Regulation of autophagic response by CNOT11 via IL-6/JAK/STAT signaling

Regulation of autophagic response by CNOT11 via IL-6/JAK/STAT signaling | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Regulation of autophagic response by CNOT11 via IL-6/JAK/STAT signaling Saori Nishijima, Toru Suzuki, Tadashi Yamamoto This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7416154/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract While the CCR4-NOT complex is a key player of deadenylation-mediated mRNA degradation, the roles of its component CNOT11 remain elusive. Recent clinical studies have shown that CNOT11 is highly expressed in certain cancer types, and the elevated expression is associated with poor survival in cancer patients. In this study, we investigate the role of CNOT11 in cell viability, proliferation and mRNA degradation in tumor cells. Suppression of CNOT11 in HeLa cells leads to decreased expression of CCR4-NOT subunits and induces autophagy through the AMPK/ULK1 pathway. Transcriptomic and biochemical analyses reveal an activation of the JAK-STAT signaling pathway in CNOT11-knockdown (CNOT11-KD) cells, accompanied by increased IL-6 expression that contributes to autophagy. The increase of IL-6 is caused by an enhanced transcription rather than impaired deadenylation. We also find that proliferation of HeLa cells is significantly retarded, and cells are more sensitive to adriamycin treatment upon CNOT11-KD. These findings suggest that CNOT11 modulates cancer cell viability through regulation of cytokine production at the transcriptional level, implicating CNOT11 as a potential pharmacological target against cancer. Biological sciences/Cancer Biological sciences/Cell biology Biological sciences/Molecular biology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Regulation of gene expression is crucial for cellular function, maintenance of homeostasis, and adaptation to environmental changes. mRNA abundance is regulated at both the transcriptional level by transcription factors and the post-transcriptional level by RNA-binding proteins and non-coding RNAs. In recent years, the importance of regulation of mRNA stability and translational efficiency in gene expression has been increasingly recognized, with particular attention to mRNA degradation pathways as one of the major regulatory mechanisms. A typical mRNA degradation pathway begins with the shortening of poly(A) tails, a process called deadenylation, which serves as a key determinant of mRNA expression levels. [ 1 ] The carbon catabolite repressor 4-negative on TATA-less (CCR4-NOT) complex is a multi-subunit protein complex that is central to mRNA deadenylation. [ 2 ] This complex is evolutionarily conserved from yeast to humans, and eight subunits have been identified as components of the complex in mammal. The large scaffold protein CNOT1 plays a crucial role in tethering the other subunits together. [ 3 , 4 ] CNOT6/6L/7/8 possess deadenylase activity, while CNOT2 and CNOT3 contribute to the stabilization of the complex as regulatory subunits. [ 5 – 8 ] CNOT9 is involved in microRNA/small interfering RNA (siRNA)-mediated mRNA degradation through the RNA-induced silencing complex (RISC) and also functions as a cofactor in transcriptional regulation. [ 9 , 10 ] CNOT10 enhances the deadenylase activity of the complex. [ 11 ] When the CCR4-NOT complex loses its function, mRNA expression patterns are largely abrogated, leading to cell death via apoptosis or necroptosis, and resulting in abnormal development and differentiation at the organismal level. CNOT11 (also known as C2ORF29) was specifically identified in vertebrates as a component of the CCR4-NOT complex due to its association with CNOT10. [ 12 ] Since its discovery is relatively recent, CNOT11 has a shorter research history than the other subunits, delaying detailed functional analyses. Earlier study showed that CNOT11 depletion did not significantly alter deadenylation kinetics in a β-globin reporter assay. [ 12 ] On the other hand, structural analyses have shown that the CNOT1–CNOT10–CNOT11 submodule serves as a scaffold for protein–protein interactions. 13 The antenna domain of CNOT11 binds to the tumor suppressor GGNBP2 (gametogenetin-binding protein 2) and regulates mRNA deadenylation. [ 13 , 14 ] Furthermore, CNOT11 is involved in translation-dependent tubulin mRNA degradation during tubulin autoregulation. [ 15 ] Therefore, CNOT11 contributes to mRNA turnover in several biological aspects. Clinical studies have reported that CNOT11 is significantly upregulated in multiple malignancies, most notably hepatocellular carcinoma and renal cell carcinoma, where its overexpression has been linked to enhanced tumor cell proliferation, invasion, and decreased overall survival in cancer patients. [ 16 ] Moreover, elevated CNOT11 levels often correlate with advanced tumor stage and metastasis, suggesting a direct role in driving oncogenic phenotypes. [ 16 ] Other CCR4-NOT subunits likewise are relevant to cancer development: CNOT2 overexpression promotes cell cycle progression and suppresses apoptotic pathways, correlating with increased proliferation, lymph node metastasis, and poor prognosis in both breast and lung cancers. [ 17 , 18 ] CNOT3 functions as a critical cofactor for leukemic stem cell maintenance and facilitates malignant transformation through transcriptional dysregulation in leukemia. [ 19 ] Deadenylase activity of CNOT7 stabilizes key oncogenic transcripts such as those encoding growth and survival factors, thereby supporting glioblastoma and colorectal cancer progression. [ 20 , 21 ] These data suggest that both enzymatic and non-enzymatic subunits of the CCR4-NOT complex contribute to oncogenic processes by altering mRNA expression. In this study, we investigate the role of CNOT11 in cell survival, proliferation, and mRNA degradation, and propose its potential involvement in cancer progression within the broader functional context of the CCR4-NOT complex. Results CNOT11-KD results in a decrease of CCR4-NOT subunits To investigate biological and biochemical roles of CNOT11, we suppressed CNOT11 expression by introducing siRNA targeting CNOT11 in HeLa cells. We first examined the effects of CNOT11-KD on the expression of other CCR4-NOT complex subunits and on the integrity of complex itself. Immunoblot analysis showed that expression of CNOT6, 6L, 7, 8, 10 was decreased upon CNOT11-KD (Fig. 1A). Consistently, immunoblot analysis following immunoprecipitation with a CNOT3 antibody revealed that CNOT6, 8, 10 within the CCR4-NOT complex were markedly reduced in CNOT11-KD cells compared to control cells that were transfected with scramble siRNA (Fig. 1A). Quantitative PCR (qPCR) analyses demonstrated that mRNA levels of CNOT1, CNOT6, and CNOT8 were significantly lower in CNOT11-KD cells (Fig. 1B). These results suggest that CNOT11-KD leads to a decrease of several complex subunits, consequently influencing the function of the CCR4-NOT complex. CNOT11-KD induces autophagy An accumulation of small vesicles was detected in the cytoplasm of HeLa cells upon CNOT11-KD (Fig. 2A). Similar results were obtained in A549 (lung cancer) and HT29 (colon cancer) cell lines. These cytoplasmic vesicles were stained with a dye that recognizes autophagosome, suggesting that CNOT11-KD cells undergo autophagy (Fig. 2B). Consistently, levels of LC3-II, a marker of autophagy, were increased in CNOT11-KD cells compared to control cells (Fig. 2C). An increase of LC3-II alone does not necessarily indicate autophagy induction, as it may reflect either enhanced autophagosome formation or impaired degradation of autophagosomes following lysosomal fusion. To distinguish between these possibilities, we performed an autophagic flux assay. When CNOT11-KD cells were treated with lysosomal protease inhibitors such as bafilomycin A1, chloroquine, or concanamycin A which block autophagosome degradation in lysosomes, LC3-II levels were further increased (Fig. 2D). Moreover, microscopic observation showed that both the number and size of vehicles in CNOT11-KD cells were further increased following chloroquine treatment (Fig. 2E). Collectively, these findings indicate that HeLa cells undergo autophagy upon CNOT11-KD. Autophagy is induced via AMPK/ULK1 activation in CNO11-KD cells In general, autophagy is initiated by the activation of the Unc-51 like kinase 1 (ULK1) complex, which is regulated by mTOR and/or AMPK depending on the cellular nutritional and energy status. [22] Under nutrient-rich conditions, mTORC1 binds to ULK1 and phosphorylates it at Ser757, thereby preventing ULK1 from interacting with AMPK and blocking autophagy initiation. Conversely, upon nutrient starvation, AMPK is activated and phosphorylates ULK1 at Ser555 for activation. Activated ULK1 forms a complex with dephosphorylated autophagy-related 13 (ATG13) and the focal adhesion kinase family interacting protein of 200 kD (FIP200), leading to autophagy. [23] We then examined the contribution of AMPK, ULK1 and ATG13 to autophagy in CNOT11-KD cells. Immunoblot analyses showed that phosphorylated forms of AMPKa and ULK1 at Ser555 were increased, whereas phosphorylated forms of ATG13 and ULK1 at Ser757 were decreased (Fig. 3A). The increase of LC3-II in CNOT11-KD cells was attenuated upon simultaneous suppression of ULK1 concomitant with modest decrease of AMPKa phosphorylation (Fig. 3B). ULK1 suppression reduced ATG13 expression, also contributing to the decrease of LC3-II in CNOT11-KD cells (Fig. 3B). To further confirm that CNOT11-KD induces autophagy, we re-introduced CNOT11 in CNOT11-KD cells. In these cells, the CNOT11 sequence is modified at the nucleotide level without altering the amino acid sequence so that it becomes resistant to targeting by CNOT11 siRNA. When siRNA-resistant CNOT11 is exogenously expressed via retrovirus-mediated gene transfer, an increase of LC3-II expression was not observed even after CNOT11 siRNA introduction (Fig. 3C). In cells infected with control retrovirus, CNOT11-KD led to an increase of LC3-II. These results suggest that the AMPK/ULK1 pathway contributes to LC3-II accumulation in CNOT11-KD cells, indicating a potential involvement of CNOT11 in the autophagy-related processes. The JAK/STAT pathway is involved in Autophagy in CNOT11-KD cells To understand the molecular basis of the autophagy induction upon CNOT11-KD, we performed RNA-seq analysis. The results showed that 142 and 151 genes were significantly upregulated and downregulated upon CNOT11-KD, respectively (Fig. 4A). Gene set enrichment analysis of the differentially expressed genes showed that the JAK-STAT signaling pathway was the most significantly enriched among the upregulated genes (Fig. 4B). The JAK-STAT pathway is a critical intracellular signaling cascade that primarily transduces signals from cytokines and growth factors, playing essential roles in immune responses, cell proliferation, and inflammation. Interleukin-6 (IL-6) is a representative cytokine known to activate the JAK-STAT pathway, particularly STAT3 24 . Indeed, the results of RNA-seq revealed that IL-6 expression was upregulated 1.9-fold in CNOT11-KD cells (Fig. 4A), leading us to investigate the relationship between the IL-6/JAK/STAT pathway and autophagy upon CNOT11-KD. We confirmed a significant increase in IL-6 mRNA in CNOT11-KD cells compared with control cells by performing qPCR analysis (Fig.4C). Immunoblot analyses also showed that CNOT11-KD led to an increase in IL-6 protein together with an increase of LC3-II (Fig. 4D). Furthermore, the JAK/STAT pathway is activated in CNOT11-KD cells as indicated by an increase of phosphorylated STAT1 and 3 (Fig. 4D). Importantly, the simultaneous KD of CNOT11 and IL-6 or a treatment of CNOT11-KD cells with the STAT3 inhibitor S31-201 reduced the increase of LC3-II (Fig. 4D and 4E). These data suggest that the LC3-II increase upon CNOT11-KD is mediated, at least in part, through IL-6-dependent activation of the JAK-STAT pathway. Increased IL-6 in CNOT11-KD cells is not caused by mRNA stabilization We next investigated whether the increase of IL-6 mRNA was due to impaired deadenylase activity of the CCR4-NOT complex lacking CNOT11. First, we found that the level of premature unspliced IL-6 mRNA significantly increased in CNOT11-KD cells (Fig.5A). Next, we compared the stability of IL-6 mRNA by measuring its half-life between control and CNOT11-KD cells, but there was no significant difference in the stability of IL-6 mRNA between them (Fig.5B). Furthermore, the polyA tail length of IL-6 mRNA was comparable between control and CNOT11-KD cells (Fig.5C). Therefore, the increased IL-6 mRNA in CNOT11-KD cells is likely due to enhanced transcription rather than due to impaired deadenylase activity. CNOT11-KD reduces HeLa cell proliferation and enhances Adriamycin sensitivity Autophagy and the cell cycle are closely interconnected, and activation of autophagy is known to influence cell cycle progression as well as cellular sensitivity to anticancer therapies. Therefore, we investigated cell proliferation, cell cycle progression, and chemotherapeutic response in CNOT11-KD HeLa cells. Live-cell imaging analysis using the IncuCyte system revealed that CNOT11-KD cells exhibited significantly slower proliferation compared to control cells (Fig. 6A).Flow cytometry analysis demonstrated a decrease in the proportion of cells in the G1 phase and an increase in that in the S and G2/M phases relative to controls (Fig. 6B), suggesting that autophagy induced by CNOT11-KD may alter cell cycle progression, particularly during the S phase. To explore whether CNOT11-KD influences the response to chemotherapy, we compared the effects of Adriamycin (doxorubicin), a DNA-damaging agent, on cell viability between control and CNOT11-KD HeLa cells. While low concentrations of Adriamycin had minimal impact on cell viability in control cells, high concentrations resulted in the appearance of floating cells (Fig. 6C). Under the CNOT11-KD condition, floating cells were observed even after low-dose Adriamycin treatment, and the number of floating cells further increased at higher-dose Adriamycin treatment (Fig. 6C). Immunoblot analysis revealed that Adriamycin treatment induced only a modest increase in cleaved PARP in control cells, whereas a more pronounced increase in cleaved PARP was observed in CNOT11-KD cells (Fig. 6D). These findings indicate that suppression of CNOT11 not only slows proliferation by altering cell cycle progression but also renders HeLa cells more sensitive to Adriamycin-induced cytotoxicity. Discussion In this study, we identified CNOT11 as a critical regulatory component of the CCR4-NOT complex that influences cellular responses such as autophagy, proliferation and sensitivity to anti-cancer drug. CNOT11-KD led to reduced expression of several complex subunits, indicating insufficient function of the complex. The increase of IL-6 mRNA is one of the major characteristics in CNOT11-KD cells but is not caused by an impaired mRNA deadenylation. Therefore, the structural disruption of the complex upon CNOT11-KD compromises broader transcriptional and post-transcriptional regulatory mechanisms. [ 11 ] A key finding of our study is that the loss of CNOT11 promotes autophagy through both the AMPK–ULK1 and IL-6/JAK/STAT3 signaling pathways. IL-6–mediated autophagy has been reported in various cancer types, highlighting the broad role of cytokine signaling in metabolic regulation. Cathepsin L (CTSL) activates the IL-6/JAK/STAT3 signaling and induces autophagy in laryngeal carcinoma, thereby contributing to tumor metastasis. [ 25 ] Increasing evidence points to a functional interaction between the JAK/STAT and AMPK/ULK1 pathways. Notably, STAT3 directly binds to the promoter of LKB1 (STK11), a master upstream kinase that phosphorylates and activates AMPK under energy stress conditions. [ 26 ] Once activated, AMPK phosphorylates ULK1 at Ser555 and other residues, initiating autophagy. [ 27 ] Conversely, ULK1 can phosphorylate STAT3, enhancing its transcriptional activity and establishing a feed-forward loop between autophagy induction and cytokine signaling. [ 28 ] While the IL-6/STAT3 signaling is known to promote metabolic adaptation in breast cancer cells, direct evidence connecting IL-6–induced STAT3 phosphorylation to AMPKα1 and ULK1 activation remains limited. [ 27 ] Nevertheless, our findings support the existence of the crosstalk between the JAK/STAT and AMPK/ULK1 pathways in the context of autophagy induced by CNOT11-KD. By linking CCR4–NOT complex dysfunction to autophagy-regulatory pathways, this study provides new insights into how RNA regulatory mechanisms integrate with metabolic stress responses to support cancer cell survival and progression. The increase of IL-6 mRNA observed in CNOT11-KD cells was not due to enhanced mRNA stabilization. This raises the possibility that transcriptional regulation may be involved. Several lines of evidence suggest that the mammalian CCR4–NOT complex plays a direct role in transcriptional control. For example, CNOT1 recruits the histone acetyltransferase p300 to specific promoters, promoting H3K27 acetylation and activation of stress-responsive genes. [ 30 ] Similarly, CNOT3 interacts with the SWI/SNF chromatin remodeling complex to regulate cytokine gene accessibility in macrophages. [ 31 ] In mouse embryonic stem cells, the complex is localized in the nucleus and associates with promoter regions of self-renewal genes, [ 32 ] while also regulating transcriptional elongation and lineage-specific transcription in B cell development via interactions with transcription factors and nuclear receptors. [ 33 , 34 ] These findings collectively suggest that CNOT11, as a component of the CCR4–NOT complex, may also participate in transcriptional regulation of IL-6, possibly through interaction with nuclear transcription factors or chromatin modifiers. Supporting this idea, recent studies have identified GGNBP2 as a tumor suppressor in triple-negative breast cancer (TNBC), which acts as a negative regulator of the IL-6/STAT3 signaling. Overexpression of GGNBP2 in TNBC cells reduces proliferation, migration, invasion, and stem cell–like properties, accompanied by attenuated IL-6/STAT3 signaling. [ 35 ] This is particularly relevant to our findings, where CNOT11 knockdown results in increased IL-6 expression and enhanced STAT3 activation, leading to autophagy. Taken together, the suppressive effect of GGNBP2 on IL-6/STAT3 signaling and our own results suggest that loss of CNOT11 may relieve transcriptional repression or enhance activation of cytokine pathways, consequently inducing autophagy. CNOT11-KD in HeLa cells altered cell-cycle distribution, characterized by a reduced G1-phase and increased S- and G2/M-phase populations. While the shortening of the G1 phase and accumulation in the S phase are generally associated with accelerated proliferation, proliferation of CNOT11-KD HeLa cells was suppressed. Several studies have shown that replication stress and checkpoint activation can lead to similar phenotypes, particularly in p53-deficient cells such as HeLa cells. Under conditions of replication fork stalling, activation of the ATR–CHK1 pathway slows progression from S phase to M phase, resulting in a decreased G1 pool and increased S- and G2/M-phase populations. [ 36 ] In U2OS cells, which lack a functional G1/S checkpoint, forced S-phase entry under stress similarly induces ATR/CHK1-mediated surveillance, transiently increasing the proportions of cells in the S and G2/M phases. [ 37 ] Moreover, in p53-deficient cells, the G2/M checkpoint serves as the primary barrier to mitotic entry following replication perturbations. [ 38 ] Whether such checkpoint machinery is activated in CNOT11-KD cells remains an important question for future investigation. CNOT11-KD sensitized cells to Adriamycin, a DNA-damaging chemotherapeutic agent. While autophagy functions as a cytoprotective response particularly under nutrient-starved conditions, excessive or uncontrolled autophagy can lead to cell death, as seen in Bax/Bak–null cells. [ 39 ] Under CNOT11-KD conditions, we observed a greater number of floating cells following low-dose Adriamycin treatment, accompanied by enhanced PARP cleavage. Several anticancer agents, such as obatoclax, gossypol, resveratrol, and betulinic acid, are known to induce autophagic cell death in liver, prostate, colon, and pancreatic cancers. [ 40 – 43 ] Collectively, our findings position CNOT11 as a regulatory node linking CCR4–NOT complex integrity, cytokine signaling, autophagy, and cell viability. Suppression of CNOT11 in cancer cells initiates a cascade of transcriptional activation that leads to autophagy, cell cycle arrest, and enhanced sensitivity to anticancer drugs, suggesting a novel approach for cancer chemotherapy. Materials and Methods Cells and Reagents HeLa (RCB0007) was obtained from the RIKEN BioResource Research Center (RIKEN BRC, Tsukuba, Japan), and HT29 (JCRB0019) and A549 (JCRB0076) cells were purchased from the JCRB Cell Bank (Japanese Collection of Research Bioresources, Osaka, Japan). Adriamycin (doxorubicin) was purchased from Funakoshi Co., Ldt (Tokyo, Japan). Bafilomycin A1 and STAT3 inhibitor (S3I-201) were from Sigma-Aldrich (St. Louis, MO, USA). Chloroquine and concanamycin A were from Tocris Bioscience (Bristol, UK). Antibodies Antibodies against CNOT1, CNOT2, CNOT3, CNOT6, CNOT6L, CNOT8, CNOT9, and CNOT10 were used as previously described. [40] The antibody against CNOT11 (HPA069823) was from Atlas Antibodies AB (Bromma, Sweden). Antibodies against GAPDH (#2118), AMPKα (#2603), phospho-AMPKα (Thr172; #2535), mTOR (#2983), phospho-mTOR (Ser2448; #2974), ULK1 (#8054), phospho-ULK1 (Ser555; #5869), Atg13 (#13273), phospho-Atg13 (Ser318; #46329), IL-6 (#12153), STAT1 (#9172), phospho-STAT1 (Tyr701; #7649), STAT3 (#4904), phospho-STAT3 (Tyr705; #9145), and cleaved PARP (#9541) were obtained from Cell Signaling Technology (Danvers, MA, USA). The antibody against LC3 (PM036) was from MBL International (Woburn, MA, USA), and α-Tubulin (T9026) was from Sigma-Aldrich. Cell culture and siRNA transfection HeLa, A549, and HT29 cells were cultured in Dulbecco's Modified Eagle’s Medium (DMEM; Fujifilm Wako, Osaka, Japan) supplemented with 10% fetal bovine serum (FBS; Nichirei Corporation, Tokyo, Japan) and 100 U/mL penicillin–streptomycin (Thermo Fisher Scientific, Waltham, MA, USA) at 37°C in a humidified atmosphere containing 5% CO₂. For siRNA-mediated knockdown, 100 pmol of double-stranded siRNA was transfected into 5 × 10⁵ cells using Lipofectamine RNAiMAX (Thermo Fisher Scientific) according to the manufacturer’s instructions. The siRNA sequences used were as follows: scramble, 5′-UUCUCCGAACGUGUCACGUTT-3′ and 5′-ACGUGACACGUUCGGAGAATT-3′; CNOT11, 5′-CCGAACGCCAAUCUGAAUUGC-3′ and 5′-AAUUCAGAUUGGCGUUCGGCC-3′; ULK1, 5’-GCACAGAGACCGUGGGCAATT-3’ and 5’-UUGCCCACGGUCUCUGUGCTT. For IL-6 knockdown, Silencer™ Pre-Designed siRNA targeting human IL6 (ID: 144576; Cat# AM16708; Thermo Fisher Scientific) was used. Cells were analyzed 72 hours after transfection. Autophagy detection and autophagy flux assay Autophagy and autophagic flux were assessed in HeLa cells 72 hours after siRNA transfection. For detection of autophagic vacuoles, cells were incubated with CYTO-ID® Green Detection Reagent (1:1000 dilution; Enzo Life Sciences, Farmingdale, NY, USA) for 30 minutes at 37 °C in the dark. Nuclei were counterstained with Hoechst 33342, and cells were washed twice with the provided assay buffer. Fluorescence images were acquired using a laser scanning confocal microscope (TCS SPE; Leica Microsystems, Wetzlar, Germany). For autophagic flux, cells were treated with lysosomal inhibitors; bafilomycin A1 (5 nM), chloroquine (50 nM), and concanamycin A (5 nM) during the final 4 hours. After treatment, one set of cells was subjected to immunoblotting to analyze LC3-II protein levels, and another set was examined by phase-contrast microscopy. Immunoprecipitation and immunoblot Cells were washed with PBS and lysed in TNE buffer (50 mM Tris-HCl [pH 7.5], 150 mM NaCl, 1 mM EDTA, 1 mM phenylmethylsulfonyl fluoride, 10 mM NaF, 10 mM β-glycerophosphate, and 1% Nonidet P-40). Cell lysates were immunoprecipitated using 1 µg of mouse monoclonal anti-CNOT3 antibody, incubated overnight at 4 °C with rotation in the presence of Dynabeads Protein G (Thermo Fisher Scientific). Immunoprecipitates or equal amounts of total protein were resolved by SDS-PAGE and transferred to Immobilon-P membranes (Merck Millipore). Membranes were blocked with 3% skim milk in Tris-buffered saline containing 0.05% Tween 20 (TBST) for 1 hour at room temperature, and then incubated overnight at 4 °C with primary antibodies in Can Get Signal® Immunoreaction Enhancer Solution (TOYOBO, Osaka, Japan). After three washes with TBST, membranes were incubated with HRP-conjugated secondary antibodies for 1 hour at room temperature, followed by three additional washes with TBST. Detection was performed using Immobilon Western Chemiluminescent HRP Substrate (Merck Millipore), and chemiluminescent signals were visualized using an Amersham Imager 680 (GE Healthcare). Virus infection Retroviruses were produced by transfecting Plat-E packaging cells with 2 µg of pMXs-puro vectors encoding CNOT11 cDNA using TransIT-LT1 transfection reagent (Mirus Bio LLC). Forty-eight hours later, supernatants were filtered, supplemented with polybrene (5 µg/mL), and used to infect ecotropic receptor–expressing HeLa cells. Cells were seeded at 8.5 × 10⁵ cells per 10-cm dish one day prior to infection. Two days after retroviral infection, cells were trypsinized, diluted, and cultured in the presence of puromycin (1 µg/mL) for an additional 3 days to select infected cell populations. Reverse transcriptase PCR assays and mRNA half-life measurement Total RNA was extracted using Isogen reagent (Nippon Gene Co., Ltd., Toyama, Japan). Complementary DNA (cDNA) was synthesized from 0.5–1 µg of total RNA using PrimeScript II reverse transcriptase (Takara Bio Inc., Shiga, Japan). Quantitative reverse transcription PCR (qRT-PCR) was performed using a QuantStudio™ 5 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) and FastStart Universal SYBR Green Master Mix (Takara Bio Inc.). GAPDH expression was used as an internal control for normalization. For mRNA stability, cells were treated with actinomycin D (2.5 µg/mL; Sigma-Aldrich) 3 days after siRNA transfection, and RNA was collected at 0, 30, and 60 min following the addition of actinomycin D. Poly(A) tail assay Poly(A) tail lengths of mRNAs were analyzed using the Poly(A) Tail-Length Assay Kit (Thermo Fisher Scientific,) with minor modifications. Total RNA (1 µg) was incubated with poly(A) polymerase in the presence of guanosine (G) and inosine (I) to add a GI tail. Complementary DNA (cDNA) was synthesized from GI-tailed RNA using a PCR poly(A) test (PAT) universal primer and reverse transcriptase. PCR amplification was performed using gene-specific primers, the PAT universal primer, and HotStart-IT® Taq DNA Polymerase (Affymetrix, Santa Clara, CA, USA). RNA sequencing RNA sequencing (RNA-seq) was performed on total RNA from HeLa cells by the DNA Sequencing Section at the Okinawa Institute of Science and Technology Graduate University (OIST). One hundred nanograms of total RNA were used for library preparation with the TruSeq Stranded mRNA Library Prep Kit for NeoPrep (Cat# NP-202-1001; Illumina Inc., San Diego, CA, USA), which enables poly(A) selection using oligo(dT) beads, following the manufacturer’s instructions. Paired-end RNA-seq (150 bp × 2) was conducted using the HiSeq 3000/4000 PE Cluster Kit (Cat# PE-410-1001; Illumina Inc.) in accordance with the manufacturer's protocol. RNA-seq analysis Paired-end RNA-seq reads were mapped using Strand NGS software (Strand Life Sciences, Bangalore, India). Transcript abundance was quantified as fragments per kilobase of transcript per million mapped reads (FPKM). Gene expression values were normalized to Gapdh FPKM, and fold changes between knockdown and control conditions were calculated. Differentially expressed genes (DEGs) and pathway enrichment analyses were conducted using iDEP.96 (http://bioinformatics.sdstate.edu/idep96/). Gene Ontology (GO) enrichment analysis was also performed using DAVID Bioinformatics Resources 6.8 (https://david.ncifcrf.gov). The raw and processed RNA-seq data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE306607. STAT3 inhibition assay STAT3 signaling was inhibited with S3I-201 (100 µM; Selleck Chemicals, Houston, TX, USA) for 6 hours prior to harvesting. For siRNA co-transfection experiments, CNOT11 and IL-6 siRNAs were simultaneously introduced using Lipofectamine RNAiMAX. LC3-II protein levels were analyzed by immunoblotting as described above. Cell proliferation assay using live-cell imaging Proliferation of HeLa cells was monitored using the IncuCyte® S3 Live-Cell Analysis System (Sartorius AG, Göttingen, Germany) according to the manufacturer’s instructions. Phase-contrast images were acquired every 4 hours over a 96 hour period. Cell confluence was automatically quantified using the IncuCyte software to generate growth curves. Flow cytometric analysis HeLa cells were harvested 72 hrs after siRNA transfection and resuspended in PI solution containing 1 mL PBS, 50 μL PI (1 mg/mL; Invitrogen), 10 μL RNase A (10 mg/mL; Sigma-Aldrich), and 10 μL FBS. Cell cycle distribution was analyzed using a FACSAria™ III flow cytometer (BD Biosciences, Franklin Lakes, NJ, USA), and data were processed using FlowJo™ software version 10.10 (BD Biosciences). Statistical analysis Differences between groups were examined for statistical significance using Student’s t-test (one-tailed distribution with two-sample equal variance). We considered a p-value of <0.05 statistically significant. Declarations Acknowledgements We thank Okinawa Institute of Science and Technology Graduate University for generous support to the Cell Signal Unit. Data Availability All data generated or analyzed during this study are included in this published article and its supplementary information files. Authors contributions S.N. T.S. and T.Y. designed the study. S.N. performed the experiments. S.N. and T. S. wrote the manuscript, and All authors reviewed and approved the manuscript. Competing Interests The authors declare no competing interests. References Mugridge JS, Coller J, Gross JD. Structural and molecular mechanisms for the control of eukaryotic 5′–3′ mRNA decay. Nat Struct Mol Biol . 2018;25(11):1077–1085. Collart MA. Global control of gene expression in yeast by the Ccr4-Not complex. Gene . 2003;313:1–16. Ito K, Takahashi A, Morita M, Suzuki T, Yamamoto T. The role of the CNOT1 subunit of the CCR4-NOT complex in mRNA deadenylation and cell viability. Protein Cell . 2011;2(8):755–763. Shirai YT, Suzuki T, Morita M, Takahashi A, Yamamoto T. Multifunctional roles of the mammalian CCR4-NOT complex in physiological phenomena. 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Wei Y, Zou Z, Becker N, Anderson M, Sumpter R Jr, Xiao G, et al. EGFR-mediated tyrosine phosphorylation of Beclin 1 regulates autophagy and tumorigenesis. Cell. 2013;154(6):1269–1284. Kuba K, et al. CNOT3 interacts with the SWI/SNF complex to regulate chromatin accessibility at cytokine loci in macrophages. J Biol Chem . 2022;297(5):101235. Hu G, Kim J, Xu Q, Leng Y, Orkin SH, Elledge SJ. A genome-wide RNAi screen identifies a new transcriptional module required for self-renewal. Genes Dev . 2009;23(7):837–848. Winkler GS, Mulder KW, Bardwell VJ, Kalkhoven E, Timmers HT. Human Ccr4–Not complex is a positive regulator of transcription elongation. Mol Cell Biol . 2006;26(1):272–279. Yang CY, Ramamoorthy S, Boller S, Rosenbaum M, Rodriguez Gil A, Mittler G, et al. Interaction of the CCR4–NOT complex with EBF1 regulates gene-specific transcription and B cell development. EMBO J . 2016;35(13):1422–1436. Liu J, Liu L, Yagüe E, Yang Q, Pan T, Zhao H, et al. GGNBP2 suppresses triple-negative breast cancer aggressiveness through inhibition of IL‑6/STAT3 signaling activation. Breast Cancer Res Treat. 2019;174(1):65–78. Gorman MA, Man C, et al. ATR–Chk1 activation mitigates replication stress caused by mismatch repair–dependent processing of DNA damage. Proc Natl Acad Sci USA. 2018;115(7):1523–1528. Leung JW, Zhou S, et al. Chk1 dynamics in G2 phase upon replication stress predict daughter cell outcome. Dev Cell. 2022;57(6):638–653. Qiu Z, Oleinick NL, Zhang J. ATR/CHK1 inhibitors and cancer therapy. Radiother Oncol . 2018 Mar;126(3):450–464. Shimizu S, Kanaseki T, Mizukami T, et al. Role of Bcl-2 family proteins in a non-apoptotic programmed cell death dependent on autophagy genes. Nat Cell Biol. 2004;6(12):1221–1228. Nguyen M, Kobayashi KS, Goodell MA, et al. Obatoclax induces autophagy-dependent apoptosis in leukemia cells via Beclin-1 release. Blood. 2007;109(12):5075–5080. Bischoff P, Hu Y, et al. (−)-Gossypol triggers autophagic death in prostate cancer cells through Bcl-2 dissociation. Mol Cancer Ther. 2009;8(5):1236–1245. Liu B, Chen X, Zhang Y, et al. Resveratrol induces autophagy-mediated cell death in colorectal carcinoma via p38 MAPK. Autophagy. 2014;10(7):1172–1182. Fulda S, Jeremias I, Debatin KM. Betulinic acid triggers apoptosis and autophagy in melanoma cells. Cancer Res. 2002;62(10):3388–3394. Suzuki T, et al. Regulation of CCR4-NOT complex deadenylase activity and cellular responses by MK2-dependent phosphorylation of CNOT2. RNA Biol. 2022;19(1):234–246. Additional Declarations No competing interests reported. Supplementary Files supplementarymaterial.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7416154","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":511790216,"identity":"9cb2162a-74a8-40e4-9027-f0eb14ecbe02","order_by":0,"name":"Saori Nishijima","email":"","orcid":"","institution":"Okinawa Institute of Science and Technology Graduate University","correspondingAuthor":false,"prefix":"","firstName":"Saori","middleName":"","lastName":"Nishijima","suffix":""},{"id":511790217,"identity":"1007c9dc-bbb4-4fb9-b975-9b027f1cba25","order_by":1,"name":"Toru Suzuki","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Toru","middleName":"","lastName":"Suzuki","suffix":""},{"id":511790218,"identity":"9bf3228f-7897-4cbf-b9fc-1a57db698301","order_by":2,"name":"Tadashi Yamamoto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYHACAwbGBgkElx/IBVJsONXzoGkxYJBsAGo5QFgLkpUGB4DUATyusmc/vPHjzx0WDAbHTyd+ulHxR874eHPz5w8MfHk4beFJK5bmPSPBYHAmd7N0zhkDY7MzB9skgA4rxu2wHANpxjaglgO5G6Rz2wwSt91IbAP5JbEBlxb+N8Y/f4K0nH+7+TdIy+YZic0f8GqRyDGT4AVpuZG7DWzLBonEBgm8Wm48K7MGauGRvPF2m3XOGWNjCZBfzhjg9gt7f/Lmmz/b6uT4zuduvp1TISfH397++ENFxTGcIQa3TeEACt/gWAIhLQzyaE6vIaxlFIyCUTAKRgoAAPL9WxBJUaq3AAAAAElFTkSuQmCC","orcid":"","institution":"Okinawa Institute of Science and Technology Graduate University","correspondingAuthor":true,"prefix":"","firstName":"Tadashi","middleName":"","lastName":"Yamamoto","suffix":""}],"badges":[],"createdAt":"2025-08-20 10:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7416154/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7416154/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91078614,"identity":"f8f48383-b5b6-44f9-8511-a03bfe6ef020","added_by":"auto","created_at":"2025-09-11 11:20:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":111789,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of CNOT11-KD on CCR4-NOT subunit stability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) HeLa cell lysates transfected with scramble or CNOT11 siRNA were immunoprecipitated using an anti-CNOT3 antibody. Whole-cell lysates (left) and immunoprecipitates (right) were analyzed by immunoblotting with the indicated antibodies. GAPDH was used as a loading control. (B) Quantitative RT-PCR analysis of CCR4-NOT subunit mRNAs (C1–C11) in control and CNOT11-KD HeLa cells. Data were normalized to HPRT and are presented as mean ± SE (n = 3 independent experiments). *p \u0026lt; 0.05, **p \u0026lt; 0.01 versus control by unpaired Student’s t-test. The blots shown were obtained from the same experiment and processed in parallel. The corresponding original, uncropped Western blot images are provided in Supplementary Material 1.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7416154/v1/ccce3301cb1820231f1a36a8.png"},{"id":91076785,"identity":"ed23ea1a-9755-46f4-83fe-fe2a2b0ece84","added_by":"auto","created_at":"2025-09-11 11:12:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":425304,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAutophagy induction in CNOT11-KD cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Phase-contrast images of HeLa, A549, and HT29 cells transfected with scramble or CNOT11 siRNA. Yellow arrows indicate cytoplasmic vesicle-like structures. (B) HeLa cells transfected with scramble or CNOT11 siRNA were stained with CYTO-ID® Autophagy Detection Reagent (green) and DAPI (blue). Representative images of control (left) and CNOT11-KD (right) cells are shown. (C) Immunoblot analysis of cell lysates transfected with scramble or CNOT11 siRNA. (D) HeLa cells transfected with scramble or CNOT11 siRNA were treated with the indicated inhibitors. Cell lysates were prepared and analyzed by immunoblotting with an anti-LC3 antibody. (E) Phase-contrast images of CNOT11 knockdown HeLa cells with or without chloroquine treatment. The blots shown were obtained from the same experiment and processed in parallel. The corresponding original, uncropped Western blot images are provided in Supplementary Material 1.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7416154/v1/21c6fa8740e4c403868cefc5.png"},{"id":91076783,"identity":"2058a3b2-55d9-45a7-85ef-14b58155ac39","added_by":"auto","created_at":"2025-09-11 11:12:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":149999,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe AMPK/ULK1 signaling-mediated autophagy in CNOT11-KD cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A, B) Lysates were prepared from HeLa cells transfected with the indicated siRNAs and analyzed byimmunoblot. (C) HeLa cells stably expressing siRNA-resistant FLAG-tagged CNOT11 or control HeLa cells were transfected with scramble or CNOT11 siRNA. Cell lysates were prepared and analyzed by immunoblot. GAPDH was used as loading controls. The blots shown were obtained from the same experiment and processed in parallel. The corresponding original, uncropped Western blot images are provided in Supplementary Material 1.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7416154/v1/204549740bd33e76828f42c5.png"},{"id":91080006,"identity":"989f64b2-41e3-40fe-ac12-2b0b5a501d06","added_by":"auto","created_at":"2025-09-11 11:28:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":139968,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL-6/JAK-STAT signaling contributes to autophagy in CNOT11-KD cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Volcano plot of RNA-seq data comparing CNOT11 siRNA– and scramble siRNA–treated HeLa cells. The x-axis shows log₂(fold change), and the y-axis shows –log₁₀(FDR). Significantly upregulated (red, FDR \u0026lt; 0.05, log₂FC ≥ 1) and downregulated (blue, FDR \u0026lt; 0.05, log₂FC ≤ –1) genes are indicated. IL-6 is highlighted by an arrow. (B) Gene set enrichment analysis of significantly altered transcripts in CNOT11-KD cells. Bars represent –log₁₀(adjusted p-value); the dashed line indicates the FDR = 0.05 threshold (≈1.30). (C) Quantitative RT-PCR of IL-6 mRNA in control and CNOT11-KD HeLa cells. Data are normalized to GAPDH and presented as mean ± SE (n = 3). p \u0026lt; 0.01 by unpaired t-test. (D) Immunoblot analysis of HeLa cells transfected with the indicated siRNAs. (E) Immunoblot of HeLa cells transfected with scramble or CNOT11 siRNA and treated with STAT3 inhibitor S3I-201. The blots shown were obtained from the same experiment and processed in parallel. The corresponding original, uncropped Western blot images are provided in Supplementary Material 1.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7416154/v1/536dc6b60888e8aea8a5b1ad.png"},{"id":91078616,"identity":"8649c3c1-236f-487a-a378-d05d4409655e","added_by":"auto","created_at":"2025-09-11 11:20:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":76101,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL-6 upregulation in CNOT11-KD cells is not caused by impaired deadenylase activity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Quantitative RT-PCR analysis of unspliced IL-6 precursor transcripts (pre-IL-6) in HeLa cells transfected with scramble or CNOT11 siRNA. Data are normalized to GAPDH and presented as fold change relative to scramble control (mean ± SE; n = 3). p \u0026lt; 0.01 by unpaired t-test. (B) IL-6 mRNA stability in HeLa cells transfected with scramble or CNOT11 siRNA. Total RNA was extracted at 0, 30, and 60 minutes after actinomycin D treatment and analyzed by qRT-PCR for IL-6 mRNA levels. (C) Comparison of poly(A) tail lengths of IL-6 mRNA in control and CNOT11-KD HeLa cells by PCR-based assay (see Materials and Methods).\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7416154/v1/d7c33274a04ac2b9d39339f6.png"},{"id":91076789,"identity":"a87fc1e8-d91e-448a-89e2-ce785894289d","added_by":"auto","created_at":"2025-09-11 11:12:27","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":294020,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCNOT11-KD influences proliferation and increases Adriamycin sensitivity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Real-time proliferation assay of HeLa cells transfected with scramble or CNOT11 siRNA using IncuCyte live cell imaging. Cells were seeded and phase contrast images acquired every 4 h for 96 h. Confluence (%) is plotted as a mean ± SE (n = 6 wells per condition). CNOT11-KD caused a modest but significant delay in proliferation from 48 h onward *p \u0026lt; 0.05 versus control by unpaired Student t-test. (B) Cell-cycle analysis using flow cytometry. Representative histograms of percentages of cells in G1, S, and G2/M phase obtained from control (left) and CNOT11-KD (right) cells are shown. (C) Phase-contrast images of HeLa cells transfected with scramble or CNOT11 siRNA after 24h treatment with Adriamycin (0, 0.5 or 1.5 µM). (D) HeLa cells transfected with scramble or CNOT11 siRNA were treated with Adriamycin at the indicated concentration for 72h. Cell lysates were prepared and subjected to immunoblot analysis. The blots shown were obtained from the same experiment and processed in parallel. The corresponding original, uncropped Western blot images are provided in Supplementary Material 1.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-7416154/v1/2c970a5af069fd208a2da9c2.png"},{"id":96808046,"identity":"cf1f9cc4-4ada-4ae7-b0cd-0867199725ac","added_by":"auto","created_at":"2025-11-26 09:24:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1979129,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7416154/v1/52d3bc80-4c07-42c0-b9b5-182ff424243e.pdf"},{"id":91076780,"identity":"d35686af-f0d6-4365-95ea-991fe307c5d7","added_by":"auto","created_at":"2025-09-11 11:12:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1889905,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarymaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7416154/v1/566991aa9bc011ea6ca54bf7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Regulation of autophagic response by CNOT11 via IL-6/JAK/STAT signaling","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRegulation of gene expression is crucial for cellular function, maintenance of homeostasis, and adaptation to environmental changes. mRNA abundance is regulated at both the transcriptional level by transcription factors and the post-transcriptional level by RNA-binding proteins and non-coding RNAs. In recent years, the importance of regulation of mRNA stability and translational efficiency in gene expression has been increasingly recognized, with particular attention to mRNA degradation pathways as one of the major regulatory mechanisms. A typical mRNA degradation pathway begins with the shortening of poly(A) tails, a process called deadenylation, which serves as a key determinant of mRNA expression levels.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe carbon catabolite repressor 4-negative on TATA-less (CCR4-NOT) complex is a multi-subunit protein complex that is central to mRNA deadenylation.\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e This complex is evolutionarily conserved from yeast to humans, and eight subunits have been identified as components of the complex in mammal. The large scaffold protein CNOT1 plays a crucial role in tethering the other subunits together.\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e CNOT6/6L/7/8 possess deadenylase activity, while CNOT2 and CNOT3 contribute to the stabilization of the complex as regulatory subunits.\u003csup\u003e[\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e CNOT9 is involved in microRNA/small interfering RNA (siRNA)-mediated mRNA degradation through the RNA-induced silencing complex (RISC) and also functions as a cofactor in transcriptional regulation.\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e CNOT10 enhances the deadenylase activity of the complex.\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e When the CCR4-NOT complex loses its function, mRNA expression patterns are largely abrogated, leading to cell death via apoptosis or necroptosis, and resulting in abnormal development and differentiation at the organismal level. CNOT11 (also known as C2ORF29) was specifically identified in vertebrates as a component of the CCR4-NOT complex due to its association with CNOT10.\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e Since its discovery is relatively recent, CNOT11 has a shorter research history than the other subunits, delaying detailed functional analyses. Earlier study showed that CNOT11 depletion did not significantly alter deadenylation kinetics in a β-globin reporter assay.\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e On the other hand, structural analyses have shown that the CNOT1\u0026ndash;CNOT10\u0026ndash;CNOT11 submodule serves as a scaffold for protein\u0026ndash;protein interactions.\u003csup\u003e13\u003c/sup\u003e The antenna domain of CNOT11 binds to the tumor suppressor GGNBP2 (gametogenetin-binding protein 2) and regulates mRNA deadenylation.\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e Furthermore, CNOT11 is involved in translation-dependent tubulin mRNA degradation during tubulin autoregulation.\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e Therefore, CNOT11 contributes to mRNA turnover in several biological aspects.\u003c/p\u003e\u003cp\u003eClinical studies have reported that CNOT11 is significantly upregulated in multiple malignancies, most notably hepatocellular carcinoma and renal cell carcinoma, where its overexpression has been linked to enhanced tumor cell proliferation, invasion, and decreased overall survival in cancer patients.\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e Moreover, elevated CNOT11 levels often correlate with advanced tumor stage and metastasis, suggesting a direct role in driving oncogenic phenotypes.\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e Other CCR4-NOT subunits likewise are relevant to cancer development: CNOT2 overexpression promotes cell cycle progression and suppresses apoptotic pathways, correlating with increased proliferation, lymph node metastasis, and poor prognosis in both breast and lung cancers.\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e CNOT3 functions as a critical cofactor for leukemic stem cell maintenance and facilitates malignant transformation through transcriptional dysregulation in leukemia.\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e Deadenylase activity of CNOT7 stabilizes key oncogenic transcripts such as those encoding growth and survival factors, thereby supporting glioblastoma and colorectal cancer progression.\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e These data suggest that both enzymatic and non-enzymatic subunits of the CCR4-NOT complex contribute to oncogenic processes by altering mRNA expression.\u003c/p\u003e\u003cp\u003eIn this study, we investigate the role of CNOT11 in cell survival, proliferation, and mRNA degradation, and propose its potential involvement in cancer progression within the broader functional context of the CCR4-NOT complex.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eCNOT11-KD results in a decrease of CCR4-NOT subunits\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate biological and biochemical roles of CNOT11, we suppressed CNOT11 expression by introducing siRNA targeting CNOT11 in HeLa cells. We first examined the effects of CNOT11-KD on the expression of other CCR4-NOT complex subunits and on the integrity of complex itself. Immunoblot analysis showed that expression of CNOT6, 6L, 7, 8, 10 was decreased upon CNOT11-KD (Fig. 1A). Consistently, immunoblot analysis following immunoprecipitation with a CNOT3 antibody revealed that CNOT6, 8, 10 within the CCR4-NOT complex were markedly reduced in CNOT11-KD cells compared to control cells that were transfected with scramble siRNA (Fig. 1A). Quantitative PCR (qPCR) analyses demonstrated that mRNA levels of \u003cem\u003eCNOT1, CNOT6,\u003c/em\u003e and \u003cem\u003eCNOT8\u003c/em\u003e were significantly lower in CNOT11-KD cells (Fig. 1B). These results suggest that CNOT11-KD leads to a decrease of several complex subunits, consequently influencing the function of the CCR4-NOT complex.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCNOT11-KD induces autophagy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn accumulation of small vesicles was detected in the cytoplasm of HeLa cells upon CNOT11-KD (Fig. 2A). Similar results were obtained in A549 (lung cancer) and HT29 (colon cancer) cell lines. These cytoplasmic vesicles were stained with a dye that recognizes autophagosome, suggesting that CNOT11-KD cells undergo autophagy (Fig. 2B). Consistently, levels of LC3-II, a marker of autophagy, were increased in CNOT11-KD cells compared to control cells (Fig. 2C). An increase of LC3-II alone does not necessarily indicate autophagy induction, as it may reflect either enhanced autophagosome formation or impaired degradation of autophagosomes following lysosomal fusion. To distinguish between these possibilities, we performed an autophagic flux assay. When CNOT11-KD cells were treated with lysosomal protease inhibitors such as bafilomycin A1, chloroquine, or concanamycin A which block autophagosome degradation in lysosomes, LC3-II levels were further increased (Fig. 2D). Moreover, microscopic observation showed that both the number and size of vehicles in CNOT11-KD cells were further increased following chloroquine treatment (Fig. 2E). Collectively, these findings indicate that HeLa cells undergo autophagy upon CNOT11-KD. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAutophagy is induced via AMPK/ULK1 activation in CNO11-KD cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn general, autophagy is initiated by the activation of the Unc-51 like kinase 1 (ULK1) complex, which is regulated by mTOR and/or AMPK depending on the cellular nutritional and energy status.\u003csup\u003e[22]\u003c/sup\u003e Under nutrient-rich conditions, mTORC1 binds to ULK1 and phosphorylates it at Ser757, thereby preventing ULK1 from interacting with AMPK and blocking autophagy initiation. Conversely, upon nutrient starvation, AMPK is activated and phosphorylates ULK1 at Ser555 for activation. Activated ULK1 forms a complex with dephosphorylated autophagy-related 13 (ATG13) and the focal adhesion kinase family interacting protein of 200 kD (FIP200), leading to autophagy.\u003csup\u003e[23]\u003c/sup\u003e We then examined the contribution of AMPK, ULK1 and ATG13 to autophagy in CNOT11-KD cells. Immunoblot analyses showed that phosphorylated forms of AMPKa and ULK1 at Ser555 were increased, whereas phosphorylated forms of ATG13 and ULK1 at Ser757 were decreased (Fig. 3A). The increase of LC3-II in CNOT11-KD cells was attenuated upon simultaneous suppression of ULK1 concomitant with modest decrease of AMPKa phosphorylation (Fig. 3B). ULK1 suppression reduced ATG13 expression, also contributing to the decrease of LC3-II in CNOT11-KD cells (Fig. 3B). To further confirm that CNOT11-KD induces autophagy, we re-introduced CNOT11 in CNOT11-KD cells. In these cells, the CNOT11 sequence is modified at the nucleotide level without altering the amino acid sequence so that it becomes resistant to targeting by CNOT11 siRNA. When siRNA-resistant CNOT11 is exogenously expressed via retrovirus-mediated gene transfer, an increase of LC3-II expression was not observed even after CNOT11 siRNA introduction (Fig. 3C). In cells infected with control retrovirus, CNOT11-KD led to an increase of LC3-II. These results suggest that the AMPK/ULK1 pathway contributes to LC3-II accumulation in CNOT11-KD cells, indicating a potential involvement of CNOT11 in the autophagy-related processes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe JAK/STAT pathway is involved in Autophagy in CNOT11-KD cells\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo understand the molecular basis of the autophagy induction upon CNOT11-KD, we performed RNA-seq analysis. The results showed that 142 and 151 genes were significantly upregulated and downregulated upon CNOT11-KD, respectively (Fig. 4A). Gene set enrichment analysis of the differentially expressed genes showed that the JAK-STAT signaling pathway was the most significantly enriched among the upregulated genes (Fig. 4B). The JAK-STAT pathway is a critical intracellular signaling cascade that primarily transduces signals from cytokines and growth factors, playing essential roles in immune responses, cell proliferation, and inflammation. Interleukin-6 (IL-6) is a representative cytokine known to activate the JAK-STAT pathway, particularly STAT3\u003csup\u003e24\u003c/sup\u003e. Indeed, the results of RNA-seq revealed that \u003cem\u003eIL-6\u003c/em\u003e expression was upregulated 1.9-fold in CNOT11-KD cells (Fig. 4A), leading us to investigate the relationship between the IL-6/JAK/STAT pathway and autophagy upon CNOT11-KD. We confirmed a significant increase in \u003cem\u003eIL-6\u003c/em\u003e mRNA in CNOT11-KD cells compared with control cells by performing qPCR analysis (Fig.4C). Immunoblot analyses also showed that CNOT11-KD led to an increase in IL-6 protein together with an increase of LC3-II (Fig. 4D). Furthermore, the JAK/STAT pathway is activated in CNOT11-KD cells as indicated by an increase of phosphorylated STAT1 and 3 (Fig. 4D). Importantly, the simultaneous KD of CNOT11 and IL-6 or a treatment of CNOT11-KD cells with the STAT3 inhibitor S31-201 reduced the increase of LC3-II (Fig. 4D and 4E). These data suggest that the LC3-II increase upon CNOT11-KD is mediated, at least in part, through IL-6-dependent activation of the JAK-STAT pathway.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncreased IL-6 in CNOT11-KD cells is not caused by mRNA stabilization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe next investigated whether the increase of \u003cem\u003eIL-6\u003c/em\u003e mRNA was due to impaired deadenylase activity of the CCR4-NOT complex lacking CNOT11. First, we found that the level of premature unspliced \u003cem\u003eIL-6\u003c/em\u003e mRNA significantly increased in CNOT11-KD cells (Fig.5A). Next, we compared the stability of \u003cem\u003eIL-6\u003c/em\u003e mRNA by measuring its half-life between control and CNOT11-KD cells, but there was no significant difference in the stability of \u003cem\u003eIL-6\u003c/em\u003e mRNA between them (Fig.5B). Furthermore, the polyA tail length of \u003cem\u003eIL-6\u003c/em\u003e mRNA was comparable between control and CNOT11-KD cells (Fig.5C). Therefore, the increased \u003cem\u003eIL-6\u003c/em\u003e mRNA in CNOT11-KD cells is likely due to enhanced transcription rather than due to impaired deadenylase activity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCNOT11-KD reduces HeLa cell proliferation and enhances Adriamycin sensitivity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAutophagy and the cell cycle are closely interconnected, and activation of autophagy is known to influence cell cycle progression as well as cellular sensitivity to anticancer therapies. Therefore, we investigated cell proliferation, cell cycle progression, and chemotherapeutic response in CNOT11-KD HeLa cells. Live-cell imaging analysis using the IncuCyte system revealed that CNOT11-KD cells exhibited significantly slower proliferation compared to control cells (Fig. 6A).Flow cytometry analysis demonstrated a decrease in the proportion of cells in the G1 phase and an increase in that in the S and G2/M phases relative to controls (Fig. 6B), suggesting that autophagy induced by CNOT11-KD may alter cell cycle progression, particularly during the S phase. To explore whether CNOT11-KD influences the response to chemotherapy, we compared the effects of Adriamycin (doxorubicin), a DNA-damaging agent, on cell viability between control and CNOT11-KD HeLa cells. While low concentrations of Adriamycin had minimal impact on cell viability in control cells, high concentrations resulted in the appearance of floating cells (Fig. 6C). Under the CNOT11-KD condition, floating cells were observed even after low-dose Adriamycin treatment, and the number of floating cells further increased at higher-dose Adriamycin treatment (Fig. 6C). Immunoblot analysis revealed that Adriamycin treatment induced only a modest increase in cleaved PARP in control cells, whereas a more pronounced increase in cleaved PARP was observed in CNOT11-KD cells (Fig. 6D). These findings indicate that suppression of CNOT11 not only slows proliferation by altering cell cycle progression but also renders HeLa cells more sensitive to Adriamycin-induced cytotoxicity.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we identified CNOT11 as a critical regulatory component of the CCR4-NOT complex that influences cellular responses such as autophagy, proliferation and sensitivity to anti-cancer drug. CNOT11-KD led to reduced expression of several complex subunits, indicating insufficient function of the complex. The increase of \u003cem\u003eIL-6\u003c/em\u003e mRNA is one of the major characteristics in CNOT11-KD cells but is not caused by an impaired mRNA deadenylation. Therefore, the structural disruption of the complex upon CNOT11-KD compromises broader transcriptional and post-transcriptional regulatory mechanisms.\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eA key finding of our study is that the loss of CNOT11 promotes autophagy through both the AMPK\u0026ndash;ULK1 and IL-6/JAK/STAT3 signaling pathways. IL-6\u0026ndash;mediated autophagy has been reported in various cancer types, highlighting the broad role of cytokine signaling in metabolic regulation. Cathepsin L (CTSL) activates the IL-6/JAK/STAT3 signaling and induces autophagy in laryngeal carcinoma, thereby contributing to tumor metastasis.\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e Increasing evidence points to a functional interaction between the JAK/STAT and AMPK/ULK1 pathways. Notably, STAT3 directly binds to the promoter of LKB1 (STK11), a master upstream kinase that phosphorylates and activates AMPK under energy stress conditions.\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e Once activated, AMPK phosphorylates ULK1 at Ser555 and other residues, initiating autophagy.\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e Conversely, ULK1 can phosphorylate STAT3, enhancing its transcriptional activity and establishing a feed-forward loop between autophagy induction and cytokine signaling.\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e While the IL-6/STAT3 signaling is known to promote metabolic adaptation in breast cancer cells, direct evidence connecting IL-6\u0026ndash;induced STAT3 phosphorylation to AMPKα1 and ULK1 activation remains limited.\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e Nevertheless, our findings support the existence of the crosstalk between the JAK/STAT and AMPK/ULK1 pathways in the context of autophagy induced by CNOT11-KD. By linking CCR4\u0026ndash;NOT complex dysfunction to autophagy-regulatory pathways, this study provides new insights into how RNA regulatory mechanisms integrate with metabolic stress responses to support cancer cell survival and progression.\u003c/p\u003e\u003cp\u003eThe increase of \u003cem\u003eIL-6\u003c/em\u003e mRNA observed in CNOT11-KD cells was not due to enhanced mRNA stabilization. This raises the possibility that transcriptional regulation may be involved. Several lines of evidence suggest that the mammalian CCR4\u0026ndash;NOT complex plays a direct role in transcriptional control. For example, CNOT1 recruits the histone acetyltransferase p300 to specific promoters, promoting H3K27 acetylation and activation of stress-responsive genes.\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e Similarly, CNOT3 interacts with the SWI/SNF chromatin remodeling complex to regulate cytokine gene accessibility in macrophages.\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e In mouse embryonic stem cells, the complex is localized in the nucleus and associates with promoter regions of self-renewal genes,\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e while also regulating transcriptional elongation and lineage-specific transcription in B cell development via interactions with transcription factors and nuclear receptors.\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e These findings collectively suggest that CNOT11, as a component of the CCR4\u0026ndash;NOT complex, may also participate in transcriptional regulation of IL-6, possibly through interaction with nuclear transcription factors or chromatin modifiers. Supporting this idea, recent studies have identified GGNBP2 as a tumor suppressor in triple-negative breast cancer (TNBC), which acts as a negative regulator of the IL-6/STAT3 signaling. Overexpression of GGNBP2 in TNBC cells reduces proliferation, migration, invasion, and stem cell\u0026ndash;like properties, accompanied by attenuated IL-6/STAT3 signaling.\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e This is particularly relevant to our findings, where CNOT11 knockdown results in increased IL-6 expression and enhanced STAT3 activation, leading to autophagy. Taken together, the suppressive effect of GGNBP2 on IL-6/STAT3 signaling and our own results suggest that loss of CNOT11 may relieve transcriptional repression or enhance activation of cytokine pathways, consequently inducing autophagy.\u003c/p\u003e\u003cp\u003eCNOT11-KD in HeLa cells altered cell-cycle distribution, characterized by a reduced G1-phase and increased S- and G2/M-phase populations. While the shortening of the G1 phase and accumulation in the S phase are generally associated with accelerated proliferation, proliferation of CNOT11-KD HeLa cells was suppressed. Several studies have shown that replication stress and checkpoint activation can lead to similar phenotypes, particularly in p53-deficient cells such as HeLa cells. Under conditions of replication fork stalling, activation of the ATR\u0026ndash;CHK1 pathway slows progression from S phase to M phase, resulting in a decreased G1 pool and increased S- and G2/M-phase populations.\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e In U2OS cells, which lack a functional G1/S checkpoint, forced S-phase entry under stress similarly induces ATR/CHK1-mediated surveillance, transiently increasing the proportions of cells in the S and G2/M phases.\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e Moreover, in p53-deficient cells, the G2/M checkpoint serves as the primary barrier to mitotic entry following replication perturbations.\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e Whether such checkpoint machinery is activated in CNOT11-KD cells remains an important question for future investigation.\u003c/p\u003e\u003cp\u003eCNOT11-KD sensitized cells to Adriamycin, a DNA-damaging chemotherapeutic agent. While autophagy functions as a cytoprotective response particularly under nutrient-starved conditions, excessive or uncontrolled autophagy can lead to cell death, as seen in Bax/Bak\u0026ndash;null cells.\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e Under CNOT11-KD conditions, we observed a greater number of floating cells following low-dose Adriamycin treatment, accompanied by enhanced PARP cleavage. Several anticancer agents, such as obatoclax, gossypol, resveratrol, and betulinic acid, are known to induce autophagic cell death in liver, prostate, colon, and pancreatic cancers.\u003csup\u003e[\u003cspan additionalcitationids=\"CR41 CR42\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e Collectively, our findings position CNOT11 as a regulatory node linking CCR4\u0026ndash;NOT complex integrity, cytokine signaling, autophagy, and cell viability. Suppression of CNOT11 in cancer cells initiates a cascade of transcriptional activation that leads to autophagy, cell cycle arrest, and enhanced sensitivity to anticancer drugs, suggesting a novel approach for cancer chemotherapy.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eCells and Reagents\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeLa (RCB0007) was obtained from the RIKEN BioResource Research Center (RIKEN BRC, Tsukuba, Japan), and HT29 (JCRB0019) and A549 (JCRB0076) cells were purchased from the JCRB Cell Bank (Japanese Collection of Research Bioresources, Osaka, Japan). Adriamycin (doxorubicin) was purchased from Funakoshi Co., Ldt (Tokyo, Japan). Bafilomycin A1 and STAT3 inhibitor (S3I-201) were from Sigma-Aldrich (St. Louis, MO, USA). Chloroquine and concanamycin A were from Tocris Bioscience (Bristol, UK).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntibodies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAntibodies against CNOT1, CNOT2, CNOT3, CNOT6, CNOT6L, CNOT8, CNOT9, and CNOT10 were used as previously described.\u003csup\u003e[40]\u003c/sup\u003e The antibody against CNOT11 (HPA069823) was from Atlas Antibodies AB (Bromma, Sweden). Antibodies against GAPDH (#2118), AMPK\u0026alpha; (#2603), phospho-AMPK\u0026alpha; (Thr172; #2535), mTOR (#2983), phospho-mTOR (Ser2448; #2974), ULK1 (#8054), phospho-ULK1 (Ser555; #5869), Atg13 (#13273), phospho-Atg13 (Ser318; #46329), IL-6 (#12153), STAT1 (#9172), phospho-STAT1 (Tyr701; #7649), STAT3 (#4904), phospho-STAT3 (Tyr705; #9145), and cleaved PARP (#9541) were obtained from Cell Signaling Technology (Danvers, MA, USA). The antibody against LC3 (PM036) was from MBL International (Woburn, MA, USA), and \u0026alpha;-Tubulin (T9026) was from Sigma-Aldrich.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell culture and siRNA transfection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeLa, A549, and HT29 cells were cultured in Dulbecco\u0026apos;s Modified Eagle\u0026rsquo;s Medium (DMEM; Fujifilm Wako, Osaka, Japan) supplemented with 10% fetal bovine serum (FBS; Nichirei Corporation, Tokyo, Japan) and 100 U/mL penicillin\u0026ndash;streptomycin (Thermo Fisher Scientific, Waltham, MA, USA) at 37\u0026deg;C in a humidified atmosphere containing 5% CO₂. For siRNA-mediated knockdown, 100 pmol of double-stranded siRNA was transfected into 5 \u0026times; 10⁵ cells using Lipofectamine RNAiMAX (Thermo Fisher Scientific) according to the manufacturer\u0026rsquo;s instructions. The siRNA sequences used were as follows: scramble, 5\u0026prime;-UUCUCCGAACGUGUCACGUTT-3\u0026prime; and 5\u0026prime;-ACGUGACACGUUCGGAGAATT-3\u0026prime;; CNOT11, 5\u0026prime;-CCGAACGCCAAUCUGAAUUGC-3\u0026prime; and 5\u0026prime;-AAUUCAGAUUGGCGUUCGGCC-3\u0026prime;; ULK1, 5\u0026rsquo;-GCACAGAGACCGUGGGCAATT-3\u0026rsquo; and 5\u0026rsquo;-UUGCCCACGGUCUCUGUGCTT. For IL-6 knockdown, Silencer\u0026trade; Pre-Designed siRNA targeting human IL6 (ID: 144576; Cat# AM16708; Thermo Fisher Scientific) was used. Cells were analyzed 72 hours after transfection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAutophagy detection and autophagy flux assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAutophagy and autophagic flux were assessed in HeLa cells 72 hours after siRNA transfection. For detection of autophagic vacuoles, cells were incubated with CYTO-ID\u0026reg; Green Detection Reagent (1:1000 dilution; Enzo Life Sciences, Farmingdale, NY, USA) for 30 minutes at 37\u0026nbsp;\u0026deg;C in the dark. Nuclei were counterstained with Hoechst 33342, and cells were washed twice with the provided assay buffer. Fluorescence images were acquired using a laser scanning confocal microscope (TCS SPE; Leica Microsystems, Wetzlar, Germany). For autophagic flux, cells were treated with lysosomal inhibitors; bafilomycin A1 (5\u0026nbsp;nM), chloroquine (50\u0026nbsp;nM), and concanamycin A (5\u0026nbsp;nM) during the final 4 hours. After treatment, one set of cells was subjected to immunoblotting to analyze LC3-II protein levels, and another set was examined by phase-contrast microscopy.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoprecipitation and immunoblot\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were washed with PBS and lysed in TNE buffer (50 mM Tris-HCl [pH 7.5], 150 mM NaCl, 1 mM EDTA, 1 mM phenylmethylsulfonyl fluoride, 10 mM NaF, 10 mM \u0026beta;-glycerophosphate, and 1% Nonidet P-40). Cell lysates were immunoprecipitated using 1 \u0026micro;g of mouse monoclonal anti-CNOT3 antibody, incubated overnight at 4 \u0026deg;C with rotation in the presence of Dynabeads Protein G (Thermo Fisher Scientific). Immunoprecipitates or equal amounts of total protein were resolved by SDS-PAGE and transferred to Immobilon-P membranes (Merck Millipore). Membranes were blocked with 3% skim milk in Tris-buffered saline containing 0.05% Tween 20 (TBST) for 1 hour at room temperature, and then incubated overnight at 4 \u0026deg;C with primary antibodies in Can Get Signal\u0026reg; Immunoreaction Enhancer Solution (TOYOBO, Osaka, Japan). After three washes with TBST, membranes were incubated with HRP-conjugated secondary antibodies for 1 hour at room temperature, followed by three additional washes with TBST. Detection was performed using Immobilon Western Chemiluminescent HRP Substrate (Merck Millipore), and chemiluminescent signals were visualized using an Amersham Imager 680 (GE Healthcare).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVirus infection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRetroviruses were produced by transfecting Plat-E packaging cells with 2 \u0026micro;g of pMXs-puro vectors encoding CNOT11 cDNA using TransIT-LT1 transfection reagent (Mirus Bio LLC). Forty-eight hours later, supernatants were filtered, supplemented with polybrene (5 \u0026micro;g/mL), and used to infect ecotropic receptor\u0026ndash;expressing HeLa cells. Cells were seeded at 8.5 \u0026times; 10⁵ cells per 10-cm dish one day prior to infection. Two days after retroviral infection, cells were trypsinized, diluted, and cultured in the presence of puromycin (1 \u0026micro;g/mL) for an additional 3 days to select infected cell populations. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReverse transcriptase PCR assays and mRNA half-life measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted using Isogen reagent (Nippon Gene Co., Ltd., Toyama, Japan). Complementary DNA (cDNA) was synthesized from 0.5\u0026ndash;1 \u0026micro;g of total RNA using PrimeScript II reverse transcriptase (Takara Bio Inc., Shiga, Japan). Quantitative reverse transcription PCR (qRT-PCR) was performed using a QuantStudio\u0026trade; 5 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) and FastStart Universal SYBR Green Master Mix (Takara Bio Inc.). GAPDH expression was used as an internal control for normalization. For mRNA stability, cells were treated with actinomycin D (2.5 \u0026micro;g/mL; Sigma-Aldrich) 3 days after siRNA transfection, and RNA was collected at 0, 30, and 60 min following the addition of actinomycin D.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePoly(A) tail assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePoly(A) tail lengths of mRNAs were analyzed using the Poly(A) Tail-Length Assay Kit (Thermo Fisher Scientific,) with minor modifications. Total RNA (1 \u0026micro;g) was incubated with poly(A) polymerase in the presence of guanosine (G) and inosine (I) to add a GI tail. Complementary DNA (cDNA) was synthesized from GI-tailed RNA using a PCR poly(A) test (PAT) universal primer and reverse transcriptase. PCR amplification was performed using gene-specific primers, the PAT universal primer, and HotStart-IT\u0026reg; Taq DNA Polymerase (Affymetrix, Santa Clara, CA, USA).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA sequencing (RNA-seq) was performed on total RNA from HeLa cells by the DNA Sequencing Section at the Okinawa Institute of Science and Technology Graduate University (OIST). One hundred nanograms of total RNA were used for library preparation with the TruSeq Stranded mRNA Library Prep Kit for NeoPrep (Cat# NP-202-1001; Illumina Inc., San Diego, CA, USA), which enables poly(A) selection using oligo(dT) beads, following the manufacturer\u0026rsquo;s instructions. Paired-end RNA-seq (150 bp \u0026times; 2) was conducted using the HiSeq 3000/4000 PE Cluster Kit (Cat# PE-410-1001; Illumina Inc.) in accordance with the manufacturer\u0026apos;s protocol.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA-seq analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePaired-end RNA-seq reads were mapped using Strand NGS software (Strand Life Sciences, Bangalore, India). Transcript abundance was quantified as fragments per kilobase of transcript per million mapped reads (FPKM). Gene expression values were normalized to Gapdh FPKM, and fold changes between knockdown and control conditions were calculated. Differentially expressed genes (DEGs) and pathway enrichment analyses were conducted using iDEP.96 (http://bioinformatics.sdstate.edu/idep96/). Gene Ontology (GO) enrichment analysis was also performed using DAVID Bioinformatics Resources 6.8 (https://david.ncifcrf.gov). The raw and processed RNA-seq data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE306607.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSTAT3 inhibition assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSTAT3 signaling was inhibited with S3I-201 (100\u0026nbsp;\u0026micro;M; Selleck Chemicals, Houston, TX, USA) for 6 hours prior to harvesting. For siRNA co-transfection experiments, CNOT11 and IL-6 siRNAs were simultaneously introduced using Lipofectamine RNAiMAX. LC3-II protein levels were analyzed by immunoblotting as described above.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell proliferation assay using live-cell imaging\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProliferation of HeLa cells was monitored using the IncuCyte\u0026reg; S3 Live-Cell Analysis System (Sartorius AG, G\u0026ouml;ttingen, Germany) according to the manufacturer\u0026rsquo;s instructions. Phase-contrast images were acquired every 4 hours over a 96 hour period. Cell confluence was automatically quantified using the IncuCyte software to generate growth curves.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlow cytometric analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeLa cells were harvested 72 hrs after siRNA transfection and resuspended in PI solution containing 1 mL PBS, 50 \u0026mu;L PI (1 mg/mL; Invitrogen), 10 \u0026mu;L RNase A (10 mg/mL; Sigma-Aldrich), and 10 \u0026mu;L FBS. Cell cycle distribution was analyzed using a FACSAria\u0026trade; III flow cytometer (BD Biosciences, Franklin Lakes, NJ, USA), and data were processed using FlowJo\u0026trade; software version 10.10 (BD Biosciences).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferences between groups were examined for statistical significance using Student\u0026rsquo;s t-test (one-tailed distribution with two-sample equal variance). We considered a p-value of \u0026lt;0.05 statistically significant.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Okinawa Institute of Science and Technology Graduate University for generous support to the Cell Signal Unit.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article and its supplementary information files.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.N. T.S. and T.Y. designed the study. S.N. performed the experiments. S.N. and T. S. wrote the manuscript, and All authors reviewed and approved the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMugridge JS, Coller J, Gross JD. Structural and molecular mechanisms for the control of eukaryotic 5\u0026prime;\u0026ndash;3\u0026prime; mRNA decay. \u003cem\u003eNat Struct Mol Biol\u003c/em\u003e. 2018;25(11):1077\u0026ndash;1085.\u003c/li\u003e\n\u003cli\u003eCollart MA. Global control of gene expression in yeast by the Ccr4-Not complex. \u003cem\u003eGene\u003c/em\u003e. 2003;313:1\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eIto K, Takahashi A, Morita M, Suzuki T, Yamamoto T. 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RNA Biol. 2022;19(1):234\u0026ndash;246. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7416154/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7416154/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWhile the CCR4-NOT complex is a key player of deadenylation-mediated mRNA degradation, the roles of its component CNOT11 remain elusive. Recent clinical studies have shown that CNOT11 is highly expressed in certain cancer types, and the elevated expression is associated with poor survival in cancer patients. In this study, we investigate the role of CNOT11 in cell viability, proliferation and mRNA degradation in tumor cells. Suppression of CNOT11 in HeLa cells leads to decreased expression of CCR4-NOT subunits and induces autophagy through the AMPK/ULK1 pathway. Transcriptomic and biochemical analyses reveal an activation of the JAK-STAT signaling pathway in CNOT11-knockdown (CNOT11-KD) cells, accompanied by increased IL-6 expression that contributes to autophagy. The increase of IL-6 is caused by an enhanced transcription rather than impaired deadenylation. We also find that proliferation of HeLa cells is significantly retarded, and cells are more sensitive to adriamycin treatment upon CNOT11-KD. These findings suggest that CNOT11 modulates cancer cell viability through regulation of cytokine production at the transcriptional level, implicating CNOT11 as a potential pharmacological target against cancer.\u003c/p\u003e","manuscriptTitle":"Regulation of autophagic response by CNOT11 via IL-6/JAK/STAT signaling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 11:12:22","doi":"10.21203/rs.3.rs-7416154/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"11b0073c-300f-4ec6-af59-cff8f71648b8","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":54350874,"name":"Biological sciences/Cancer"},{"id":54350875,"name":"Biological sciences/Cell biology"},{"id":54350876,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-11-26T09:23:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 11:12:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7416154","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7416154","identity":"rs-7416154","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}