Distinguish Breast Cancer Patients Research Articles

Discovery of Plasma Lipids as Potential Biomarkers Distinguishing Breast Cancer Patients from Healthy Controls.

The development of a sensitive and specific blood test for the early detection of breast cancer is crucial to improve screening and patient outcomes. Existing methods, such as mammography, have limitations, necessitating the exploration of alternative approaches, including circulating factors. Using 598 prospectively collected blood samples, a multivariate plasma-derived lipid biomarker signature was developed that can distinguish healthy control individuals from those with breast cancer. Liquid chromatography with high-resolution and tandem mass spectrometry (LC-MS/MS) was employed to identify lipids for both extracellular vesicle-derived and plasma-derived signatures. For each dataset, we identified a signature of 20 lipids using a robust, statistically rigorous feature selection algorithm based on random forest feature importance applied to cross-validated training samples. Using an ensemble of machine learning models, the plasma 20-lipid signature generated an area under the curve (AUC) of 0.95, sensitivity of 0.91, and specificity of 0.79. The results from this study indicate that lipids extracted from plasma can be used as target analytes in the development of assays to detect the presence of early-stage breast cancer.

Identification of TAT as a Biomarker Involved in Cell Cycle and DNA Repair in Breast Cancer.

Breast cancer (BC) is the most frequently diagnosed cancer and the primary cause of cancer-related mortality in women. Treatment of triple-negative breast cancer (TNBC) remains particularly challenging due to its resistance to chemotherapy and poor prognosis. Extensive research efforts in BC screening and therapy have improved clinical outcomes for BC patients. Therefore, identifying reliable biomarkers for TNBC is of great clinical importance. Here, we found that tyrosine aminotransferase (TAT) expression was significantly reduced in BC and strongly correlated with the poor prognosis of BC patients, which distinguished BC patients from normal individuals, indicating that TAT is a valuable biomarker for early BC diagnosis. Mechanistically, we uncovered that methylation of the TAT promoter was significantly increased by DNA methyltransferase 3 (DNMT3A/3B). In addition, reduced TAT contributes to DNA replication and cell cycle activation by regulating homologous recombination repair and mismatch repair to ensure genomic stability, which may be one of the reasons for TNBC resistance to chemotherapy. Furthermore, we demonstrated that Diazinon increases TAT expression as an inhibitor of DNMT3A/3B and inhibits the growth of BC by blocking downstream pathways. Taken together, we revealed that TAT is silenced by DNMT3A/3B in BC, especially in TNBC, which promotes the proliferation of tumor cells by supporting DNA replication, activating cell cycle, and enhancing DNA damage repair. These results provide fresh insights and a theoretical foundation for the clinical diagnosis and treatment of BC.

Proximity-Guaranteed DNA Machine for Accurate Identification of Breast Cancer Extracellular Vesicles.

Breast cancer is one of the most diagnosed cancers worldwide. Precise diagnosis and subtyping have important significance for targeted therapy and prognosis prediction of breast cancer. Herein, we design a proximity-guaranteed DNA machine for accurate identification of breast cancer extracellular vesicles (EVs), which is beneficial to explore the subtype features of breast cancer. In our design, two proximity probes are located close on the same EV through specific recognition of coexisting surface biomarkers, thus being ligated with the help of click chemistry. Then, the ligated product initiates the operation of a DNA machine involving catalytic hairpin assembly and clusters of regularly interspaced short palindromic repeats (CRISPR)-Cas12a-mediated trans-cleavage, which finally generates a significant response that enables the identification of EVs expressing both biomarkers. Principle-of-proof studies are performed using EVs derived from the breast cancer cell line BT474 as the models, confirming the high sensitivity and specificity of the DNA machine. When further applied to clinical samples, the DNA machine is shown to be capable of not only distinguishing breast cancer patients with special subtypes but also realizing the tumor staging regarding the disease progression. Therefore, our work may provide new insights into the subtype-based diagnosis of breast cancer as well as identification of more potential therapeutic targets in the future.

Unlocking the diagnostic potential: N-Glycan profiling for distinguishing breast cancer patients from healthy individuals

Chest sickness is now the most broadly perceived dangerous development, addressing 12.5% of all new yearly harmful development cases all over the planet. Around 13% (around 1 out of 8) of U.S. women will cultivate prominent chest illness all through their lives. In 2022, a normal 287,850 new occurrences of prominent chest illness should be examined in women in the U.S., close to 51,400 new examples of easy chest dangerous development. The exploration directed a review where N-glycans were gotten from the serum of bosom disease patients and solid people, and their general overflow contrasts were used for primer bosom malignant growth determination. Through Fractional Least Squares Discriminant Examination (PLS-DA), the creator had the option to successfully recognize bosom malignant growth patients from the sound populace, demonstrating the capability of N-glycan profiles in segregating between bosom disease and non-bosom disease people. This examination denotes a promising step towards the improvement of expected demonstrative and prognostic markers for bosom disease, giving likely biomarkers to beginning-phase bosom malignant growth patients. The discoveries of this study might hold critical pertinence in the field of bosom disease determination and treatment. This exploration will utilize work area and trial. Past assessment found that the level of serum N-glycan A2G1(6)FB, a biantennary N-glycan containing focus fucose and bisecting GlcNAc developments was higher in chest-threatening development patients than in those without chest illness. Additionally, A2G1(6)FB was recognizable in chest dangerous development patients with starting stage and could be a precise marker. Hence, concurrent utilization of IgG blood tests and customary biomarkers could work on the exactness of bosom disease determination, recommending that IgG blood tests might be a solid biomarker for beginning phase bosom malignant growth patients.

Integrated analysis of diverse cancer types reveals a breast cancer-specific serum miRNA biomarker through relative expression orderings analysis

PurposeSerum microRNA (miRNA) holds great potential as a non-invasive biomarker for diagnosing breast cancer (BrC). However, most diagnostic models rely on the absolute expression levels of miRNAs, which are susceptible to batch effects and challenging for clinical transformation. Furthermore, current studies on liquid biopsy diagnostic biomarkers for BrC mainly focus on distinguishing BrC patients from healthy controls, needing more specificity assessment.MethodsWe collected a large number of miRNA expression data involving 8465 samples from GEO, including 13 different cancer types and non-cancer controls. Based on the relative expression orderings (REOs) of miRNAs within each sample, we applied the greedy, LASSO multiple linear regression, and random forest algorithms to identify a qualitative biomarker specific to BrC by comparing BrC samples to samples of other cancers as controls.ResultsWe developed a BrC-specific biomarker called 7-miRPairs, consisting of seven miRNA pairs. It demonstrated comparable classification performance in our analyzed machine learning algorithms while requiring fewer miRNA pairs, accurately distinguishing BrC from 12 other cancer types. The diagnostic performance of 7-miRPairs was favorable in the training set (accuracy = 98.47%, specificity = 98.14%, sensitivity = 99.25%), and similar results were obtained in the test set (accuracy = 97.22%, specificity = 96.87%, sensitivity = 98.02%). KEGG pathway enrichment analysis of the 11 miRNAs within the 7-miRPairs revealed significant enrichment of target mRNAs in pathways associated with BrC.ConclusionOur study provides evidence that utilizing serum miRNA pairs can offer significant advantages for BrC-specific diagnosis in clinical practice by directly comparing serum samples with BrC to other cancer types.

A highly sensitive and selective fluorescent biosensor for breast cancer derived exosomes using click reaction of azide-CD63 aptamer and alkyne-polymer dots.

Exosomes have gained recognition as valuable reservoirs of biomarkers, holding immense potential for early cancer detection. Consequently, there is a pressing need for the development of an economical and highly sensitive exosome detection methodology. In this work, we present a fluorescence method for breast cancer-derived exosome detection based on Cu-triggered click reaction of azide-modified CD63 aptamer and alkyne functionalized Pdots. The detection threshold for the exosomes obtained from the breast cancer serum was determined to be 6.09 × 107 particles per μL, while the measurable range spanned from 6.50 × 107 to 1.30 × 109 particles per μL. The employed methodology achieved notable success in accurately distinguishing breast cancer patients from healthy individuals through serum analysis. The application of this method showcases the significant potential for early exosome analysis in the clinical diagnosis of breast cancer patients.

LncRNA LY6E-DT and its encoded metastatic-related protein play oncogenic roles via different pathways and promote breast cancer progression.

Abnormal long noncoding RNA (lncRNA) expression plays an important role in tumor invasion and metastasis. Here, we show that lncRNA LY6E divergent transcript (LY6E-DT) levels are increased in breast cancer (BC) tissues. Transcription factor SP3 binds directly to the LY6E-DT promoter, activating its transcription. Moreover, LY6E-DT N6-methyladenosine modification by methyltransferase-like protein 14 (METTL14) promotes its expression, dependent on the "reader" insulin-like growth factor 2 mRNA binding protein 1(IGF2BP1)-dependent pathway. Notably, we discovered that the lncRNA LY6E-DT encodes a conserved 153-aa protein, "Metastatic-Related Protein" (MRP). Both LY6E-DT and MRP promote BC invasion and metastasis, and MRP expression could distinguish BC patients with lymph node metastasis from those without. Mechanistically, MRP binds heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC), enhancing the interaction between HNRNPC and epidermal growth factor receptor (EGFR) mRNA, increasing EGFR mRNA stability and protein expression and subsequently activating the phosphatidylinositol 3‑kinase/protein kinase B signaling (PI3K) pathway. LncRNA LY6E-DT promotes the interaction between Y box binding protein 1 (YBX1) and importin α1 and increases YBX1 protein entry into the nucleus, where it transcriptionally activates zinc finger E-box-binding homeobox 1(ZEB1). Our findings uncover a novel regulatory mechanism underlying BC invasion orchestrated by LY6E-DT and its encoded MRP.

Cas-Rainbow: Cas12a-driven single-reaction multiplex detection system

Recently, CRISPR/Cas system has garnered considerable attention owing to its high cleavage efficiency. However, it lacks the ability to differentiate between signal sources. To address this, we have developed a multiplex detection system called Cas-Rainbow. This system combines CRISPR/Cas with rolling circle amplification (RCA) and hybridization chain reaction (HCR) to enable the detection of multiple miRNAs using reporter probes labeled with different fluorescent groups. The RCA product can trigger the formation of HCR and activate the Cas12a/crRNA complex, achieving the simultaneous detection of multiple miRNAs. Detection limits of three miRNAs (miR-155, miR-10b, and miR-21) were 33 fM, 41 fM, and 79 fM, respectively. Cas-Rainbow system could effectively identify these three miRNAs in serum, distinguishing breast cancer patients from healthy donors with accuracy of 100 %. Moreover, this system exhibited exceptional performance in logic gate circuits, showcasing its remarkable versatility and robustness. In summary, our proposed method offers a new approach for multiplex detection based on the CRISPR/Cas system.

Employing the Anchor DSPE-PEG as a Redox Probe for Ratiometric Electrochemical Detection of Surface Proteins on Extracellular Vesicles with Aptamers.

Quantitative analysis of surface proteins on extracellular vesicles (EVs) has been considered to be a crucial approach for reflecting the status of diseases. Due to the diverse composition of surface proteins on EVs and the interference from nonvesicular proteins, accurately detecting the expression of surface proteins on EVs remains a challenging task. While membrane affinity molecules have been widely employed as EVs capture probes to address this issue, their inherent biochemical properties have not been effectively harnessed. In this paper, we found that the electrochemical redox activity of the DSPE-PEG molecule was diminished upon its insertion into the membrane of EVs. This observation establishes the DSPE-PEG molecule modified on the Au electrode surface as a capture and a redox probe for the electrochemical detection of EVs. By utilizing methylene blue-labeled aptamers, the targeted surface proteins of EVs can be detected by recording the ratio of the oxidation peak current of methylene blue and DSPE-PEG. Without complicated signal amplification, the detection limit for EVs is calculated to be 8.11 × 102 particles/mL. Using this platform, we directly analyzed the expression of CD63 and HER2 proteins on the surface of EVs in human clinical plasma samples, demonstrating its significant potential in distinguishing breast cancer patients from healthy individuals.

Localized Imaging of Programmed Death-Ligand 1 on Individual Tumor-Derived Extracellular Vesicles for Prediction of Immunotherapy Response.

Programmed death-ligand 1 (PD-L1) on tumor-derived small extracellular vesicles (EVs) is a biomarker for prediction of the immunotherapy response. However, conventional bulk measurement can hardly analyze the expression of PD-L1 on individual tumor-derived EVs. Herein, a method for localized imaging of tumor-derived individual EVs PD-L1 (LITIE) is developed. In this assay, EVs in plasma were directly captured on a biochip. Then the liposome-mediated membrane fusion strategy was used to image miR-21 in EVs to discriminate miR-21-positive EVs from the whole EVs populations. Subsequently, the primer exchange reaction (PER) is applied to generate localized and amplified fluorescent signals for imaging PD-L1 on identified tumor-derived EVs. When applied in clinical sample tests, the LITIE assay could effectively distinguish breast cancer patients from healthy donors or patients with benign tumors. Interestingly, in a mice melanoma model, the LITIE assay showed the ability to predict immunotherapy response even before drug treatment. Thus, we think the strategy of measuring individual tumor-derived EVs PD-L1 could serve as an alternative way for screening clinical responders suitable for immunotherapy.

B-381 A Multiplex Blood-based Assay Targeting DNA methylation in Peripheral Blood Mononuclear Cells Enables Early Detection of Breast Cancer

Abstract Background The immune system can monitor the development of tumors, and the DNA methylation is involved in the body immune response to tumors. Therefore, the DNA from peripheral blood mononuclear cell (PBMC) that carries cancer-specific epigenetic aberrations may serve as a non-invasive marker for early detection of breast cancer (BC). Methods Genome-wide DNA methylation profiling on PBMC DNA from BC patients and healthy controls (Cohort I, n = 80) was performed in the discovery phase by Infinium 850K BeadChips. The candidate CpG sites were selected and validated in a multistep validation phase (Cohort II, n = 200) via pyrosequencing and targeted bisulfite sequencing. After that, the multiplex quantitative methylation-specific PCR assay (mBC-MSP) was established to detect BC, and the performance of this diagnostic method was analyzed in a multicenter cohort (Cohort III, n = 501). Results A total of 289 differentially methylated CpG positions (DMPs) between BC patients and healthy controls were identified. Among them, eight significant DMPs markers were selected and further validated using pyrosequencing and targeted bisulfite sequencing, and four hyper-methylated DMPs (cg18637238, cg16652347, cg13828440, cg11754974) passed the final validation. Then, we developed a mBC-MSP assay based on the four methylated markers. This assay exhibited excellent performance in distinguishing BC patients, with an AUC of 0.925, sensitivity of 83.1%, and specificity of 90.4%. More importantly, compared with CA153, CA125 and CEA, the mBC-MSP assay had higher sensitivity for early-stage BC (stage 0, 88.2% vs 0%, 0%, 5.9%) and minimal tumor with diameter ≤1.5 cm (91.7% vs 0%, 2.1%, 0%). Conclusions The mBC-MSP assay based on the four identified DNA methylation markers from PBMC can serve as a noninvasive, accurate, rapid, and high-throughput method for early diagnosis of BC, and it is more sensitive than traditional tumor markers for detecting early-stage BC and minimal tumor.

Rapid Detection of Volatile Organic Metabolites in Urine by High-Pressure Photoionization Mass Spectrometry for Breast Cancer Screening: A Pilot Study.

Despite surpassing lung cancer as the most frequently diagnosed cancer, female breast cancer (BC) still lacks rapid detection methods for screening that can be implemented on a large scale in practical clinical settings. However, urine is a readily available biofluid obtained non-invasively and contains numerous volatile organic metabolites (VOMs) that offer valuable metabolic information concerning the onset and progression of diseases. In this work, a rapid method for analysis of VOMs in urine by using high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) coupled with dynamic purge injection. A simple pretreatment process of urine samples by adding acid and salt was employed for efficient VOM sampling, and the numbers of metabolites increased and the detection sensitivity was improved after the acid (HCl) and salt (NaCl) addition. The established mass spectrometry detection method was applied to analyze a set of training samples collected from a local hospital, including 24 breast cancer patients and 27 healthy controls. Statistical analysis techniques such as principal component analysis, partial least squares discriminant analysis, and the Mann-Whitney U test were used, and nine VOMs were identified as differential metabolites. Finally, acrolein, 2-pentanone, and methyl allyl sulfide were selected to build a metabolite combination model for distinguishing breast cancer patients from the healthy group, and the achieved sensitivity and specificity were 92.6% and 91.7%, respectively, according to the receiver operating characteristic curve analysis. The results demonstrate that this technology has potential to become a rapid screening tool for breast cancer, with significant room for further development.

One-step self-assembly of quantum dot-based spherical nucleic acid nanostructure for accurate monitoring of long noncoding RNA MALAT1 in living cells and tissues

Simple and sensitive measurement of long non-coding RNA (lncRNA) is critical for early detection of malignancies. Herein, we demonstrate one-step self-assembly of quantum dot (QD)-based spherical nucleic acid (SNA) nanostructure for accurate monitoring of lncRNAs in living cells and tissues. When target lncRNA is present, it binds with a dumbbell probe to expose the complementary domain of Cy5-labeled primer, which subsequently induces cascade primer exchange reaction to produce abundant Cy5-labeled initiators. The Cy5-labeled initiators subsequently hybridize with hairpin probes on the QD surface to activate isothermal circular strand-displacement polymerization reaction, generating the QD-DNA-Cy5 nanostructures and inducing efficient Förster resonance energy transfer (FRET) between donor QD and acceptor Cy5. The obtained FRET signals are accurately quantified by single-molecule imaging. Notably, the single QD-based SNA nanostructure functions not only as a signal transmitter but also as a protector against non-specific amplification. Moreover, this assay utilizes only one DNA polymerase to achieve two-stage amplification, avoiding careful modulation of multiple enzymes. The self-assembly of QD nanosensor can be accomplished in single-step and single-tube manners at room temperature, eliminating precise temperature control and labor-intensive reaction protocols. This QD nanosensor achieves high sensitivity with a limit of detection (LOD) of 65.25 aM, and it is capable of quantifying lncRNA expression at single-cell level, differentiate tumor cells from normal cells, and distinguish breast cancer patients from healthy individuals, providing a versatile paradigm for biomedical research and early clinic diagnostics.

A colorimetric and photothermal dual-mode biosensing platform based on nanozyme-functionalized flower-like DNA structures for tumor-derived exosome detection.

Tumor-derived exosomes can be served as a kind of promising biomarkers for early diagnosis of cancers. Herein, a colorimetric/photothermal dual-mode exosomes sensing platform is developed for human breast cancer cell (MCF-7)-derived exosomes based on encapsulation of 3,3',5,5'-tetramethylbenzidine-loaded graphene quantum dot nanozymes (TMB-GQDzymes) into DNA flowers (DFs) via rolling circle amplification (RCA). To achieve specific detection, EpCAM aptamer for MCF-7 cell-derived exosomes is immobilized on the well plate, while the complementary sequence of another CD63 aptamer is designed into the circular template to obtain abundant capture probes. Benefitting from the dual-aptamer recognition strategy, a sandwich structure of EpCAM aptamer/exosomes/TMB-GQDzymes@DFs is formed, in which the GQDzymes can catalyze the oxidation of TMB in the presence of H2O2. The resulting products of TMB oxidation (oxTMB) can induce not only the absorption changes but also a near-infrared (NIR) laser-driven photothermal effect, achieving dual-mode detection of exosomes with the limit of detection (LOD) of 1027 particles/μL (colorimetry) and 2170 particles/μL (photothermal detection), respectively. In addition, this sensing platform has demonstrated excellent performance to well distinguish breast cancer patients from healthy individuals in serum samples analysis. Overall, the proposed dual-readout biosensor opens promising prospects for exosome detection in biological study and clinical applications.

Abstract 2216: Construction of a prognostic 6-gene signature for breast cancer based on multi-omics data

Abstract Breast cancer (BC) is a heterogeneous disease. Distinguishing BC patients with different prognosis can help to make clinical strategies. In our study, we tried to identify novel prognostic genetic biomarkers for BC by using multi-omics data and establish a risk score (RS) signature with genetic biomarkers which have high predictive value. A combined significance (pcombined) of each gene was calculated by Fisher’s method based on the p value of the difference examination of the respective index in RNA-seq, CNV, and DNA methylation data of corresponding genes from TCGA-BRCA dataset. Genes with a pcombined < 0.010 were subjected to univariate cox and Lasso regression to screen out hub genes, whereby a RS signature consisted of six genes, C15orf52, C1orf228, CEL, FUZ, PAK6, and SIRPG, was established. With the Kaplan-Meier (KM) method, the receiver operating characteristic curves (ROC), multivariate cox regression, Nomogram, and decision curve analysis (DCA), the predicted performance of the RS signature was assessed in TCGA-BRCA, GSE7390, and GSE20685. The predicted performance in TNBC patients was emphatically analyzed in TCGA-BRCA and GSE103091, while immune characteristics were also explored. Basing on the data from Genomics of Drug Sensitivity in Cancer (GDSC) database and related R package, we further examined the drug sensitivity of TNBC patients with different RS. With survival rates having significant differences in all KM analyses and most area under ROCs reaching 0.700, the RS signature could distinguish the prognosis of patients, even stratified by disease stages or subtypes. The RS also showed a stronger predictive ability than traditional clinical indicators, including age, tumor topology (T), regional lymph node (N), metastasis (M), and TNM stage. The down-regulated expressions of many immune checkpoints were observed in TNBC patients with higher RS, while the sensitivity of many antitumor drugs was reduced in those with higher RS, except for BI2536 (CAS No.: 755038-02-9), which demonstrated a smaller half maximal inhibitory concentration (which mean a higher drug sensitivity) in TNBC patients with higher RS. In conclusion, the six genes RS signature established based on multi-omics data exhibited well performance in predicting the prognosis of BC patients, regardless of disease stages or subtypes. Contributing to a more personalized treatment, the RS signature might benefit the outcome of BC patients. Citation Format: Zeyu Xing, Yuting Hong. Construction of a prognostic 6-gene signature for breast cancer based on multi-omics data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2216.

Application of serum SERS technology based on thermally annealed silver nanoparticle composite substrate in breast cancer.

Liquid biopsy is currently a non-destructive and convenient method of cancer screening, due to human blood containing a variety of cancer-related biomolecules. Therefore, the development of an accurate and rapid breast cancer screening technique combined with breast cancer serum is crucial for the treatment and prognosis of breast cancer patients. In this study, the surface enhanced Raman spectroscopy (SERS) technique is used to enhance the Raman spectroscopy (RS) signal of serum based on a high sensitivity thermally annealed silver nanoparticle/porous silicon bragg mirror (AgNPs/PSB) composite substrate. Compared with RS, SERS reflects more and stronger spectral peak information, which is beneficial to discover new biomarkers of breast cancer. At the same time, to further explore the diagnostic ability of SERS technology for breast cancer. In this study, the raw spectral data are processed by baseline correction, polynomial smoothing, and normalization. Then, the relevant feature information of SERS and RS is extracted by principal component analysis (PCA), and five classification models are established to compare the diagnostic performance of SERS and RS models respectively. The experimental results show that the breast cancer diagnosis model based on the improved SERS substrate combined with the machine learning algorithm can be used to distinguish breast cancer patients from controls. The accuracy, sensitivity, specificity and AUC values of the SVM model are 100%, 100%, 100% and 100%, respectively, as well as the training time of 4ms. The above experimental results show that the SERS technology based on AgNPs/PSB composite substrate, combined with machine learning methods, has great potential in the rapid and accurate identification of breast cancer patients.

An Epidemiological Systematic Review with Meta-Analysis on Biomarker Role of Circulating MicroRNAs in Breast Cancer Incidence.

Breast cancer (BC) is a multifactorial disease caused by an interaction between genetic predisposition and environmental exposures. MicroRNAs are a group of small non-coding RNA molecules, which seem to have a role either as tumor suppressor genes or oncogenes and seem to be related to cancer risk factors. We conducted a systematic review and meta-analysis to identify circulating microRNAs related to BC diagnosis, paying special attention to methodological problems in this research field. A meta-analysis was performed for microRNAs analyzed in at least three independent studies where sufficient data to make analysis were presented. Seventy-five studies were included in the systematic review. A meta-analysis was performed for microRNAs analyzed in at least three independent studies where sufficient data to make analysis were presented. Seven studies were included in the MIR21 and MIR155 meta-analysis, while four studies were included in the MIR10b metanalysis. The pooled sensitivity and specificity of MIR21 for BC diagnosis were 0.86 (95%CI 0.76-0.93) and 0.84 (95%CI 0.71-0.92), 0.83 (95%CI 0.72-0.91) and 0.90 (95%CI 0.69-0.97) for MIR155, and 0.56 (95%CI 0.32-0.71) and 0.95 (95%CI 0.88-0.98) for MIR10b, respectively. Several other microRNAs were found to be dysregulated, distinguishing BC patients from healthy controls. However, there was little consistency between included studies, making it difficult to identify specific microRNAs useful for diagnosis.

Construction of a cleavable linker chemistry-based HBEXO-Chip to isolate circulating exosomes for breast cancer diagnosis.

Breast cancer is presently the most common form of malignant tumour globally, and its precise diagnosis is vital for enhancing patient survival rates and their quality of life. Exosomes, which are small extracellular vesicles containing proteins and nucleic acid molecules, have emerged as ideal cancer markers for liquid biopsy-based diagnostics. Nevertheless, the current methods for isolating exosomes present challenges for clinical implementation. Although immunoaffinity-based microfluidics hold potential for exosome-based cancer diagnostics, existing microfluidic chips struggle to capture and release intact, high-purity, and highly specific exosomes effectively. To surmount these obstacles, we developed the HBEXO-Chip, an innovative immunoaffinity microfluidic device that employs cleavable linker chemistry technology. This chip enables rapid isolation and detection of breast cancer-derived exosomes in peripheral blood. The fishbone-like microfluidic chip design of the HBEXO-Chip heightens the binding likelihood between specific exosomes and antibodies, significantly augmenting capture efficiency. Furthermore, the gentle reaction conditions of the cleavable linker chemistry retain the exosomes' membrane structure's integrity during the release process, which is advantageous for downstream experimental analysis. Our study demonstrated the effectiveness of the HBEXO-Chip in distinguishing breast cancer patients, patients with benign breast tumours, and healthy controls. By quantitatively analysing Epcam+ exosomes in clinical plasma samples, this technology platform provides a quick, user-friendly, highly sensitive, and specific assay for detecting tumour exosomes in peripheral blood, making it a valuable liquid biopsy tool for clinicians to diagnose breast cancer.

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

Breast cancer (BRCA) is the most prevalent malignancy and the leading cause of death in women. Interleukin (IL) genes are critical in tumor initiation and control. Nevertheless, the prognosis value of the IL in BRCA remains unclear. We collected data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and 94 IL genes were identified from GeneCard. Based on the random forest (RF), least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression analysis, we constructed an IL signature. GSE22219, GSE25065, and GSE21653 were derived as validation sets. The expression differences in the tumor microenvironment (TME), immunotherapy, and chemosensitivity of BRCA between the high- and low-risk groups were evaluated. Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA. IL score could distinguish BRCA patients with inferior outcomes, and AUC of it was 0.70, 0.76, and 0.72 for 1-,3- and 5- years, respectively, which was also verified in GSE22219, GSE25065, and GSE21653 cohorts. Meanwhile, compared to luminal A and luminal B, HER2-positive and TNBC had significantly higher IL score. Besides, the high-risk group had a significantly higher prevalence of TP53 and TTN but a lower prevalence of PIK3CA, as well as higher tumor mutation burden (TMB) and neoantigen level. High- and low-risk groups exhibited notable differences in immunomodulators and tumor infiltrates immune cells (TIICs), and the high-risk group had significantly lower Tumor Immune Dysfunction and Exclusion (TIDE) score. Additionally, the high-risk group has more responders to immune or anti-HER2 combination therapy, whereas the low-risk group has higher sensitivity to docetaxel and paclitaxel. Consequently, we constructed a reliable risk model based on the IL genes, which can provide more information on both the risk stratification and personalizing management strategies for BRCA.

The types of tumor infiltrating lymphocytes are valuable for the diagnosis and prognosis of breast cancer.

This study aimed at constructing a diagnostic immune risk score (dIRS) system and a prognostic immune risk score (pIRS) system for diagnose and prognosis of breast cancer (BC). The gene expression data of BC were downloaded from TCGA dataset (training set), and from GSE65194, GSE29044, GSE42568, and GSE20685 (validation sets). Then, the immune cell type proportions in each dataset were assessed using EPIC tool, and the dIRS system was built based on the SVM-RFE and RF-VIMP algorithms. Subsequently, the pIRS system and the nomogram survival model were established separately using penalized and rms packages. Finally, the differential expressed genes (DEGs) between low and high pIRS groups were screened, and submitted for functional analysis. The dIRS system consisted of B cells, CD8 + T cells, endothelial cells, NK cells, and other cells had high accuracy in distinguishing BC patients from the healthy controls (AUROC >0.7). Subsequently, the pIRS system with the five prognosis-associated immune-infiltrating cell was constructed, and Kaplan-Meier analysis demonstrated that the survival rate of low pIRS group was significantly higher than that of high pIRS group (p < 0.05). Based on age, pathologic stage and the pIRS values, the nomogram survival model was built. The AUROC value, Specificity value, Sensitivity value and C-index of the nomogram survival model were higher than 0.7000, and had a good predictive ability for BC. Finally, a total of 539 DEGs were identified, and significantly enriched in six pathways. The dIRS system and the pIRS system composed of immune cells might be critical for the diagnosis and prognosis of BC patients.