Postoperative progression and chemotherapy resistance is the major cause of treatment failure in patients with triple-negative breast cancer (TNBC). Currently, there is a lack of an ideal predictive model for the progression and drug sensitivity of postoperative TNBC patients. Diverse programmed cell death (PCD) patterns play an important role in tumor progression, which has the potential to be a prognostic and drug sensitivity indicator for TNBC after surgery. Twelve PCD patterns (apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis) were analyzed for model construction. Bulk transcriptome, single-cell transcriptome, genomics, and clinical information were collected from TCGA-BRCA, METABRIC, GSE58812, GSE21653, GSE176078, GSE75688, and KM-plotter cohorts to validate the model. The machine learning algorithm established a cell death index (CDI) with a 12-gene signature. Validated in five independent datasets, TNBC patients with high CDI had a worse prognosis after surgery. Two molecular subtypes of TNBC with distinct vital biological processes were identified by an unsupervised clustering model. A nomogram with high predictive performance was constructed by incorporating CDI with clinical features. Furthermore, CDI was associated with immune checkpoint genes and key tumor microenvironment components by integrated analysis of bulk and single-cell transcriptome. TNBC patients with high CDI are resistant to standard adjuvant chemotherapy regimens (docetaxel, oxaliplatin, etc.); however, they might be sensitive to palbociclib (an FDA-approved drug for luminal breast cancer). Generally, we established a novel CDI model by comprehensively analyzing diverse cell death patterns, which can accurately predict clinical prognosis and drug sensitivity of TNBC after surgery. A user-friendly website was created to facilitate the application of this prediction model (https://tnbc.shinyapps.io/CDI_Model/).

Accumulating evidence indicates that circular RNAs (circRNAs) are vital regulators of various biological functions involved in the progression of multiple cancers. Circular F-box and WD repeat domain containing 7 (circFBXW7) (hsa_circ_0001451) has been reported to act as a tumor suppressor by encoding a novel protein in glioma; however, its functions and mechanisms in triple-negative breast cancer (TNBC) remain elusive. In the current study, we validated by qRT-PCR that circFBXW7 was downregulated in TNBC cell lines and found that low expression of circFBXW7 was associated with poorer clinical outcomes. circFBXW7 expression was negatively correlated with tumor size and lymph node metastasis, and it was an independent prognostic factor for TNBC patients. We performed cell proliferation, colony formation, transwell, wound-healing, and mouse xenograft assays to confirm the functions of circFBXW7. Overexpression of circFBXW7 obviously inhibited cell proliferation, migration, and tumor growth in both in vitro and in vivo assays. Luciferase reporter assays and RNA immunoprecipitation assays revealed that circFBXW7 serves as a sponge of miR-197-3p and suppresses TNBC growth and metastasis by upregulating FBXW7 expression. In addition, the FBXW7-185aa protein encoded by circFBXW7 inhibited the proliferation and migration abilities of TNBC cells by increasing the abundance of FBXW7 and inducing c-Myc degradation. In summary, our research demonstrated that circFBXW7 sponges miR-197-3p and encodes the FBXW7-185aa protein to suppress TNBC progression through upregulating FBXW7 expression. Thus, circFBXW7 may act as a therapeutic target and prognostic biomarker for TNBC.

Intrinsic and acquired anti-HER2 resistance remains a major hurdle for treating HER2-positive breast cancer. Using genome-wide CRISPR/Cas9 screening in vitro and in vivo, we identify FGFR4 as an essential gene following anti-HER2 treatment. FGFR4 inhibition enhances susceptibility to anti-HER2 therapy in resistant breast cancer. Mechanistically, m6A-hypomethylation regulated FGFR4 phosphorylates GSK-3β and activates β-catenin/TCF4 signaling to drive anti-HER2 resistance. Notably, suppression of FGFR4 dramatically diminishes glutathione synthesis and Fe²⁺ efflux efficiency via the β-catenin/TCF4-SLC7A11/FPN1 axis, resulting in excessive ROS production and labile iron pool accumulation. Ferroptosis, a unique iron-dependent form of oxidative cell death, is triggered after FGFR4 inhibition. Experiments involving patient-derived xenografts and organoids reveals a synergistic effect of anti-FGFR4 with anti-HER2 therapy in breast cancer with either intrinsic or acquired resistance. Together, these results pinpoint a mechanism of anti-HER2 resistance and provide a strategy for overcoming resistance via FGFR4 inhibition in recalcitrant HER2-positive breast cancer.

Background: It was unclear whether breast cancer subtypes are associated with the risk of site-specific metastases. This study aimed to evaluate the relationship between molecular subtypes and distant metastatic sites and their prognostic significance. Methods: We identified 295,213 patients with invasive breast cancer from 2010 to 2014 using the Surveillance, Epidemiology and End Results database. Subtypes were classified into four categories: hormone receptor (HR⁺)/human epidermal growth factor receptor 2 (HER2⁻), HR⁺/HER2⁺, HR⁻/HER2⁺, and triple-negative (HR⁻/HER2⁻). Logistic regression was used to assess the association between metastasis location and subtypes. Multivariate Cox models were used to estimate the overall survival (OS) of related factors.
Results: According to our study, 3.28%, 1.52%, 1.20%, and 0.35% of newly diagnosed breast cancers presented bone, lung, liver, and brain metastases at diagnosis, respectively. Both metastatic sites and subtypes significantly affected the OS after metastasis. In multivariate analysis, HR⁺/HER2⁺ subtype (OR as compared with HR⁺/HER2⁻ subtype, 1.30 [95% CI, 1.22–1.39]) significantly correlated with elevated bone metastasis risk, whereas HR⁻/HER2⁺ did not. Both HER2⁺ subtypes (HR⁺/HER2⁺ and HR⁻/HER2⁺) were significantly associated with higher rates of liver, brain, and lung metastases, while the highest OR was observed in liver metastases. Triple-negative tumors had a higher rate of brain (OR, 1.95 [95% CI, 1.61–2.35]), liver (OR, 1.35 [95% CI, 1.20–1.51]), and lung metastases (OR, 1.34 [95% CI, 1.21–1.47]), but a significantly lower rate of bone metastases (OR, 0.64 [95% CI, 0.59–0.69]) than HR⁺/HER2− tumors. Conclusions: Breast cancer subtypes are associated with different metastatic patterns and confer different prognostic impacts. Molecular subtypes can identify patients at increased risk of site-specific metastases.

Circular RNAs (circRNAs) are a class of single-stranded RNAs with covalently closed structures. Owing to their not having 3' or 5' ends, circRNAs are highly durable and insusceptible to exonuclease-mediated degradation. Moreover, some circRNAs with certain structures are translatable, making them novel vaccines. Vaccines are efficient tools for immunotherapy, such as for the prevention of infectious diseases and cancer treatment. The immune system is activated during immunotherapy to fight against abnormal allies or invaders. CircRNA vaccines represent a potential new avenue in the vaccine era. Recently, several circRNA vaccines have been synthesized and tested in vitro and in vivo. Our review briefly introduces the current understanding of the biology and function of translatable circRNAs, molecular biology, synthetic methods, delivery of circRNA, and current circRNA vaccines. We also discussed the challenges and future directions in the field by summarizing the developments in circRNA vaccines in the past few years.

Immune checkpoint inhibitors (ICIs) have shown encouraging treatment efficacy for metastatic breast cancer in several clinical trials. However, response only occurred in a small population. Evidence predicting response and survival of patients with metastatic breast cancer following ICI treatment with existing biomarkers has not been well summarized. This review aimed to summarize the efficacy and predictive factors of immune checkpoint therapy in metastatic breast cancer, which is critical for clinical practice. PubMed, Embase, Cochrane Library, Web of Science, www.clinicaltrials.gov, and meeting abstracts were comprehensively searched to identify clinical trials. The outcomes were objective response rate (ORR), treatment-related adverse events (trAEs), immune-related adverse events (irAEs), progression-free survival (PFS), and overall survival (OS). In this review, 27 studies with 1746 patients were included for quantitative synthesis. The pooled ORR was 19% [95% confidence interval (CI) = 12–27%]. Programmed death-ligand 1 (PD-L1)-positive patients had a higher response rate [odds ratio (OR) = 1.44, p = 0.01]. First-line immunotherapy had a better ORR than second-line immunotherapy (OR = 2.00, p = 0.02). Tumor-infiltrating lymphocytes (TILs) ⩾5% (OR = 2.53, p = 0.002) and high infiltrated CD8+ T-cell level (OR = 4.33, p = 0.006) were ideal predictors of immune checkpoint therapy response. Liver metastasis indicated poor response (OR = 0.19, p = 0.009). However, the difference was non-significant in ORR based on age, performance status score, lymph node metastasis, and lactate dehydrogenase (LDH) level. In addition, the PD-L1-positive subgroup had a better 1-year PFS (OR = 1.55, p = 0.04) and 2-year OS (OR = 2.28, p = 0.02) following ICI treatment. The pooled incidence during ICI therapy of grade 3–4 trAEs was 25% (95% CI = 16–34%), whereas for grade 3–4 irAEs it was 15% (95% CI = 11–19%). Metastatic breast cancer had modest response to ICI therapy. PD-L1-positive, first-line immunotherapy, non-liver metastasis, and high TIL and CD8+ T-cell infiltrating levels could predict better response to ICI treatment. Patients with PD-L1-positive tumor could gain more survival benefits from immune checkpoint therapy.