YY1 mediated DCUN1D5 transcriptional activation promotes triple-negative breast cancer progression by targeting FN1/PI3K/AKT pathway.

Triple-negative breast cancer (TNBC) is more aggressive and has a higher metastasis rate compared with other subtypes of breast cancer. Due to the lack of drug-targetable receptors, chemotherapy is now the only available systemic treatment for TNBC. However, some patients might still develop drug resistance and have poor prognosis. Therefore, novel molecular biomarkers and new treatment targets are urgently needed for patients with TNBC. To provide molecular insights into TNBC progression, we investigated the function and the underlying mechanism of Defective in cullin neddylation 1 domain containing 5 (DCUN1D5) in the regulation of TNBC. By TCGA dataset and surgical specimens with immunohistochemical (IHC) staining method, DCUN1D5 was identified to be significantly upregulated in TNBC tumor tissues and negatively associated with prognosis. A series of in vitro and in vivo experiments were performed to confirm the oncogenic role of DCUN1D5 in TNBC. Overexpression of FN1 or PI3K/AKT activator IGF-1 could restore the proliferative and invasive ability induced by DCUN1D5 knockdown and DCUN1D5 could act as a novel transcriptional target of transcription factor Yin Yang 1 (YY1). In conclusion, YY1-enhanced DCUN1D5 expression could promote TNBC progression by FN1/PI3K/AKT pathway and DCUN1D5 might be a potential prognostic biomarker and therapeutic target for TNBC treatment.

Ultrasound-based radiomics-clinical nomogram for noninvasive prediction of residual cancer burden grading in breast cancer.

PURPOSE: To assess the predictive value of an ultrasound-based radiomics-clinical nomogram for grading residual cancer burden (RCB) in breast cancer patients. METHODS: This retrospective study of breast cancer patients who underwent neoadjuvant therapy (NAC) and ultrasound scanning between November 2020 and July 2023. First, a radiomics model was established based on ultrasound images. Subsequently, multivariate LR (logistic regression) analysis incorporating both radiomic scores and clinical factors was performed to construct a nomogram. Finally, Receiver operating characteristics (ROC) curve analysis and decision curve analysis (DCA) were employed to evaluate and validate the diagnostic accuracy and effectiveness of the nomogram. RESULTS: A total of 1122 patients were included in this study. Among them, 427 patients exhibited a favorable response to NAC chemotherapy, while 695 patients demonstrated a poor response to NAC therapy. The radiomics model achieved an AUC value of 0.84 in the training cohort and 0.83 in the validation cohort. The ultrasound-based radiomics-clinical nomogram achieved an AUC value of 0.90 in the training cohort and 0.91 in the validation cohort. CONCLUSIONS: Ultrasound-based radiomics-clinical nomogram can accurately predict the effectiveness of NAC therapy by predicting RCB grading in breast cancer patients.

LncRNA-LINC00472 suppresses the malignant progression of non-small cell lung cancer via modulation of the miRNA-1275/Homeobox A2 axis.

BACKGROUND: Long non-coding RNAs (lncRNAs) are increasingly observed as regulatory factors for the initiation and progression of varying kinds of cancers. However, studies on lncRNAs in non-small cell lung cancer (NSCLC) progression are currently lacking. OBJECTIVES: We intended to determine the role of lncRNA LINC00472 and its downstream regulatory mechanism in NSCLC, thus providing novel ideas for targeted therapies for NSCLC. MATERIAL AND METHODS: The target signaling axis comprising the lncRNA/microRNA/mRNA was identified through bioinformatics analysis. Subcellular localization of LINC00472 was assessed with fluorescence in situ hybridization (FISH). Cellular function experiments were conducted to examine the proliferation, migration, invasion, and apoptosis of NSCLC cells, and dual-luciferase and RNA binding protein immunoprecipitation assays were performed to validate the binding relationship. Quantitative real-time polymerase chain reaction (qPCR) and western blot were utilized to assess the expression levels of the investigated gene and protein, respectively. RESULTS: The LINC00472 expression was markedly decreased in NSCLC tissues and cells. The FISH, combined with nuclear-cytoplasm separation assay, demonstrated that LINC00472 was mainly located in the cytoplasm. The overexpression of LINC00472 restrained proliferation and metastasis of NSCLC in vitro. The LINC00472 could target and repress miR-1275 level, and overexpression of LINC00472 reduced the miR-1275-dependent malignant cell phenotype in NSCLC. Further study revealed that HOXA2 was a downstream target of miR-1275 and was negatively modulated by miR-1275. Rescue assays exhibited that the overexpression of miR-1275 or inhibition of HOXA2 reversed the impact of LINC00472 overexpression on the malignant progression of NSCLC cells. The LINC00472 repressed the epithelial-mesenchymal transition (EMT) of NSCLC cells through miR-1275/HOXA2. CONCLUSIONS: The LINC00472 functioned as a competing endogenous RNA to modulate HOXA2 level by sponging miR-1275 in NSCLC. Simultaneously, the LINC00472/miR-1275/HOXA2 axis may be a possible therapeutic target and biomarker for NSCLC.

Indocyanine green fluorescence imaging-guided versus conventional laparoscopic lymphadenectomy for gastric cancer: long-term outcomes of a phase 3 randomised clinical trial.

Indocyanine green (ICG) fluorescence imaging-guided lymphadenectomy has been demonstrated to be effective in increasing the number of lymph nodes (LNs) retrieved in laparoscopic gastrectomy for gastric cancer (GC). Previously, we reported the primary outcomes and short-term secondary outcomes of a phase 3, open-label, randomized clinical trial (NCT03050879) investigating the use of ICG for image-guided lymphadenectomy in patients with potentially resectable GC. Patients were randomly (1:1 ratio) assigned to either the ICG or non-ICG group. The primary outcome was the number of LNs retrieved and has been reported. Here, we report the primary outcome and long-term secondary outcomes including three-year overall survival (OS), three-year disease-free survival (DFS), and recurrence patterns. The per-protocol analysis set population is used for all analyses (258 patients, ICG [n = 129] vs. non-ICG group [n = 129]). The mean total LNs retrieved in the ICG group significantly exceeds that in the non-ICG group (50.5 ± 15.9 vs 42.0 ± 10.3, P < 0.001). Both OS and DFS in the ICG group are significantly better than that in the non-ICG group (log-rank P = 0.015; log-rank P = 0.012, respectively). There is a difference in the overall recurrence rates between the ICG and non-ICG groups (17.8% vs 31.0%). Compared with conventional lymphadenectomy, ICG guided laparoscopic lymphadenectomy is safe and effective in prolonging survival among patients with resectable GC.

Loss of ATOH1 in Pit Cell Drives Stemness and Progression of Gastric Adenocarcinoma by Activating AKT/mTOR Signaling through GAS1.

Gastric cancer stem cells (GCSCs) are self-renewing tumor cells that govern chemoresistance in gastric adenocarcinoma (GAC), whereas their regulatory mechanisms remain elusive. Here, the study aims to elucidate the role of ATOH1 in the maintenance of GCSCs. The preclinical model and GAC sample analysis indicate that ATOH1 deficiency is correlated with poor GAC prognosis and chemoresistance. ScRNA-seq reveals that ATOH1 is downregulated in the pit cells of GAC compared with those in paracarcinoma samples. Lineage tracing reveals that Atoh1 deletion strongly confers pit cell stemness. ATOH1 depletion significantly accelerates cancer stemness and chemoresistance in Tff1-CreERT2; Rosa26Tdtomato and Tff1-CreERT2; Apcfl/fl ; p53fl/fl (TcPP) mouse models and organoids. ATOH1 deficiency downregulates growth arrest-specific protein 1 (GAS1) by suppressing GAS1 promoter transcription. GAS1 forms a complex with RET, which inhibits Tyr1062 phosphorylation, and consequently activates the RET/AKT/mTOR signaling pathway by ATOH1 deficiency. Combining chemotherapy with drugs targeting AKT/mTOR signaling can overcome ATOH1 deficiency-induced chemoresistance. Moreover, it is confirmed that abnormal DNA hypermethylation induces ATOH1 deficiency. Taken together, the results demonstrate that ATOH1 loss promotes cancer stemness through the ATOH1/GAS1/RET/AKT/mTOR signaling pathway in GAC, thus providing a potential therapeutic strategy for AKT/mTOR inhibitors in GAC patients with ATOH1 deficiency.

Global patterns of taxonomic and phylogenetic diversity of flowering plants: Biodiversity hotspots and coldspots.

Species diversity of angiosperms (flowering plants) varies greatly among regions. Geographic patterns of variation in species diversity are shaped by the interplay of ecological and evolutionary processes. Here, using a comprehensive data set for regional angiosperm floras across the world, we show geographic patterns of taxonomic (species) diversity, phylogenetic diversity, phylogenetic dispersion, and phylogenetic deviation (i.e., phylogenetic diversity after accounting for taxonomic diversity) across the world. Phylogenetic diversity is strongly and positively correlated with taxonomic diversity; as a result, geographic patterns of taxonomic and phylogenetic diversity across the world are highly similar. Areas with high taxonomic and phylogenetic diversity are located in tropical regions whereas areas with low taxonomic and phylogenetic diversity are located in temperate regions, particularly in Eurasia and North America, and in northern Africa. Similarly, phylogenetic dispersion is, in general, higher in tropical regions and lower in temperate regions. However, the geographic pattern of phylogenetic deviation differs substantially from those of taxonomic and phylogenetic diversity and phylogenetic dispersion. As a result, hotspots and coldspots of angiosperm diversity identified based on taxonomic and phylogenetic diversity and phylogenetic dispersion are incongruent with those identified based on phylogenetic deviations. Each of these metrics may be considered when selecting areas to be protected for their biodiversity.

Construction of lung cancer serum markers based on ReliefF feature selection.

Serum miRNAs are available clinical samples for cancer screening. Identifying early serum markers in lung cancer (LC) is essential for patients' early diagnosis and clinical treatment. Expression data of serum miRNAs of lung adenocarcinoma (LUAD) patients and healthy individuals were downloaded from the Gene Expression Omnibus (GEO). These data were normalized and subjected to differential expression analysis to obtain differentially expressed miRNAs (DEmiRNAs). The DEmiRNAs were subsequently subjected to ReliefF feature selection, and subsets closely related to cancer were screened as candidate feature miRNAs. Thereafter, a Gaussian Naive Bayes (NB), Support Vector Machine (SVM), and Random Forest (RF) classifier were constructed based on these candidate feature miRNAs. Then the best diagnostic signature was constructed through NB combined with incremental feature selection (IFS). Thereafter, these samples were subjected to principal component analysis (PCA) based on miRNAs with optimal predictive performance. Finally, the peripheral serum miRNAs of 64 LUAD patients and 59 normal individuals were extracted for qRT-PCR analysis to validate the performance of the diagnostic model in respect of clinical detection. Finally, according to area under the curve (AUC) and accuracy values, the NB classifier composed of miR-5100 and miR-663a manifested the most outstanding diagnostic performance. The PCA results also revealed that the 2-miRNA diagnostic signature could effectively distinguish cancer patients from healthy individuals. Finally, qRT-PCR results of clinical serum samples revealed that miR-5100 and miR-663a expression in tumor samples was remarkably higher than that in normal samples. The AUC of the 2-miRNA diagnostic signature was 0.968. In summary, we identified markers (miR-5100 and miR-663a) in serum for early LUAD screening, providing ideas for developing early LUAD diagnostic models.

Comprehensive proteome, phosphoproteome and kinome characterization of luminal A breast cancer.

Background: Breast cancer is one of the most frequently occurring malignant cancers worldwide. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two most common histological subtypes of breast cancer. In this study, we aimed to deeply explore molecular characteristics and the relationship between IDC and ILC subtypes in luminal A subgroup of breast cancer using comprehensive proteomics and phosphoproteomics analysis. Methods: Cancer tissues and noncancerous adjacent tissues (NATs) with the luminal A subtype (ER- and PR-positive, HER2-negative) were obtained from paired IDC and ILC patients respectively. Label-free quantitative proteomics and phosphoproteomics methods were used to detect differential proteins and the phosphorylation status between 10 paired breast cancer and NATs. Then, the difference in protein expression and its phosphorylation between IDC and ILC subtypes were explored. Meanwhile, the activation of kinases and their substrates was also revealed by Kinase-Substrate Enrichment Analysis (KSEA). Results: In the luminal A breast cancer, a total of 5,044 high-confidence proteins and 3,808 phosphoproteins were identified from 10 paired tissues. The protein phosphorylation level in ILC tissues was higher than that in IDC tissues. Histone H1.10 was significantly increased in IDC but decreased in ILC, Conversely, complement C4-B and Crk-like protein were significantly decreased in IDC but increased in ILC. Moreover, the increased protein expression of Septin-2, Septin-9, Heterogeneous nuclear ribonucleoprotein A1 and Kinectin but reduce of their phosphorylation could clearly distinguish IDC from ILC. In addition, IDC was primarily related to energy metabolism and MAPK pathway, while ILC was more closely involved in the AMPK and p53/p21 pathways. Furthermore, the kinomes in IDC were primarily significantly activated in the CMGC groups. Conclusions: Our research provides insights into the molecular characterization of IDC and ILC and contributes to discovering novel targets for further drug development and targeted treatment.

SNHG15 enhances cisplatin resistance in lung adenocarcinoma by affecting the DNA repair capacity of cancer cells.

BACKGROUND: Lung adenocarcinoma (LUAD) is a prevalent malignancy. SNHG15 has been demonstrated to be oncogenic in many kinds of cancers, however the mechanism of SNHG15 in LUAD cisplatin (DDP) resistance remains unclear. In this study, we demonstrated the effect of SNHG15 on DDP resistance in LUAD and its related mechanism. METHODS: Bioinformatics analysis was adopted to assess SNHG15 expression in LUAD tissues and predict the downstream genes of SNHG15. The binding relationship between SNHG15 and downstream regulatory genes was proved through RNA immunoprecipitation, chromatin immunoprecipitation and dual-luciferase reporter assays. Cell counting kit-8 assay was adopted to evaluate LUAD cell viability, and gene expression was determined by Western blot and quantitative real-time polymerase chain reaction. We then performed comet assay to assess DNA damage. Cell apoptosis was detected by Tunnel assay. Xenograft animal models were created to test the function of SNHG15 in vivo. RESULTS: SNHG15 was up-regulated in LUAD cells. Moreover, SNHG15 was also highly expressed in drug-resistant LUAD cells. Down-regulated SNHG15 strengthened the sensitivity of LUAD cells to DDP and induced DNA damage. SNHG15 could elevate ECE2 expression through binding with E2F1, and it could induce DDP resistance by modulating the E2F1/ECE2 axis. In vivo experiments verified that the SNHG15 could enhance DDP resistance in LUAD tissue. CONCLUSION: The results suggested that SNHG15 could up-regulate ECE2 expression by recruiting E2F1, thereby enhancing the DDP resistance of LUAD.

Global patterns and climatic determinants of phylogenetic structure of regional fern floras.

Knowledge of relationships between phylogenetic structure of a biological assemblage and ecological factors that drive the variation of phylogenetic structure among regions is crucial for understanding the causes of variation in taxonomic composition and richness among regions, but this knowledge is lacking for the global flora of ferns. Here, we fill this critical knowledge gap. We divided the globe into 392 geographic units on land, collated species lists of ferns for each geographic unit, and used different phylogenetic metrics (tip- vs basal-weighted) reflecting different evolutionary depths to quantify phylogenetic structure. We then related taxonomic and phylogenetic structure metrics to six climatic variables for ferns as a whole and for two groups of ferns (old clades vs polypods) reflecting different evolutionary histories across the globe and within each continental region. We found that when old clades and polypods were considered separately, temperature-related variables explained more variation in these metrics than did precipitation-related variables in both groups. When analyses were conducted for continental regions separately, this pattern holds in most cases. Climate extremes have a stronger relationship with phylogenetic structure of ferns than does climate seasonality. Climatic variables explained more variation in phylogenetic structure at deeper evolutionary depths.

Identification and validation of a hypoxia-immune signature for overall survival prediction in lung adenocarcinoma.

Objective: The interaction between immunity and hypoxia in tumor microenvironment (TME) has clinical significance, and this study aims to explore immune-hypoxia related biomarkers in LUAD to guide accurate prognosis of patients. Methods: The LUAD gene expression dataset was downloaded from GEO and TCGA databases. The immune-related genes and hypoxia-related genes were acquired from ImmPort and MSigDB databases, respectively. Genes related to immune and hypoxia in LUAD were obtained by intersection. The significantly prognostic genes in LUAD were obtained by LASSO and Cox regression analyses and a prognostic model was constructed. Kaplan-Meier and receiver operating characteristic curves were generated to evaluate and validate model reliability. Single-sample gene set enrichment analysis (ssGSEA) and gene set variation analysis (GSVA) were employed to analyze immune cell infiltration and pathway differences between high- and low-risk groups. Nomogram and calibration curves for survival curve and clinical features were drawn to measure prognostic value of the model. Results: The prognosis model of LUAD was constructed based on seven immune-hypoxia related genes: S100P, S100A16, PGK1, TNFSF11, ARRB1, NCR3, and TSLP. Survival analysis revealed a poor prognosis in high-risk group. ssGSEA result suggested that activities of immune cells in high-risk group was remarkably lower than in low-risk group, and GSVA result showed that immune-related pathway was notably activated in low-risk group. Conclusion: Immune-hypoxia related genes were found to be prognostic biomarkers for LUAD patients, based on which a 7-immune-hypoxia related gene-signature was constructed. This model can assess immune status of LUAD patients, and provide clinical reference for individualized prognosis, treatment and follow-up of LUAD patients.

Identification of LARS as an essential gene for osteosarcoma proliferation through large-Scale CRISPR-Cas9 screening database and experimental verification.

BACKGROUND: Osteosarcoma is one of the most malignant tumors, and it occurs mostly in children and adolescents. Currently, surgery and chemotherapy are the main treatments. The recurrence rate is high and the prognosis is often poor. Finding an effective target gene therapy for osteosarcoma may effectively improve its prognosis. METHOD: In this study, genes essential for the survival of osteosarcoma cells were identified by genome-wide screening of CRISPR-Cas9 based on the DepMap database. The expression of these essential genes in osteosarcoma patients' tissues and normal tissues was identified in the GSE19276 database. Functional pathway enrichment analysis, protein interaction network construction, and LASSO were performed to construct a prognostic risk model based on these essential genes. CCK8 assay was used to detect the effect of essential gene-LARS (Leucyl-TRNA Synthetase 1) on the proliferation of osteosarcoma. RESULTS: In this study, 785 genes critical for osteosarcoma cell proliferation were identified from the DepMap. Among these 785 essential genes, 59 DEGs were identified in osteosarcoma tissues. In the functional enrichment analysis, these 59 essential genes were mainly enriched in cell cycle-related signaling pathways. Furthermore, we established a risk score module, including LARS and DNAJC17, screened from these 59 genes, and this module could divide osteosarcoma patients into the low-risk and high-risk groups. In addition, knockdown of LARS expression inhibited the proliferative ability of osteosarcoma cells. A significant correlation was found between LARS expression and Monocytic lineage, T cells, and Fibroblasts. CONCLUSION: In conclusion, LARS was identified as an essential gene for survival in osteosarcoma based on the DepMap database. Knockdown of LARS expression significantly inhibited the proliferation of osteosarcoma cells, suggesting that it is involved in the formation and development of osteosarcoma. The results are useful as a foundation for further studies to elucidate a potential osteosarcoma diagnostic index and therapeutic targets.

Machine Learning Models for the Diagnosis and Prognosis Prediction of High-Grade B-Cell Lymphoma.

High-grade B-cell lymphoma (HGBL) is a newly introduced category of rare and heterogeneous invasive B-cell lymphoma (BCL), which is diagnosed depending on fluorescence in situ hybridization (FISH), an expensive and laborious analysis. In order to identify HGBL with minimal workup and costs, a total of 187 newly diagnosed BCL patients were enrolled in a cohort study. As a result, the overall survival (OS) and progression-free survival (PFS) of the HGBL group were inferior to those of the non-HGBL group. HGBL (n = 35) was more likely to have a high-grade histomorphology appearance, extranodal involvement, bone marrow involvement, and whole-body maximum standardized uptake (SUVmax). The machine learning classification models indicated that histomorphology appearance, Ann Arbor stage, lactate dehydrogenase (LDH), and International Prognostic Index (IPI) risk group were independent risk factors for diagnosing HGBL. Patients in the high IPI risk group, who are CD10 positive, and who have extranodal involvement, high LDH, high white blood cell (WBC), bone marrow involvement, old age, advanced Ann Arbor stage, and high SUVmax had a higher risk of death within 1 year. In addition, these models prompt the clinical features with which the patients should be recommended to undergo a FISH test. Furthermore, this study supports that first-line treatment with R-CHOP has dismal efficacy in HGBL. A novel induction therapeutic regimen is still urgently needed to ameliorate the poor outcome of HGBL patients.

Global patterns of fern species diversity: An evaluation of fern data in GBIF.

Despite that several studies have shown that data derived from species lists generated from distribution occurrence records in the Global Biodiversity Information Facility (GBIF) are not appropriate for those ecological and biogeographic studies that require high sampling completeness, because species lists derived from GBIF are generally very incomplete, Suissa et al. (2021) generated fern species lists based on data with GBIF for 100 km × 100 km grid cells across the world, and used the data to determine fern diversity hotspots and species richness-climate relationships. We conduct an evaluation on the completeness of fern species lists derived from GBIF at the grid-cell scale and at a larger spatial scale, and determine whether fern data derived from GBIF are appropriate for studies on the relations of species composition and richness with climatic variables. We show that species sampling completeness of GBIF is low (<40%) for most of the grid cells examined, and such low sampling completeness can substantially bias the investigation of geographic and ecological patterns of species diversity and the identification of diversity hotspots. We conclude that fern species lists derived from GBIF are generally very incomplete across a wide range of spatial scales, and are not appropriate for studies that require data derived from species lists in high completeness. We present a map showing global patterns of fern species diversity based on complete or nearly complete regional fern species lists.

YTHDF3 facilitates triple-negative breast cancer progression and metastasis by stabilizing ZEB1 mRNA in an m6A-dependent manner.

Background: The YTH domain family protein 3 (YTHDF3) is an important N6-methyladenosine (m6A) reader which is involved in multiple cancers. However, the biological role and mechanisms of action for YTHDF3 in triple-negative breast cancer (TNBC) remains to be elucidated. Methods: The expression of YTHDF3 in TNBC tissues was evaluated using The Cancer Genome Atlas (TCGA) database, BC-GenExMiner, and immunohistochemistry (IHC) staining. Cell migration, invasion, and epithelial-mesenchymal transition (EMT) were validated by wound healing assays, transwell assays, and Western blot (WB) analyses. The association between YTHDF3 and zinc finger E-box-binding homeobox 1 (ZEB1) was confirmed by Pearson correlation analysis. RNA-binding protein immunoprecipitation (RIP) assays and mRNA actinomycin stability analyses were applied to confirm whether YTHDF3 could interact with ZEB1in an m6A-dependent manner. Results: The expression of YTHDF3 was correlated with poorer disease-free survival (DFS) and overall survival (OS) in TNBC patients. Functional experiments indicated that YTHDF3 positively regulated cell migration, invasion, and EMT in TNBC cells. Moreover, ZEB1 was identified as a key downstream target for YTHDF3 and YTHDF3 could enhance ZEB1 mRNA stability in an m6A-dependent manner. Inhibition of YTHDF3 reduced migration, invasion, and EMT, all of which were reversed by rescue experiments overexpressing ZEB1. Conclusions: The findings herein confirmed that the YTHDF3/ZEB1 axis plays an important role in the progression and metastasis of TNBC. YTHDF3 is a promising prognosis biomarker and potential therapeutic target for patients with TNBC.

CTPS1 promotes malignant progression of triple-negative breast cancer with transcriptional activation by YBX1.

BACKGROUND: Cytidine nucleotide triphosphate synthase 1 (CTPS1) is a CTP synthase which play critical roles in DNA synthesis. However, its biological regulation and mechanism in triple-negative breast cancer (TNBC) has not been reported yet. METHODS: The expression of CTPS1 in TNBC tissues was determined by GEO, TCGA databases and immunohistochemistry (IHC). The effect of CTPS1 on TNBC cell proliferation, migration, invasion, apoptosis and tumorigenesis were explored in vivo and in vitro. In addition, the transcription factor Y-box binding protein 1 (YBX1) was identified by bioinformatics methods, dual luciferase reporter and chromatin immunoprecipitation (CHIP) assays. Pearson correlation analysis was utilized to assess the association between YBX1 and CTPS1 expression. RESULTS: CTPS1 expression was significantly upregulated in TNBC tissues and cell lines. Higher CTPS1 expression was correlated with a poorer disease-free survival (DFS) and overall survival (OS) in TNBC patients. Silencing of CTPS1 dramatically inhibited the proliferation, migration, invasion ability and induced apoptosis of MDA-MB-231 and HCC1937 cells. Xenograft tumor model also indicated that CTPS1 knockdown remarkably reduced tumor growth in mice. Mechanically, YBX1 could bind to the promoter of CTPS1 to promote its transcription. Furthermore, the expression of YBX1 was positively correlated with CTPS1 in TNBC tissues. Rescue experiments confirmed that the enhanced cell proliferation and invasion ability induced by YBX1 overexpression could be reversed by CTPS1 knockdown. CONCLUSION: Our data demonstrate that YBX1/CTPS1 axis plays an important role in the progression of TNBC. CTPS1 might be a promising prognosis biomarker and potential therapeutic target for patients with triple-negative breast cancer.

The Expression and Prognostic Value of SUMO1-Activating Enzyme Subunit 1 and Its Potential Mechanism in Triple-Negative Breast Cancer.

Background: Triple-negative breast cancer (TNBC) is the most invasive and metastatic subtype of breast cancer. SUMO1-activating enzyme subunit 1 (SAE1), an E1-activating enzyme, is indispensable for protein SUMOylation. SAE1 has been found to be a relevant biomarker for progression and prognosis in several tumor types. However, the role of SAE1 in TNBC remains to be elucidated. Methods: In the research, the mRNA expression of SAE1 was analyzed via the cancer genome atlas (TCGA) and gene expression omnibus (GEO) database. Cistrome DB Toolkit was used to predict which transcription factors (TFs) are most likely to increase SAE1 expression in TNBC. The correlation between the expression of SAE1 and the methylation of SAE1 or quantity of tumor-infiltrating immune cells was further invested. Single-cell analysis, using CancerSEA, was performed to query which functional states are associated with SAE1 in different cancers in breast cancer at the single-cell level. Next, weighted gene coexpression network (WGCNA) was applied to reveal the highly correlated genes and coexpression networks of SAE1 in TNBC patients, and a prognostic model containing SAE1 and correlated genes was constructed. Finally, we also examined SAE1 protein expression of 207 TNBC tissues using immunohistochemical (IHC) staining. Results: The mRNA and protein expression of SAE1 were increased in TNBC tissues compared with adjacent normal tissues, and the protein expression of SAE1 was significantly associated with overall survival (OS) and disease-free survival (DFS). Correlation analyses revealed that SAE1 expression was positively correlated with forkhead box M1 (FOXM1) TFs and negatively correlated with SAE1 methylation site (cg14042711) level. WGCNA indicated that the genes coexpressed with SAE1 belonged to the green module containing 1,176 genes. Through pathway enrichment analysis of the module, 1,176 genes were found enriched in cell cycle and DNA repair. Single-cell analysis indicated that SAE1 and its coexpression genes were associated with cell cycle, DNA damage, DNA repair, and cell proliferation. Using the LASSO COX regression, a prognostic model including SAE1 and polo-like kinase 1 (PLK1) was built to accurately predict the likelihood of DFS in TNBC patients. Conclusion: In conclusion, we comprehensively analyzed the mRNA and protein expression, prognosis, and interaction genes of SAE1 in TNBC and constructed a prognostic model including SAE1 and PLK1. These results might be important for better understanding of the role of SAE1 in TNBC. In addition, DNA methyltransferase and TFs inhibitor treatments targeting SAE1 might improve the survival of TNBC patients.

An immunohistochemical panel of three small ubiquitin-like modifier genes predicts outcomes of patients with triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is a highly heterogeneous and aggressive disease. Developing new candidate biomarkers for chemotherapy response and possible therapeutic targets has become an urgent clinical need. Small ubiquitin-like modifiers (SUMOs) mediate post-translational modifications (SUMOylation) has been shown to be involved in numerous biological processes. However, the role of SUMOylation in TNBC has yet to be elucidated. METHOD: The mRNA expression of SUMO1/2/3 was analyzed by the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO) databases (N=412). We also evaluated the SUMO1/2/3 protein expression in 212 TNBC patients using immunohistochemical (IHC) staining method. A classifier with Least absolute shrinkage and selection operator (LASSO) Cox regression model was then built based on the associations between the expression of SUMO1/2/3 proteins and the disease-free survival (DFS) of TNBC patients. RESULTS: Elevated SUMO1/2/3 levels were indicated to be associated with a poorer overall survival (OS) and DFS for TNBC patients. With the LASSO model, we built a classifier based on the IHC scores of SUMO1/2/3 proteins and named it the 'SB classifier'. Patients with SB classifier-defined high score were found to have an unfavorable response to chemotherapy [hazard ratio (HR) 4.04, 95% confidence interval (CI): 2.14-7.63; P<0.0001]. A nomogram was then developed to identify which patients might benefit from chemotherapy. Finally, our results also suggested that the activation of SUMOylation pathway in TNBC might be induced by MYC signaling. CONCLUSIONS: We constructed a reliable prognostic and predictive tool for TNBC patients treated with chemotherapy, which could facilitate individualized counseling and management.

Quantitative proteomics reveals stage-specific protein regulation of triple negative breast cancer.

BACKGROUNDS: Triple negative breast cancer (TNBC) is a heterogeneous disease with more aggressive clinical courses than other subtypes of breast cancer. In this study, we performed high-resolution mass spectrometry-based quantitative proteomics with TNBC clinical tissue specimens to explore the early and sensitive diagnostic signatures and potential therapeutic targets for TNBC patients. METHODS: We performed an iTRAQ labeling coupled LC-MS/MS approach to explore the global proteome in tumor tissues and corresponding para-tumor tissues from 24 patients with grade I-II and grade III primary TNBC. Relative peptide quantification and protein identification were performed by Proteome Discoverer™ software with Mascot search engine. Differentially expressed proteins were analyzed by bioinformatic analyses, including GO function classification annotation and KEGG enrichment analysis. Pathway analyses for protein-protein interactions and upstream regulations of differentially expressed candidates were performed by Ingenuity Pathway Analysis (IPA) software. RESULTS: Totally, 5401 unique proteins were identified and quantified in different stage of TNBCs. 845 proteins were changed in patients with grade I or II TNBC, among which 304 were up-regulated and 541 were down-regulated. Meanwhile, for patients with grade III TNBC, 358 proteins were increased and 651 proteins were decreased. Comparing to para-cancerous tissues, various signaling pathways and metabolic processes, including PPAR pathways, PI3K-Akt pathway, one-carbon metabolism, amino acid synthesis, and lipid metabolism were activated in TNBC cancer tissues. Death receptor signaling was significantly activated in grade I-II TNBCs, however, remarkably inhibited in grade III TNBCs. Western blot experiments were conducted to validate expression levels of CYCS, HMGA1 and XIAP with samples from individual patients. CONCLUSIONS: Overall, our proteomic data presented precise quantification of potential signatures, signaling pathways, regulatory networks, and characteristic differences in each clinicopathological subgroup. The proteome provides complementary information for TNBC accurate subtype classification and therapeutic targets research.