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Abstract Background N4-Acetylcytidine (ac4C), a highly conserved post-transcriptional mechanism, plays a pivotal role in RNA modification and tumor progression. However, the molecular mechanism by which ac4C modification mediates tumor immunosuppression remains elusive in triple-negative breast cancer (TNBC). Methods NAT10 expression was analyzed in TNBC samples in the level of mRNA and protein, and compared with the corresponding normal tissues. ac4C modification levels also measured in the TNBC samples. The effects of NAT10 on immune microenvironment and tumor metabolism were investigated. NAT10-mediated ac4C and its downstream regulatory mechanisms were determined in vitro and in vivo. The combination therapy of targeting NAT10 in TNBC was further explored. Results The results revealed that the loss of NAT10 inhibited TNBC development and promoted T cell activation. Mechanistically, NAT10 upregulated JunB expression by increasing ac4C modification levels on its mRNA. Moreover, JunB further up-regulated LDHA expression and facilitated glycolysis. By deeply digging, remodelin, a NAT10 inhibitor, elevated the surface expression of CTLA-4 on T cells. The combination of remodelin and CTLA-4 mAb can further activate T cells and inhibite tumor progression. Conclusion Taken together, our study demonstrated that the NAT10-ac4C-JunB-LDHA pathway increases glycolysis levels and creates an immunosuppressive tumor microenvironment (TME). Consequently, targeting this pathway may assist in the identification of novel therapeutic strategies to improve the efficacy of cancer immunotherapy.

Abstract Although programmed death-ligand 1 (PD-L1) inhibitors have achieved some therapeutic success in breast cancer, their efficacy is limited by low therapeutic response rates, which is closely related to the immune escape of breast cancer cells. Tissue differentiation inducing non-protein coding RNA (TINCR), a long non-coding RNA, as an oncogenic gene associated with the progression of various malignant tumors, including breast cancer; however, the role of TINCR in tumor immunity, especially in breast cancer, remains unclear. We confirmed that TINCR upregulated PD-L1 expression in vivo and in vitro, and promoted the progression of breast cancer. Next, we revealed that TINCR knockdown can significantly improve the therapeutic effect of PD-L1 inhibitors in breast cancer in vivo. Mechanistically, TINCR recruits DNMT1 to promote the methylation of miR-199a-5p loci and inhibit its transcription. Furthermore, in the cytoplasm, TINCR potentially acts as a molecular sponge of miR-199a-5p and upregulates the stability of USP20 mRNA through a competing endogenous RNA (ceRNA) regulatory mechanism, thus promoting PD-L1 expression by decreasing its ubiquitination level. IFN-γ stimulation activates STAT1 by phosphorylation, which migrates into the nucleus to promote TINCR transcription. This is the first study to describe the regulatory role of TINCR in breast cancer tumor immunity, broadening the current paradigm of the functional diversity of TINCR in tumor biology. In addition, our study provides new research directions and potential therapeutic targets for PD-L1 inhibitors in breast cancer.

Background and ObjectiveSentinel lymph node biopsy (SLNB) is used to assess the status of axillary lymph node (ALN), but it causes many adverse reactions. Considering the low rate of sentinel lymph node (SLN) metastasis in T1 breast cancer, this study aims to identify the characteristics of T1 breast cancer without SLN metastasis and to select T1 breast cancer patients who avoid SLNB through constructing a nomogram.MethodsA total of 1,619 T1 breast cancer patients with SLNB in our hospital were enrolled in this study. Through univariate and multivariate logistic regression analysis, we analyzed the tumor anatomical and clinicopathological factors and constructed the Heilongjiang Medical University (HMU) nomogram. We selected the patients exempt from SLNB by using the nomogram.ResultsIn the training cohort of 1,000 cases, the SLN metastasis rate was 23.8%. Tumor volume, swollen axillary lymph nodes, pathological types, and molecular subtypes were found to be independent predictors for SLN metastasis in multivariate regression analysis. Distance from nipple or surface and position of tumor have no effect on SLN metastasis. A regression model based on the results of the multivariate analysis was developed to predict the risk of SLN metastasis, indicating an AUC of 0.798. It showed excellent diagnostic performance (AUC = 0.773) in the validation cohort.ConclusionThe HMU nomogram for predicting SLN metastasis incorporates four variables, including tumor volume, swollen axillary lymph nodes, pathological types, and molecular subtypes. The SLN metastasis rates of intraductal carcinoma and HER2 enriched are 2.05% and 6.67%. These patients could be included in trials investigating the SLNB exemption.

Breast cancer (BRCA) is one of the leading causes of death among women worldwide, and drug resistance often leads to a poor prognosis. Necroptosis is a type of programmed cell death (PCD) and exhibits regulatory effects on tumor progression, but few studies have focused on the relationships between necroptosis-associated lncRNAs and BRCA. In this study, we established a signature basis of 7 necroptosis-related lncRNAs associated with prognosis and divided BRCA patients into high- and low-risk groups. Kaplan-Meier curves all showed an adverse prognosis for patients in the high-risk group. Cox assays confirmed that risk score was an independent prognostic factor for BRCA patients. The receiver operating characteristic (ROC) curve proved the predictive accuracy of the signature and the area under the curve (AUC) values of the risk score reached 0.722. The nomogram relatively accurately predicted the prognosis of the patients. GSEA analysis suggested that the related signaling pathways and biological processes enriched in the high- and low-risk groups may influence the tumor microenvironment (TME) of BRCA. ssGSEA showed the difference in immune cell infiltration, immune pathway activation, and immune checkpoint expression between the two risk groups, with the low-risk group more suitable for immunotherapy. According to the significant difference in IC50 between risk groups, patients can be guided for an individualized treatment plan. Overall, the authors established a prognostic signature consisting of 7 necroptosis-associated lncRNAs that can independently predict the clinical outcome of BRCA patients. The difference in the tumor immune microenvironment between the low- and high-risk populations may be the reason for the resistance to immunotherapy in some patients.

Abstract Server workload in the form of cloud-end clusters is a key factor in server maintenance and task scheduling. How to balance and optimize hardware resources and computation resources should thus receive more attention. However, we have observed that the disordered execution of running application and batching seriously cuts down the efficiency of the server. To improve the workload prediction accuracy, this paper proposes an approach using the long short-term memory (LSTM) encoder-decoder network with attention mechanism. First, the approach extracts the sequential and contextual features of the historical workload data through the encoder network. Second, the model integrates the attention mechanism into the decoder network, through which the prediction for batch workloads can be carried out. Third, experiments carried out on Alibaba and Dinda workload traces dataset demonstrate that our method achieves state-of-the-art performance in mixed workload prediction in cloud computing environment. Furthermore, we also propose a scroll prediction method, which splits a long prediction sequence into several small sequences to monitor and control prediction accuracy. This work helps to dynamically guide the configuration for workload balancing.

The dysregulation of transfer RNA (tRNA) expression contributes to the diversity of proteomics, heterogeneity of cell populations, and instability of the genome, which may be related to human cancer susceptibility. However, the relationship between tRNA dysregulation and cancer susceptibility remains elusive because the landscape of cancer-associated tRNAs has not been portrayed yet. Furthermore, the molecular mechanisms of tRNAs involved in tumorigenesis and cancer progression have not been systematically understood. In this review, we detail current knowledge of cancer-related tRNAs and comprehensively summarize the basic characteristics and functions of these tRNAs, with a special focus on their role and involvement in human cancer. This review bridges the gap between tRNAs and cancer and broadens our understanding of their relationship, thus providing new insights and strategies to improve the potential clinical applications of tRNAs for cancer diagnosis and therapy.