Elongin B promotes breast cancer progression by ubiquitinating tumor suppressor p14/ARF.

Elongin B (ELOB), a pivotal element in the ELOB/c-Cullin2/5-SOCS-box E3 ubiquitin-protein ligase complex, plays a significant role in catalyzing the ubiquitination and subsequent degradation of a broad spectrum of target proteins. Notably, it is documented to facilitate these processes. However, the regulatory role of ELOB in breast cancer remains ambiguous. In this study, through bio-informatic analysis of The Cancer Genome Atlas and Fudan University Shanghai Cancer Center database, we demonstrated that ELOB was over-expressed in breast cancer tissues and was related to unfavorable prognosis. Additionally, pathway enrichment analysis illustrated that high expression of ELOB was associated with multiple cancer promoting pathways, like cell cycle, DNA replication, proteasome and PI3K - Akt signaling pathway, indicating ELOB as a potential anticancer target. Then, we confirmed that both in vivo and in vitro, the proliferation of breast cancer cells could be significantly suppressed by the down-regulation of ELOB. Mechanically, immunoprecipitation and in vivo ubiquitination assays prompted that, as the core element of Cullin2-RBX1-ELOB E3 ligase (CRL2) complex, ELOB regulated the ubiquitination and the subsequent degradation of oncoprotein p14/ARF. Moreover, the anticancer efficacy of erasing ELOB could be rescued by simultaneous knockdown of p14/ARF. Finally, through analyzing breast cancer tissue microarrays and western blot of patient samples, we demonstrated that the expression of ELOB in tumor tissues was elevated in compared to adjacent normal tissues. In conclusion, ELOB is identified to be a promising innovative target for the drug development of breast cancer by promoting the ubiquitination and degradation of oncoprotein p14/ARF.

Optimising first-line subtyping-based therapy in triple-negative breast cancer (FUTURE-SUPER): a multi-cohort, randomised, phase 2 trial.

BACKGROUND: Triple-negative breast cancers display heterogeneity in molecular drivers and immune traits. We previously classified triple-negative breast cancers into four subtypes: luminal androgen receptor (LAR), immunomodulatory, basal-like immune-suppressed (BLIS), and mesenchymal-like (MES). Here, we aimed to evaluate the efficacy and safety of subtyping-based therapy in the first-line treatment of triple-negative breast cancer. METHODS: FUTURE-SUPER is an ongoing, open-label, randomised, controlled phase 2 trial being conducted at Fudan University Shanghai Cancer Center (FUSCC), Shanghai, China. Eligible participants were females aged 18-70 years, with an Eastern Cooperative Oncology Group performance status of 0-1, and histologically confirmed, untreated metastatic or recurrent triple-negative breast cancer. After categorising participants into five cohorts according to molecular subtype and genomic biomarkers, participants were randomly assigned (1:1) with a block size of 4, stratified by subtype, to receive, in 28-day cycles, nab-paclitaxel (100 mg/m2, intravenously on days 1, 8, and 15) alone (control group) or with a subtyping-based regimen (subtyping-based group): pyrotinib (400 mg orally daily) for the LAR-HER2mut subtype, everolimus (10 mg orally daily) for the LAR-PI3K/AKTmut and MES-PI3K/AKTmut subtypes, camrelizumab (200 mg intravenously on days 1 and 15) and famitinib (20 mg orally daily) for the immunomodulatory subtype, and bevacizumab (10 mg/kg intravenously on days 1 and 15) for the BLIS/MES-PI3K/AKTWT subtype. The primary endpoint was investigator-assessed progression-free survival for the pooled subtyping-based group versus the control group in the intention-to-treat population (all randomly assigned participants). Safety was analysed in all patients with safety records who received at least one dose of study drug. This study is registered with ClinicalTrials.gov (NCT04395989). FINDINGS: Between July 28, 2020, and Oct 16, 2022, 139 female participants were enrolled and randomly assigned to the subtyping-based group (n=69) or control group (n=70). At the data cutoff (May 31, 2023), the median follow-up was 22·5 months (IQR 15·2-29·0). Median progression-free survival was significantly longer in the pooled subtyping-based group (11·3 months [95% CI 8·6-15·2]) than in the control group (5·8 months [4·0-6·7]; hazard ratio 0·44 [95% CI 0·30-0·65]; p<0·0001). The most common grade 3-4 treatment-related adverse events were neutropenia (21 [30%] of 69 in the pooled subtyping-based group vs 16 [23%] of 70 in the control group), anaemia (five [7%] vs none), and increased alanine aminotransferase (four [6%] vs one [1%]). Treatment-related serious adverse events were reported for seven (10%) of 69 patients in the subtyping-based group and none in the control group. No treatment-related deaths were reported in either group. INTERPRETATION: These findings highlight the potential clinical benefits of using molecular subtype-based treatment optimisation in patients with triple-negative breast cancer, suggesting a path for further clinical investigation. Phase 3 randomised clinical trials assessing the efficacy of subtyping-based regimens are now underway. FUNDING: National Natural Science Foundation of China, Natural Science Foundation of Shanghai, Shanghai Hospital Development Center, and Jiangsu Hengrui Pharmaceuticals. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

A novel eight-gene Immune Cell-Associated Predictive Gene model to predict recurrence in triple-negative breast cancer.

Background: Tumour tissue contains not only tumour cells but also some stromal cells and immune cells. This is one composition of the immune microenvironment of the tumour and causes a significant effect on the prognostic factors and recurrence of malignant tumor. Methods: In this research, single-cell RNA data from triple-negative breast cancers (TNBCs) were comprehensively analyzed and 1,527 marker genes expressed in immune cells were identified. Subsequently, RNA sequencing and clinical data from 360 patients in the Triple Negative Breast Cancer database at the Fudan University Shanghai Cancer Center (FUSCC) were divided into two groups in a 1:1 ratio, the training group and the validation group. An eight-gene Immune Cell-Associated Predictive Gene (ICAPG) model for predicting breast cancer (BC) recurrence was developed using mRNA data from the training group combined with immune cell marker genes. Based on this model, subjects were divided into two different risk level groups. The predictive power of the model was fully validated using the validation group and The Cancer Genome Atlas (TCGA) database. The localization and expression of these eight genes were then confirmed in a single-cell database. ssGSEA and CIBERSORT algorithms were used to characterize the differences in immune cell infiltration between the two different risk groups. Results: The eight-gene ICAPG model was proven to be effective in the validation group. The low-risk group patients presented higher criterion of infiltration of CD8+ T cells and higher levels of tumour-infiltrating lymphocytes (TILs). In addition, the relationship between predictive models and homologous recombination deficiency (HRD) was explored and it was revealed that subjects from the high-risk group tended to have higher HRD values. Conclusions: This research established a new predictive model on the basis of immune cell marker genes that might effectively predict relapse in TNBC patients.

High expression of TLR3 in triple-negative breast cancer predicts better prognosis-data from the Fudan University Shanghai Cancer Center cohort and tissue microarrays.

INTRODUCTION: We have previously reported that Toll-like receptor 3 (TLR3) acts as a suppressor gene for breast cancer initiation and progression. In this study, we evaluated the role of TLR3 in breast cancer using our original Fudan University Shanghai Cancer Center (FUSCC) datasets and breast cancer tissue microarrays. METHODS: Using FUSCC multiomics datasets on triple- negative breast cancer (TNBC), we compared the mRNA expression of TLR3 in TNBC tissue and the adjacent normal tissue. A Kaplan-Meier plotter was performed to investigate the expression of TLR3 on prognosis in the FUSCC TNBC cohort. We performed immunohistochemical staining to analyze TLR3 protein expression in the TNBC tissue microarrays. Furthermore, bioinformatics analysis was performed using the Cancer Genome Atlas (TCGA) data to verify the results of our FUSCC study. The relationship between TLR3 and clinicopathological features was analyzed with logistic regression and the Wilcoxon signed-rank test. The association between clinical characteristics and overall survival in TCGA patients was assessed using the Kaplan-Meier method and Cox regression analysis. Gene set enrichment analysis (GSEA) was performed to identify signaling pathways that are differentially activated in breast cancer. RESULTS: The mRNA expression of TLR3 was lower in TNBC tissue than in the adjacent normal tissue in the FUSCC datasets. The TLR3 had high expression in immunomodulatory (IM) and mesenchymal-like (MES) subtypes and low expression in luminal androgen receptor (LAR) and basal-like immune-suppressed (BLIS) subtypes. High expression of TLR3 in TNBC predicted better prognosis in the FUSCC TNBC cohort. Immunohistochemical staining of the tissue microarrays showed that TLR3 had lower expression in breast cancer tissues than in the adject normal tissues. Furthermore, the TLR3 expression was positively associated with B cell, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and myeloid dendritic cells. Bioinformatic analysis using high-throughput RNA-sequencing data from the TCGA demonstrated that the reduced expression of TLR3 in breast cancer was associated with advanced clinicopathological characteristics, survival time, and poor prognosis. CONCLUSIONS: TLR3 has low expression in TNBC tissue. High expression of TLR3 in triple-negative breast cancer predicts better prognosis. TLR3 expression may be a potential prognostic molecular marker of poor survival in breast cancer.