and the UPR as well as ER-phagy-dependent cell death. Interestingly, overexpression of FAM134B alone in HeLa cells is sufficient to impair ER homeostasis and cause ER stress and cell death. These findings suggest a mechanism involving FAM134B activity for ER-phagy to promote cell death.Autophagy is a highly conserved physiological process, playing important roles in development, differentiation, immune defense, suppression of tumorigenesis and the prevention of neuronal degeneration in multicellular organisms (1-5). It is characterized by the formation of double-membrane autophagosomes, which then fuse with lysosomes for the degradation of components inside. During starvation, autophagy is initiated nonselectively to degrade substrates and thus provide nutrients and energy for survival. Meanwhile, autophagy can function selectively to remove damaged organelles or aggregated proteins, as a quality control mechanism (6). A growing number of subcellular components are found to be cleared by selective autophagy; each is named after its specific target, such as mitochondria (mitophagy) (7), aggregated proteins (aggrephagy) This work was supported by Ministry of Science and Technology of ChinaGrants 2016YFA0501200 and 2012CB910703 (to B. X.) and National Natural Science Foundation of China Grant 91013011 (to B. X.). The authors declare that they have no conflicts of interest with the contents of this article. This article contains Figs. S1-S5 and Sheets S1-S4. The RNA-Seq data have been deposited in NCBI Gene Expression Omnibus (GEO) under the accession number GSE130006.

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Objectives: Bladder cancer is the fourth most common malignancy in men in the United States. Aberrant alternative splicing (AS) events are involved in the carcinogenesis, but the association between AS and bladder cancer remains unclear. This study aimed to construct an AS-based prognostic signature and elucidate the role of the tumor immune microenvironment (TIME) and the response to immunotherapy and chemotherapy in bladder cancer. Methods: Univariate Cox regression analysis was performed to detect prognosis-related AS events. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses were employed to build prognostic signatures. Kaplan–Meier survival analysis, multivariate Cox regression analysis, and receiver operating characteristic (ROC) curves were conducted to validate the prognostic signatures. Then, the Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and tumor immune estimation resource (TIMER) databases were searched and the single-sample gene set enrichment analysis (ssGSEA) algorithm and CIBERSORT method were performed to uncover the context of TIME in bladder cancer. The Tumor Immune Dysfunction and Exclusion (TIDE) web tool and pRRophetic algorithm were used to predict the response to immunotherapy and chemotherapy. Finally, we constructed a correlation network between splicing factors (SFs) and survival-related AS events. Results: A total of 4684 AS events were significantly associated with overall survival in patients with bladder cancer. Eight prognostic signatures of bladder cancer were established, and a clinical survival prediction model was built. In addition, the consolidated prognostic signature was closely related to immune infiltration and the response to immunotherapy and chemotherapy. Furthermore, the correlation identified EIF3A, DDX21, SDE2, TNPO1, and RNF40 as hub SFs, and function analysis found ubiquitin-mediated proteolysis is correlated most significantly with survival-associated AS events. Conclusion: Our findings highlight the prognostic value of AS for patients with bladder cancer and reveal pivotal players of AS events in the context of TIME and the response to immunotherapy and chemotherapy, which may be important for patient management and treatment.