Autophagy‐related long non‐coding RNAs (lncRNAs) disorders are related to the occurrence and development of breast cancer. The purpose of this study is to explore whether autophagy‐related lncRNA can predict the prognosis of breast cancer patients. The autophagy‐related lncRNAs prognostic signature was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression. We identified five autophagy‐related lncRNAs (MAPT‐AS1, LINC01871, AL122010.1, AC090912.1, AC061992.1) associated with prognostic value, and they were used to construct an autophagy‐related lncRNA prognostic signature (ALPS) model. ALPS model offered an independent prognostic value (HR = 1.664, 1.381‐2.006), where this risk score of the model was significantly related to the TNM stage, ER, PR and HER2 status in breast cancer patients. Nomogram could be utilized to predict survival for patients with breast cancer. Principal component analysis and Sankey Diagram results indicated that the distribution of five lncRNAs from the ALPS model tends to be low‐risk. Gene set enrichment analysis showed that the high‐risk group was enriched in autophagy and cancer‐related pathways, and the low‐risk group was enriched in regulatory immune‐related pathways. These results indicated that the ALPS model composed of five autophagy‐related lncRNAs could predict the prognosis of breast cancer patients.

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BackgroundPatients with triple-negative breast cancer (TNBC) have poor overall survival. The present study aimed to investigate the potential prognostics of TNBC by analyzing breast cancer proteomic and transcriptomic datasets.MethodsCandidate proteins selected from CPTAC (the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium) were validated using datasets from METABRIC (Molecular Taxonomy of Breast Cancer International Consortium). Kaplan-Meier analysis and ROC (receiver operating characteristic) curve analysis were performed to explore the prognosis of candidate genes. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis were performed on the suspected candidate genes. Single-cell RNA-seq (scRNA-seq) data from GSE118389 were used to analyze the cell clusters in which OBFC2A (Oligosaccharide-Binding Fold-Containing Protein 2A) was mainly distributed. TIMER (Tumor Immune Estimation Resource) was used to verify the correlation between OBFC2A expression and immune infiltration. Clone formation assays and wound healing assays were used to detect the role of OBFC2A expression on the proliferation, invasion, and migration of breast cancer cells. Flow cytometry was used to analyze the effects of silencing OBFC2A on breast cancer cell cycle and apoptosis.ResultsSix candidate proteins were found to be differentially expressed in non-TNBC and TNBC groups from CPTAC. However, only OBFC2A was identified as an independently poor prognostic gene marker in METABRIC (HR=3.658, 1.881-7.114). And OBFC2A was associated with immune functions in breast cancer. Biological functional experiments showed that OBFC2A might promote the proliferation and migration of breast cancer cells. The inhibition of OBFC2A expression blocked the cell cycle in G1 phase and inhibited the transformation from G1 phase to S phase. Finally, downregulation of OBFC2A also increased the total apoptosis rate of cells.ConclusionOn this basis, OBFC2A may be a potential prognostic biomarker for TNBC.

Estrogen-receptor-positive, and human epidermal growth factor receptor 2-negative (ER+HER2−) breast cancer accounts for ~60−70% of all cases of invasive breast carcinoma. High-grade ER+HER2− tumors respond poorly to endocrine therapy. In this study, we systematically analyzed clinical and multi-omics data to find potential strategies for personalized therapy of patients with high-grade ER+HER2− disease. Six different cohorts were analyzed, for which multi-omics data were available. Grade III ER+HER2-cases harbored higher proportions of large tumor size (>5cm), lymph nodes metastasis, chemotherapy use and luminal B subtypes defined by PAM50, as compared with grade I/II tumors. DNA methylation (HM450) data and methylation specific PCR indicated that the cg18629132 locus in the MKI67 promoter was hypermethylated in grade I/II cases and normal tissue, but hypomethylated in grade III cases or triple negative breast cancer (TNBC), resulting in higher expression of MKI67. Mutations in ESR1 and TP53 were detected in post-endocrine−treatment metastatic samples at a higher rate than in treatment-naive tumors in grade III cases. We identified 42 and 20 focal copy number events in non-metastatic and metastatic high-grade ER+HER2− cases, respectively, with either MYC or MDM2 amplification representing an independent prognostic event in grade III cases. Transcriptional profiling within grade III tumors, highlighted ER signaling downregulation and upregulation of immune-related pathways in non-luminal-like tumors defined by PAM50. Recursive partitioning analysis (RPA) was employed to construct a decision tree of an endocrine-resistant subgroup (GATA3-negative and AGR-negative) of two genes that was validated by immunohistochemistry in a Chinese cohort. All together, these data suggest that grade III ER+HER2− tumors have distinct clinical and molecular characteristics compared with low-grade tumors, particularly in cases with non-luminal-like biology. Due to the dismal prognosis in this group, clinical trials are warranted to test the efficacy of potential novel therapies.