Neuro-immune interactions are critical in cancer, yet their molecular features in bladder cancer remain unclear. We analyzed transcriptomic data from TCGA and UCSC Xena to investigate the expression profiles and molecular subtypes of neuro-immune–related genes, and constructed a neuro-immune–related score (NAS) model. Single-cell transcriptomic data were integrated to explore the immune microenvironmental features, and functional validation was performed by knocking down SERPINE2 with shRNA in T24 cells. The results showed that six core genes (SERPINE2, NXPH4, SERPINB2, C2orf40, SERPINB12, SERPINB10) were identified to stratify patients into high- and low-risk groups, with robust predictive power across clinical subgroups and validation cohorts. Single-cell RNA-seq data revealed significant NAS heterogeneity among cell populations. The NAS-high state was enriched in TGFβ, EGF, and FGF signaling with activation of EZH2 and SMARCA4, while the NAS-low state showed immune-regulatory features. Functional assays confirmed that SERPINE2 knockdown suppressed proliferation, migration, invasion, while increasing apoptosis of T24 cells, highlighting its oncogenic role. Moreover, genome-wide association studies (GWAS) suggested that genetic variants in SERPINE2 and related genes may increase bladder cancer susceptibility. Collectively, our findings provide novel insights into neuro-immune–driven tumor heterogeneity and immune remodeling, establish the NAS model as an innovative prognostic tool, and identify SERPINE2 as a promising therapeutic target for precision management of bladder cancer.

Hyperactivation of fatty acid biosynthesis holds promise as a targeted therapeutic strategy in prostate cancer (PCa). However, inhibiting these enzymes could potentially promote metastatic progression in various other cancers. Herein, we found that depletion of acetyl-CoA carboxylase 1 (encoded by ACACA), the enzyme responsible for the first and rate-limiting step of de novo fatty acid biosynthesis, facilitated epithelial-mesenchymal transition (EMT) and migration of PCa cells. This finding was validated in vitro through cell migration assays and in vivo using a metastatic model established by tail vein injection of ACACA-depleted cells into BALB/c nude mice. Additionally, depletion of ACACA activated the mitogen-activated protein kinase (MAPK)/extracellular signal-regulated protein kinases (ERK) pathway. Inhibition of the MAPK/ERK signaling pathway reduced EMT and migration in ACACA-depleted cells. Our study is the first to indicate targeting ACACA induces an “unexpected” escape program through activation of the MAPK/ERK signaling pathway in PCa, ultimately leading to EMT and metastasis. Therefore, we strongly recommend that the potential adverse effects of targeting ACACA or its derived therapeutic agents must be given extreme attention, especially in MAPK-related cancers.

Acetyl-CoA carboxylase alpha (ACACA) is a key enzyme in fatty acid biosynthesis and a proposed therapeutic target in prostate cancer. However, its role in androgen receptor-independent prostate cancer (ARIPC), an aggressive and treatment-resistant subtype, remains unclear. This study aimed to investigate the effects of ACACA depletion on ARIPC, with a focus on inflammation and metastasis. ACACA expression patterns were analyzed across multiple metastatic castration-resistant prostate cancer (mCRPC) datasets. In ARIPC cell lines, ACACA was inhibited via both shRNA and the pharmacological inhibitor TOFA. Transcriptomic, metabolomic, and single-cell RNA sequencing data were used to identify downstream changes. Inflammatory signaling was assessed by qPCR, western blotting, and immunofluorescence. Cell migration was evaluated via wound healing and transwell assays, and the metastatic potential was examined in a mouse tail vein injection model. The roles of arachidonic acid (AA), cytosolic phospholipase A2 (cPLA2), and NF-κB signaling were further tested through targeted inhibition. ACACA expression was reduced in ARIPC and was negatively correlated with inflammatory pathways. Its inhibition upregulated proinflammatory cytokines and chemokines, elevated AA and eicosanoid levels, and increased cPLA2 expression. Single-cell RNA sequencing confirmed NF-κB signaling enrichment in ACACA-low tumor cells. Mechanistically, elevated AA activated NF-κB signaling. ACACA depletion enhanced cell migration and metastasis, along with macrophage infiltration. Inhibiting cPLA2 or NF-κB signaling reversed these effects. This study reveals a previously unrecognized tumor-promoting effect of ACACA depletion in ARIPC. Targeting ACACA in this context enhances inflammation and metastasis via arachidonic acid-mediated activation of NF-κB signaling. These findings highlight a context dependent, tumor-promoting role of ACACA inhibition and underscore the need for combinational strategies to avoid potential adverse outcomes in metabolic therapies. Not applicable.

BACKGROUND:Prostate cancer (PCa) incidence increases as age advances and seriously endangers men's health worldwide. Arginase 2 (ARG2) has been identified as a potential diagnostic and prognostic marker for PCa. However, the molecular mechanisms underlying its function in PCa remain undefined. METHODS:ARG2 mRNA and protein expression were quantified in PCa tissues and cells using qRT-PCR and Western blot. Cellular proliferation, glucose consumption, lactate production, apoptosis, and ferroptosis were evaluated via EdU incorporation, colony formation assays, commercial kits, and flow cytometry. Subsequently, the xenograft model was established to assess ARG2's role in tumor growth in vivo. Bioinformatics analysis and RNA immunoprecipitation (RIP) were employed to investigate the interaction between Wilms' tumor 1-associating protein (WTAP), a key component of the N6-methyladenosine (m6A) methyltransferase complex, and ARG2 mRNA. Besides, mRNA stability was determined using actinomycin D chase assays. RESULTS:ARG2 exhibited low expression in PCa tissues and cells. Upregulation of ARG2 inhibited proliferation and glycolysis, and promoted apoptosis, oxidative stress and ferroptosis of PCa cells. However, silencing ARG2 had the opposite effects. In vivo, ARG2 overexpression suppressed tumor growth. Mechanistically, WTAP bound directly to ARG2 mRNA, and their expression levels were inversely correlated. WTAP knockdown phenocopied ARG2 overexpression by repressing proliferation and glycolysis and enhancing apoptosis/ferroptosis, effects reversed by ARG2 silencing. ARG2 overexpression counteracted the oncogenic effects of WTAP overexpression. CONCLUSION:WTAP bound to ARG2 and suppressed its expression, thereby promoting the malignant progression of PCa.

Objective:Metabolism, a basic need and biochemical process for cell survival and proliferation, is closely connected with the pathogenesis and progression of prostate cancer. Methods:A four-gene signature construct that includes CKM (CKM), CD38, Enoyl Coenzyme A(EHHADH), and Arginase 2(ARG2) was created by bioinformatics. Finally, hub genes were validated by IHC and in vitro experiments. Results:The results showed the AUCs of the logistic regression and neural networks diagnostic model for the diagnosis of two subtypes were 0.920 and 0.936, respectively. The risk score demonstrated by univariable and multivariable Cox analysis is an independent predictive component of the prognostic signature for DFS. According to immunohistochemical analyses, ARG2 and CD38 expression levels were considerably under-expressed, but CKM and EHHADH expression levels were significantly overexpressed. Furthermore, The expression of ARG2 was significantly down-regulated in the late Gleason score. Finally, we found that ARG2 is lowly expressed in prostate cancer cells. Furthermore, based on the effect of ARG2 on the malignant phenotype of PCa in vitro, we also found that ARG2 may be a tumor suppressor that plays an important role in inhibiting proliferation, migration, and invasion. Conclusions:These findings suggest that ARG2 has been tentatively identified as a new target for research into how PCa develops in metabolism and for the development of innovative targeted treatments.

Sorafenib is the most widely used first-line drug for the treatment of the advanced hepatocellular carcinoma (HCC). Unfortunately, sorafenib resistance often limits its therapeutic efficacy. To evaluate the efficacy of artesunate against sorafenib-resistant HCC and to investigate its underlying pharmacological mechanisms, a "sorafenib resistance related gene-ART candidate target" interaction network was constructed, and a signaling axis consisting with artesunate candidate target AFAP1L2 and sorafenib target SRC, and the downstream FUNDC1-dependent mitophagy was identified as a major contributor to the sorafenib resistance and a potential way of artesunate to mitigate resistance. Notably, our clinical data demonstrated that AFAP1L2 expression in HCC tissues was markedly higher than that in adjacent non-cancerous liver tissues (P < 0.05), and high AFAP1L2 expression was also significantly associated with an unfavorable overall survival of HCC patients (P < 0.05). Experimentally, AFAP1L2 was overexpressed in sorafenib resistant cells, leading to the activation of downstream SRC-FUNDC1 signaling axis, further blocking the FUNDC1 recruitment of LC3B to mitochondria and inhibiting the activation of mitophagy, based on both in vitro and in vivo systems. Moreover, artesunate significantly enhanced the inhibitory effects of sorafenib on resistant cells and tumors by inducing excessive mitophagy. Mechanically, artesunate reduced the expression of AFAP1L2 protein, suppressed the phosphorylation levels of SRC and FUNDC1 proteins, promoted the FUNDC1 recruitment of massive LC3B to mitochondria, and further overactivated the mitophagy and subsequent cell apoptosis of sorafenib resistant cells. In conclusion, artesunate may be a promising strategy to mitigate sorafenib resistance in HCC via exacerbating AFAP1L2-SRC-FUNDC1 axis-dependent mitophagy.

Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I–III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.

Figure S2 showed the increased GPD1 expression was seen in cancer patients in TCGA database and GPD1 overexpression enhanced the anti-proliferation ability of metformin in vitro.

Supplementary Tab S1-S9. Supplementary Tab. S1. Follow-up clinicopathological information of patients from MGH cohort; Supplementary Tab. S2. ligonucleotide Sequence for all the primers used in the study; Supplementary Tab.S3. The antibodies used in this study; Supplementary Tab.S4. Associations of miR-195 and RPS6KB1 protein expression with clinicopathological features of prostate cancer (PCa) patients; Supplementary Tab.S5. Prognostic value of miR-195 expression for the biochemical recurrence-free survival in univariate and multivariate analysis by Cox Regression; Supplementary Tab. S6 Differentially expressed proteins detected by iTRAQ; Supplementary Tab. S7 Canonical pathways analysis by IPA; Supplementary Tab. S8 Diseases and bio functions analysis by IPA; Supplementary Tab.S9. Prognostic value of RPS6KB1 expression for the biochemical recurrence-free survival in univariate and multivariate analysis by Cox Regression.

Figure S3 showed the detection of G3P, DHAP and methylglyoxal in cancer cells treated with or without different concentrations of G3P.

Background: Metastatic castration-resistant prostate cancer (mCRPC) is a highly aggressive stage of prostate cancer, and non-mutational epigenetic reprogramming plays a critical role in its progression. Super enhancers (SE), epigenetic elements, are involved in multiple tumor-promoting signaling pathways. However, the SE-mediated mechanism in mCRPC remains unclear. Methods: SE-associated genes and transcription factors were identified from a cell line (C4-2B) of mCRPC by the CUT&Tag assay. Differentially expressed genes (DEGs) between mCRPC and primary prostate cancer (PCa) samples in the GSE35988 dataset were identified. What's more, a recurrence risk prediction model was constructed based on the overlapping genes (termed SE-associated DEGs). To confirm the key SE-associated DEGs, BET inhibitor JQ1 was applied to cells to block SE-mediated transcription. Finally, single-cell analysis was performed to visualize cell subpopulations expressing the key SE-associated DEGs. Results: Nine human TFs, 867 SE-associated genes and 5417 DEGs were identified. 142 overlapping SE-associated DEGs showed excellent performance in recurrence prediction. Time-dependent receiver operating characteristic (ROC) curve analysis showed strong predictive power at 1 year (0.80), 3 years (0.85), and 5 years (0.88). The efficacy of his performance has also been validated in external datasets. In addition, FKBP5 activity was significantly inhibited by JQ1. Conclusion: We present a landscape of SE and their associated genes in mCPRC, and discuss the potential clinical implications of these findings in terms of their translation to the clinic.

Supplementary Figure and Table Legends. List of supporting information

Supplementary Fig. S1-S9. Supplementary Fig. S1. miR-195 expression is significantly reduced in both human PCa cells and tissues; Supplementary Fig. S2. Kaplan-Meier analyses of biochemical recurrence (BCR)-free survival, non-metastatic BCR-free, survival overall survival and non-metastatic survival of prostate cancer (PCa) patients based on miR-195 expression in Taylor dataset; Supplementary Fig. S3. Knockdown of miR-195 expression enhances invasion, migration, but inhibits apoptosis of LNCaP and DU145 cells; Supplementary Fig. S4. The inhibition of miR-195 enhances tumor growth, angiogenesis and invasion in vivo; Supplementary Fig. S5. Top ten enriched KEGG pathways (A) and gene ontology (GO) biological processes (B) involved by differentially-expressed proteins induced by miR-195; Supplementary Fig. S6. The knockdown of RPS6KB1 could imitate the tumor suppressive effects of miR-195; Supplementary Fig. S7. The re-expression and knockdown of RPS6KB1 could respectively rescue and imitate the tumor suppressive effects of miR-195; Supplementary Fig. S8. Reverse correlation between miR-195 and RPS6KB1 expression in human PCa tissues; Supplementary Fig. S9. MMP-9, VEGF, BAD and E-cadherin function as downstream effectors of miR-195-RPS6KB1 axis.

Figure S5 showed that metformin can suppress OCR through inhibiting GPD2 expression.

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s12943-017-0615-x.

Supplementary Information showed the additional details, such as reagents and assay kit, list of antibodies, sequences, primers and abbreviation.

Supplementary Figure and Table Legends. List of supporting information

Figure S4 showed that the extracellular acidification rate assay in GPD1 overexpressing cells and the CCK8 assay and the oxygen consumption rate in GPD1 knock-down cells.

Table S1 showed the IC50 values for metformin in cells and GPD1 overexpression cells.