Breast cancer is one of the most common malignancies and the major cause of cancer-related death in women. Although the importance of PIWI-interacting RNAs (piRNAs) in cancer has been increasingly recognized, few studies have been explored the functional mechanism of piRNAs in breast cancer development and progression. We examined the top 20 highly expressed piRNAs based on the analysis of TCGA breast cancer data in two patient cohorts to test the roles of piRNAs in breast cancer. The effects of piRNA-36,712 on the malignant phenotypes and chemosensitivity of breast cancer cells were detected in vitro and in vivo. MS2-RIP and reporter gene assays were conducted to identify the interaction and regulation among piRNA-36,712, miRNAs and SEPW1P. Kaplan-Meier estimate with log-rank test was used to compare patient survival by different piRNA-36,712 expression levels. We found piRNA-36,712 level was significantly lower in breast cancer than in normal breast tissues and low level was correlated with poor clinical outcome in patients. Functional studies demonstrated that piRNA-36,712 interacts with RNAs produced by SEPW1P, a retroprocessed pseudogene of SEPW1, and subsequently inhibits SEPW1 expression through competition of SEPW1 mRNA with SEPW1P RNA for microRNA-7 and microRNA-324. We also found that higher SEPW1 expression due to downregulation of piRNA-36,712 in breast cancer may suppress P53, leading to the upregulated Slug but decreased P21 and E-cadherin levels, thus promoting cancer cell proliferation, invasion and migration. Furthermore, we found that piRNA-36,712 had synergistic anticancer effects with the paclitaxel and doxorubicin, two chemotherapeutic agents for breast cancer. These findings suggest that piRNA-36,712 is a novel tumor suppressor and may serve as a potential predictor for the prognosis of breast cancer patients.

Lymph node metastasis is of major prognostic significance for breast cancer. Lymph node metastasis arises at a very early stage in some patients. Using the data downloaded from the TCGA database, we studied the differences between primary tumors with and without lymph node metastasis at the multi-omics level using bioinformatics approaches. Our study found that low mutation and neoantigen burdens correlated with lymph node metastazation of breast cancer. All three conserved domains in TP53 were mutated in lymph node-negative breast cancers, whereas only one domain was mutated in lymph node-positive samples. Mutations in microtubule-related proteins appear to help immune cells recognize tumors and inhibit their lymph node metastasis. Destroying microtubule-related proteins is a potential therapeutic strategy to inhibit lymph node metastasis of breast cancer. As the neoantigens specifically present in lymph node-positive breast cancers, MAPK10, BC9L, TRIM65, CD93, KITLG, CNPPD1, CPED1, CCDC146, TMEM185A, INO80D, and PSMD11 are potential targets for vaccine design. In the tumor microenvironment, reduced numbers of effector immune cells, especially activated memory CD4+ T cells and activated mast cells, facilitate breast cancer metastasis to the lymph nodes. According to transcriptome data, lymph node metastasis was mostly driven by gene mutation rather than by gene expression. Although differential gene expression analysis was based on lymph node metastasis status, many genes were shown to be differentially expressed based on estrogen receptor status.

Background: Early detection is critical for improving the survival of breast cancer (BC) patients. Exhaled breath testing as a non-invasive technique might help to improve BC detection. However, the breath test accuracy for BC diagnosis is unclear. Methods: This multi-center cohort study consecutively recruited 5047 women from four areas of China who underwent BC screening. Breath samples were collected through standardized breath collection procedures. Volatile organic compound (VOC) markers were identified from a high-throughput breathomics analysis by the high-pressure photon ionization–time-of-flight mass spectrometry (HPPI-TOFMS). Diagnostic models were constructed using the random forest algorithm in the discovery cohort and tested in three external validation cohorts. Results: A total of 465 (9.21%) participants were identified with BC. Ten optimal VOC markers were identified to distinguish the breath samples of BC patients from those of non-cancer women. A diagnostic model (BreathBC) consisting of 10 optimal VOC markers showed an area under the curve (AUC) of 0.87 in external validation cohorts. BreathBC-Plus, which combined 10 VOC markers with risk factors, achieved better performance (AUC = 0.94 in the external validation cohorts), superior to that of mammography and ultrasound. Overall, the BreathBC-Plus detection rates were 96.97% for ductal carcinoma in situ, 85.06%, 90.00%, 88.24%, and 100% for stages I, II, III, and IV BC, respectively, with a specificity of 87.70% in the external validation cohorts. Conclusions: This is the largest study on breath tests to date. Considering the easy-to-perform procedure and high accuracy, these findings exemplify the potential applicability of breath tests in BC screening.

As the malignancy with the highest global incidence, breast cancer represents a significant threat to women’s health. Recent advances have shed light on the importance of mitochondrial function in cancer, particularly in metabolic reprogramming within tumors. Recognizing this, we developed a novel risk signature based on mitochondrial-related genes to improve prognosis prediction and risk stratification in breast cancer patients. In this study, transcriptome data and clinical features of breast cancer samples were extracted from two sources: the TCGA, serving as the training set, and the METABRIC, used as the independent validation set. We developed the signature using LASSO-Cox regression and assessed its prognostic efficacy via ROC curves. Furthermore, the signature was integrated with clinical features to create a Nomogram model, whose accuracy was validated through clinical calibration curves and decision curve analysis. To further elucidate prognostic variations between high and low-risk groups, we conducted functional enrichment and immune infiltration analyses. Additionally, the study encompassed a comparison of mutation landscapes and drug sensitivity, providing a comprehensive understanding of the differing characteristics in these groups. Conclusively, we established a risk signature comprising 8 mitochondrial-related genes—ACSL1, ALDH2, MTHFD2, MRPL13, TP53AIP1, SLC1A1, ME3, and BCL2A1. This signature was identified as an independent risk predictor for breast cancer patient survival, exhibiting a significant high hazard ratio (HR = 3.028, 95%CI 2.038–4.499, P < 0.001). Patients in the low-risk group showed a more favorable prognosis, with enhanced immune infiltration, distinct mutation landscapes, and greater sensitivity to anti-tumor drugs. In contrast, the high-risk group exhibited an adverse trend in these aspects. This risk signature represents a novel and effective prognostic indicator, suggesting valuable insights for patient stratification in breast cancer.

Background: Breast cancer (BC) metastasis is the leading cause of poor prognosis and therapeutic failure. However, the mechanisms underlying cancer metastasis are far from clear. Methods: We screened candidate genes related to metastasis through genome-wide CRISPR screening and high-throughput sequencing of patients with metastatic BC, followed by a panel of metastatic model assays. The effects of tetratricopeptide repeat domain 17 (TTC17) on migration, invasion, and colony formation ability together with the responses to anticancer drugs were investigated in vitro and in vivo. The mechanism mediated by TTC17 was determined by RNA sequencing, Western blotting, immunohistochemistry, and immunofluorescence. The clinical significance of TTC17 was evaluated using BC tissue samples combined with clinicopathological data. Results: We identified the loss of TTC17 as a metastasis driver in BC, and its expression was negatively correlated with malignancy and positively correlated with patient prognosis. TTC17 loss in BC cells promoted their migration, invasion, and colony formation capacity in vitro and lung metastasis in vivo. Conversely, overexpressing TTC17 suppressed these aggressive phenotypes. Mechanistically, TTC17 knockdown in BC cells resulted in the activation of the RAP1/CDC42 pathway along with a disordered cytoskeleton in BC cells, and pharmacological blockade of CDC42 abolished the potentiation of motility and invasiveness caused by TTC17 silencing. Research on BC specimens demonstrated reduced TTC17 and increased CDC42 in metastatic tumors and lymph nodes, and low TTC17 expression was linked to more aggressive clinicopathologic characteristics. Through screening the anticancer drug library, the CDC42 inhibitor rapamycin and the microtubule-stabilizing drug paclitaxel showed stronger inhibition of TTC17-silenced BC cells, which was confirmed by more favorable efficacy in BC patients and tumor-bearing mice receiving rapamycin or paclitaxel in the TTC17^Low arm. Conclusions: TTC17 loss is a novel factor promoting BC metastasis, that enhances migration and invasion by activating RAP1/CDC42 signaling and sensitizes BC to rapamycin and paclitaxel, which may improve stratified treatment strategies under the concept of molecular phenotyping-based precision therapy of BC.