Breast cancer is the most commonly diagnosed cancer and leading cause of cancer mortality among woman worldwide. The techniques of diagnosis, prognosis, and therapy monitoring of breast cancer are critical. Current diagnostic techniques are mammography and tissue biopsy; however, they have limitations. With the development of novel techniques, such as personalized medicine and genetic profiling, liquid biopsy is emerging as the less invasive tool for diagnosing and monitoring breast cancer. Liquid biopsy is performed by sampling biofluids and extracting tumor components, such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), cell-free mRNA (cfRNA) and microRNA (miRNA), proteins, and extracellular vehicles (EVs). In this review, we summarize and focus on the recent discoveries of tumor components and biomarkers applied in liquid biopsy and novel development of detection techniques, such as surface-enhanced Raman spectroscopy (SERS) and microfluidic devices.

Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER−, PR−, and HER2−), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.

The early diagnosis, prognostic prediction, and personalized therapy of lung adenocarcinoma (LUAD) remains a challenging issue. KCNQ1 (potassium voltage-gated channel subfamily Q Member 1) is implicated in long QT syndrome (LQTS) and cardiac arrhythmia, while its significance in LUAD remains unclear. In this study, we aimed to explore the significance of KCNQ1 in terms of clinical value, tumor immunity, underlying mechanisms, and a precision medicine approach by means of multi-omics analysis. The association of KCNQ1 with LUAD was first explored. Both altered variants and high expression of KCNQ1 in a TCGA-LUAD cohort indicated a favorable outcome. KCNQ1 levels had a negative correlation with tumor proliferation index Ki67 levels. siRNA-knockdown of KCNQ1 promoted the migration ability of lung cancer cells. KCNQ1 levels were decreased in LUAD tissue compared to normal tissue. A receiver operating characteristic (ROC) curve indicated good diagnostic efficiency of KCNQ1. High KCNQ1 is associated with an immunoactive profile of immune infiltration and immunomodulators and is involved in the inhibition of the cell cycle and DNA replication. Lapatinib was identified as a potent drug for LUAD in the context of low KCNQ1. This study unveiled the significance of KCNQ1 in diagnosis and prognosis and provided a corresponding precision medicine strategy for LUAD.

(1) Background: methionine cycle is not only essential for cancer cell proliferation but is also critical for metabolic reprogramming, a cancer hallmark. Hepatic and extrahepatic tissues methionine adenosyltransferases (MATs) are products of two genes, MAT1A and MAT2A that catalyze the formation of S-adenosylmethionine (SAM), the principal biological methyl donor. Glycine N-methyltransferase (GNMT) further utilizes SAM for sarcosine formation, thus it regulates the ratio of SAM:S-adenosylhomocysteine (SAH). (2) Methods: by analyzing the TCGA/GTEx datasets available within GEPIA2, we discovered that breast cancer patients with higher MAT2A had worse survival rate (p = 0.0057). Protein expression pattern of MAT1AA, MAT2A and GNMT were investigated in the tissue microarray in our own cohort (n = 252) by immunohistochemistry. MAT2A C/N expression ratio and cell invasion activity were further investigated in a panel of breast cancer cell lines. (3) Results: GNMT and MAT1A were detected in the cytoplasm, whereas MAT2A showed both cytoplasmic and nuclear immunoreactivity. Neither GNMT nor MAT1A protein expression was associated with patient survival rate in our cohort. Kaplan–Meier survival curves showed that a higher cytoplasmic/nuclear (C/N) MAT2A protein expression ratio correlated with poor overall survival (5 year survival rate: 93.7% vs. 83.3%, C/N ratio ≥ 1.0 vs. C/N ratio < 1.0, log-rank p = 0.004). Accordingly, a MAT2A C/N expression ratio ≥ 1.0 was determined as an independent risk factor by Cox regression analysis (hazard ratio = 2.771, p = 0.018, n = 252). In vitro studies found that breast cancer cell lines with a higher MAT2A C/N ratio were more invasive. (4) Conclusions: the subcellular localization of MAT2A may affect its functions, and elevated MAT2A C/N ratio in breast cancer cells is associated with increased invasiveness. MAT2A C/N expression ratio determined by IHC staining could serve as a novel independent prognostic marker for breast cancer.

Globally, breast cancer has remained the most commonly diagnosed cancer and the leading cause of cancer death among women. Breast cancer is a highly heterogeneous and phenotypically diverse group of diseases, which require different selection of treatments. Breast cancer stem cells (BCSCs), a small subset of cancer cells with stem cell-like properties, play essential roles in breast cancer progression, recurrence, metastasis, chemoresistance and treatments. Epigenetics is defined as inheritable changes in gene expression without alteration in DNA sequence. Epigenetic regulation includes DNA methylation and demethylation, as well as histone modifications. Aberrant epigenetic regulation results in carcinogenesis. In this review, the mechanism of epigenetic regulation involved in carcinogenesis, therapeutic resistance and metastasis of BCSCs will be discussed, and finally, the therapies targeting these biomarkers will be presented.

Background/Aim: Breast cancer (BC) is the most common cancer and second leading cause of death in women worldwide. Triple-negative breast cancer (TNBC) is the most aggressive type of BC, while the treatment option is limited and has long been considered as a major unmet need. Meta-analysis indicated the anti-tumor potential of anti-depressants, especially selective serotonin-reuptake inhibitors (SSRIs). The SSRI fluoxetine has been shown to suppress BC and ovarian cancer cell growth; however, whether it suppresses tumor progression in vivo is unclear. Materials and Methods: We established an 4T1 bearing animal model, an orthotopic TNBC model, to identify the mechanism and therapeutic efficacy of fluoxetine. Results: Tumor growth evaluated by caliper and computed tomography scan demonstrated the inhibition effect by fluoxetine treatment. Immunohistochemistry showed that the expression of STAT3-mediated epithelial-to-mesenchymal transition (EMT) proteins and apoptosis-related proteins was decreased. Conclusion: Fluoxetine may induce an anti-TNBC effect via inactivating STAT3 signaling transduction and triggering the caspase-mediated apoptotic pathway.