Current and Developing Liquid Biopsy Techniques for Breast Cancer

Liquid biopsy biomarkers in breast cancer: An overview of systematic reviews

Breast cancer (BC) is the leading type of cancer affecting women globally and remains a significant cause of death. The diagnostic accuracy of liquid biopsy (LB) in the diagnosis of BC has not been well established. This overview synthesizes and critically evaluates the diagnostic test accuracy (DTA) of LB biomarkers in individuals with BC. Of 433 systematic reviews, eleven were included, assessing Fourier transform infrared (FTIR) spectroscopy, circulating tumor cells (CTCs), cell-free DNA (cfDNA), and microRNAs (miRNAs). The overall methodological quality of most of the reviews included was rated as critically low (n = 9, 81.8 %), and the remaining reviews were ranked as low and moderate. Key findings include CTCs with moderate sensitivity (0.50, 95 % confidence interval (CI) 0.48-0.52) and high specificity (0.93, 95 % CI: 0.92-0.95) with moderate certainty; cfDNA assays with high sensitivity (0.71-0.86) and specificity (0.88) with high certainty; FTIR assays with high sensitivity (0.97, 95 % CI: 0.94-0.96) and specificity (0.92, 95 % CI: 0.88-0.95) but low certainty. The miRNAs showed moderate to high sensitivity, while miR-21 had high specificity. Our overview indicates that identified liquid biopsies could serve as valuable tools for the diagnosis of breast cancer.

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes. Some genes and rules were analyzed and supported by recent literature, providing new references for studying breast cancer.

Diagnostic value of 5 miRNAs combined detection for breast cancer

Background

Breast cancer (BC) is the prevailing malignant tumor, with its prevalence and death rate steadily rising over time. BC often does not show obvious symptoms in its early stages and is difficult to distinguish from benign breast disease. We aimed to find a distinct group of miRNAs utilizing serum as a non-invasive biomarker for early BC diagnosis.

Methods

Herein, we mainly include the screening stage, testing stage, and verification stage. In the screening stage, 8 miRNAs associated with BC were selected and analyzed via literature reading, and the expression of the above miRNAs in BC was further verified by bioinformatics and included in the research analysis. In the testing phase, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was deployed to select the five miRNAs with the most significant expression differences in 15 BC patients and 15 benign breast controls to proceed to the next stage. In a subsequent validation phase, the five miRNAs obtained from serum samples from an additional 75 BC patients and 50 benign control patients were evaluated using RT-qPCR. The diagnostic capacity, specificity, and sensitivity of candidate miRNAs were estimated with the receiver operating characteristic (ROC) curve and area under the curve (AUC). Finally, the optimal diagnostic combination model with high sensitivity and strong specificity was constructed by using the above 5 miRNAs.

Results

The BC patients reported a significant decline in mir-10b-5p, mir-133a-3p, mir-195-5p, and mir-155-3p levels in serum levels contrasted with those in benign controls. Additionally, BC patients experienced elevated mir-195-3p levels than in benign controls. We implemented ROC analysis to evaluate its diagnostic capacity for BC. We demonstrated that all five miRNAs had robust diagnostic capability, with an AUC above 0.8. We developed a conclusive diagnostic combination model consisting of these 5 miRNAs in order to enhance the diagnosis accuracy. This model demonstrated a high diagnostic value, as shown by an AUC of 0.948.

Conclusion

The serum biomarker panels composed of five miRNAs identified in this study (mir-10b-5p, mir-133a-3p, mir-195-5p, mir-195-3p, and mir-155-3p) provide hope for early, non-invasive, and accurate diagnosis of BC.

Quantitative Analysis of Cell-Free RNA at Attomolar Level Using CRISPR/Cas Digital Imaging Platform

Quantitative analysis of cell-free RNA (cfRNA) in plasma sample can be used for screening, diagnosing, and prognosticating of multiple diseases. Here, we report a quantitative CRISPR/Cas digital imaging platform (qCasdip) for the detection of various cfRNAs, including circular RNAs and miRNAs, in clinical samples at the attomolar (aM) level without the need for preamplification. Digital counting strategy provides qCasdip quantitative ability with a linear detection range of 102-106 aM. Meanwhile, qCasdip demonstrated cfRNA profiling in clinical plasma samples, improving the diagnosis of breast cancer. These data highlight the potential of qCasdip to quantitatively assess the molecular patterns of specific cfRNA panels in plasma, thereby providing a novel liquid biopsy solution to enhance disease diagnosis.

Predictive models and biomarkers for survival in stage III breast cancer: a review of clinical applications and future directions

Stage III breast cancer, characterized by locally advanced tumors and potential regional lymph node involvement, presents a formidable challenge to both patients and healthcare professionals. Accurate prediction of survival outcomes is crucial for guiding treatment decisions and optimizing patient care. This publication explores the potential clinical utility of predictive tools, encompassing genetic markers, imaging techniques, and clinical parameters, to improve survival outcome predictions in stage III breast cancer. Multimodal approaches, integrating these tools, hold the promise of delivering more precise and personalized predictions. Despite the inherent challenges, such as data standardization and genetic heterogeneity, the future offers opportunities for refinement, driven by precision medicine, artificial intelligence, and global collaboration. The goal is to empower healthcare providers to make informed treatment decisions, ultimately leading to improved survival outcomes and a brighter horizon for individuals facing this challenging disease.

From Biosensors to Robotics: Pioneering Advances in Breast Cancer Management

Breast cancer stands as the most prevalent form of cancer amongst females, constituting more than one-third of all cancer cases affecting women. It causes aberrant cell development, which can assault or spread to other sections of the body, perhaps leading to the patient's death. Based on research findings, timely detection can diminish the likelihood of mortality and enhance the quality of healthcare provided for the illness. However, current technologies can only identify cancer at an advanced stage. Consequently, there is a substantial demand for rapid and productive approaches to detecting breast cancer. Researchers are actively pursuing precise and timely methods for the diagnosis of breast cancer, aiming to achieve enhanced accuracy and early detection. Biosensor technology can allow for the speedy and accurate diagnosis of cancer-related cells, as well as a more sensitive and specialized technique for generating them. Additionally, numerous treatments for breast cancer are depicted such as herbal therapy, nanomaterial-based drug delivery, miRNA targeting, CRISPR technology, immunotherapy, and precision medicine. Early detection and efficient therapy are necessary to manage such a severe illness properly.

Next-generation biomarkers for prognostic and potential therapeutic enhancement in Triple negative breast cancer

Triple-negative breast carcinoma (TNBC) is one of the most challenging subtypes of breast carcinoma and it has very limited therapeutic options as it is highly aggressive. The prognostic biomarkers are crucial for early diagnosis of the tumor, it also helps in anticipating the trajectory of the illness and optimizing the therapy options. Several therapeutic biomarkers are being used. Among them, the next-generation biomarkers that include Circulating tumor (ct) DNA, glycogen, lipid, and exosome biomarkers provide intriguing opportunities for enhancing the prognosis of TNBC. Lipid and glycogen biomarkers serve as essential details on the development of the tumor along with the efficacy of the treatment, as it exhibits metabolic alteration linked to TNBC. Several types of biomarkers have predictive abilities in TNBC. Elevated levels are associated with worse outcomes. ctDNA being a noninvasive biomarker reveals the genetic composition of the tumor, as well as helps to monitor the progression of the disease. Traditional therapies are ineffective in TNBC due to a lack of receptors, targeted drug delivery provides a tailored approach to overcome drug resistance and site-specific action by minimizing the side effects in TNBC treatment. This enhances therapeutic outcomes against the aggressive nature of breast cancer. This paper includes all the recent biomarkers which has been researched so far in TNBC and the state of art for TNBC which is explored.

Colorimetric and Electrochemical Dual-Mode Detection of Thioredoxin 1 Based on the Efficient Peroxidase-Mimicking and Electrocatalytic Property of Prussian Blue Nanoparticles

As a potent detection method for cancer biomarkers in physiological fluid, a colorimetric and electrochemical dual-mode sensing platform for breast cancer biomarker thioredoxin 1 (TRX1) was developed based on the excellent peroxidase-mimicking and electrocatalytic property of Prussian blue nanoparticles (PBNPs). PBNPs were hydrothermally synthesized using K3[Fe(CN)6] as a precursor and polyvinylpyrrolidone (PVP) as a capping agent. The synthesized spherical PBNPs showed a significant peroxidase-like activity, having approximately 20 and 60% lower Km values for 3,3',5,5'-tetramethylbenzidine (TMB) and H2O2, respectively, compared to those of horseradish peroxidase (HRP). The PBNPs also enhanced the electron transfer on the electrode surface. Based on the beneficial features, PBNPs were used to detect target TRX1 via sandwich-type immunoassay procedures. Using the strategies, TRX1 was selectively and sensitively detected, yielding limit of detection (LOD) values as low as 9.0 and 6.5 ng mL-1 via colorimetric and electrochemical approaches, respectively, with a linear range of 10-50 ng mL-1 in both strategies. The PBNP-based TRX1 immunoassays also exhibited a high degree of precision when applied to real human serum samples, demonstrating significant potentials to replace conventional HRP-based immunoassay systems into rapid, robust, reliable, and convenient dual-mode assay systems which can be widely utilized for the identification of important target molecules including cancer biomarkers.

The expansion of liquid biopsies to vascular care: an overview of existing principles, techniques and potential applications to vascular malformation diagnostics

Vascular malformations are congenital lesions that occur due to mutations in major cellular signalling pathways which govern angiogenesis, cell proliferation, motility, and cell death. These pathways have been widely studied in oncology and are substrates for various small molecule inhibitors. Given their common molecular biology, there is now a potential to repurpose these cancer drugs for vascular malformation care; however, a molecular diagnosis is required in order to tailour specific drugs to the individual patient's mutational profile. Liquid biopsies (LBs), emerging as a transformative tool in the field of oncology, hold significant promise in this feat. This paper explores the principles and technologies underlying LBs and evaluates their potential to revolutionize the management of vascular malformations. The review begins by delineating the fundamental principles of LBs, focusing on the detection and analysis of circulating biomarkers such as cell-free DNA, circulating tumor cells, and extracellular vesicles. Subsequently, an in-depth analysis of the technological advancements driving LB platforms is presented. Lastly, the paper highlights the current state of research in applying LBs to various vascular malformations, and uses the aforementioned principles and techniques to conceptualize a liquid biopsy framework that is unique to vascular malformation research and clinical care.

Clinical Impact of New Treatment Strategies for HER2-Positive Metastatic Breast Cancer Patients with Resistance to Classical Anti-HER Therapies

HER2-positive breast cancer accounts for 15-20% of all breast cancer cases. This subtype is characterized by an aggressive behavior and poor prognosis. Anti-HER2 therapies have considerably improved the natural course of the disease. Despite this, relapse still occurs in around 20% of patients due to primary or acquired treatment resistance, and metastasis remains an incurable disease. This article reviews the main mechanisms underlying resistance to anti-HER2 treatments, focusing on newer HER2-targeted therapies. The progress in anti-HER2 drugs includes the development of novel antibody-drug conjugates with improvements in the conjugation process and novel linkers and payloads. Moreover, trastuzumab deruxtecan has enhanced the efficacy of trastuzumab emtansine, and the new drug trastuzumab duocarmazine is currently undergoing clinical trials to assess its effect. The combination of anti-HER2 agents with other drugs is also being evaluated. The addition of immunotherapy checkpoint inhibitors shows some benefit in a subset of patients, indicating the need for useful biomarkers to properly stratify patients. Besides, CDK4/6 and tyrosine kinase inhibitors are also included in the design of new treatment strategies. Lapitinib, neratinib and tucatinib have been approved for HER2-positive metastasis patients, however clinical trials are currently ongoing to optimize combined strategies, to reduce toxicity, and to better define the useful setting. Clinical research should be strengthened along with the discovery and validation of new biomarkers, as well as a deeper understanding of drug resistance and action mechanisms.

The diagnostic significance of circulating miRNAs and metabolite profiling in early prediction of breast cancer in Egyptian women

OBJECTIVE

Breast cancer (BC) is one of the most commonly diagnosed solid malignancies in women worldwide.

PURPOSE

Finding new non-invasive circulating diagnostic biomarkers will facilitate the early prediction of BC and provide valuable insight into disease progression and response to therapy using a safe and more accessible approach available every inspection time. Therefore, our present study aimed to investigate expression patterns of potentially circulating biomarkers that can differentiate well between benign, malignant, and healthy subjects.

METHODS

To achieve our target, quantitative analyses were performed for some circulating biomarkers which have a role in the proliferation and tumor growth, as well as, glutamic acid, and human epidermal growth receptor 2 (HER2) in blood samples of BC patients in comparison to healthy controls using qRT-PCR, liquid chromatography/mass spectrometry (LC/MS/MS), and ELISA.

RESULTS

Our findings showed that the two miRNAs (miRNA-145, miRNA-382) were expressed at lower levels in BC sera than healthy control group, while miRNA-21 was expressed at higher levels in BC patients than control subjects. Area under ROC curves of BC samples revealed that AUC of miRNA-145, miRNA-382, miRNA-21, and glutamic acid was evaluated to equal 0.99, 1.00, 1.00 and 1.00, respectively. Besides, there was a significantly positive correlation between miRNA-145 and miRNA-382 (r = 0.737), and a highly significant positive correlation between miRNA-21 and glutamic acid (r = 0.385).

CONCLUSION

Based on our results, we conclude that the detection of serum miRNA-145, -382 and -21 as a panel along with glutamic acid, and circulating HER2 concentrations could be useful as a non-invasive diagnostic profiling for early prediction of breast cancer in Egyptian patients. It can provide an insight into disease progression, discriminate between malignancy and healthy control, and overcome the use limitations (low sensitivity and specificity, repeated risky exposure, and high cost) of other detecting tools, including mammography, magnetic resonance imaging, and ultrasound.

CNT and Graphene-Based Transistor Biosensors for Cancer Detection: A Review

An essential aspect of successful cancer diagnosis is the identification of malignant tumors during the early stages of development, as this can significantly diminish patient mortality rates and increase their chances of survival. This task is facilitated by cancer biomarkers, which play a crucial role in determining the stage of cancer cells, monitoring their growth, and evaluating the success of treatment. However, conventional cancer detection methods involve several intricate steps, such as time-consuming nucleic acid amplification, target detection, and a complex treatment process that may not be appropriate for rapid screening. Biosensors are emerging as promising diagnostic tools for detecting cancer, and carbon nanotube (CNT)- and graphene-based transistor biosensors have shown great potential due to their unique electrical and mechanical properties. These biosensors have high sensitivity and selectivity, allowing for the rapid detection of cancer biomarkers at low concentrations. This review article discusses recent advances in the development of CNT- and graphene-based transistor biosensors for cancer detection.

Exploring the Potential Role of Circulating microRNAs as Biomarkers for Predicting Clinical Response to Neoadjuvant Therapy in Breast Cancer

Breast cancer (BC) is a leading cause of cancer-related deaths among women worldwide. Neoadjuvant therapy (NAT) is increasingly being used to reduce tumor burden prior to surgical resection. However, current techniques for assessing tumor response have significant limitations. Additionally, drug resistance is commonly observed, raising a need to identify biomarkers that can predict treatment sensitivity and survival outcomes. Circulating microRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and have been shown to play a significant role in cancer progression as tumor inducers or suppressors. The expression of circulating miRNAs has been found to be significantly altered in breast cancer patients. Moreover, recent studies have suggested that circulating miRNAs can serve as non-invasive biomarkers for predicting response to NAT. Therefore, this review provides a brief overview of recent studies that have demonstrated the potential of circulating miRNAs as biomarkers for predicting the clinical response to NAT in BC patients. The findings of this review will strengthen future research on developing miRNA-based biomarkers and their translation into medical practice, which could significantly improve the clinical management of BC patients undergoing NAT.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

Intratumoral Heterogeneity in Lung Cancer

The diagnosis and treatment of lung cancer (LC) is always a challenge. The difficulty in the decision of therapeutic schedule and diagnosis is directly related to intratumoral heterogeneity (ITH) in the progression of LC. It has been proven that most tumors emerge and evolve under the pressure of their living microenvironment, which involves genetic, immunological, metabolic, and therapeutic components. While most research on ITH revealed multiple mechanisms and characteristic, a systemic exposition of ITH in LC is still hard to find. In this review, we describe how ITH in LC develops from the perspective of space and time. We discuss elaborate details and affection of every aspect of ITH in LC and the relationship between them. Based on ITH in LC, we describe a more accurate multidisciplinary therapeutic strategy on LC and provide the newest opinion on the potential approach of LC therapy.

Surface-Enhanced Raman Analysis of Uric Acid and Hypoxanthine Analysis in Fractionated Bodily Fluids

In recent years, the disease burden of hyperuricemia has been increasing, especially in high-income countries and the economically developing world with a Western lifestyle. Abnormal levels of uric acid and hypoxanthine are associated with many diseases, and therefore, to demonstrate improved methods of uric acid and hypoxanthine detection, three different bodily fluids were analysed using surface-enhanced Raman spectroscopy (SERS) and high-performance liquid chromatography (HPLC). Gold nanostar suspensions were mixed with series dilutions of uric acid and hypoxanthine, 3 kDa centrifugally filtered human blood serum, urine and saliva. The results show that gold nanostars enable the quantitative detection of the concentration of uric acid and hypoxanthine in the range 5-50 μg/mL and 50-250 ng/mL, respectively. The peak areas of HPLC and maximum peak intensity of SERS have strongly correlated, notably with the peaks of uric acid and hypoxanthine at 1000 and 640 cm^-1, respectively. The r² is 0.975 and 0.959 for uric acid and hypoxanthine, respectively. Each of the three body fluids has a number of spectral features in common with uric acid and hypoxanthine. The large overlap of the spectral bands of the SERS of uric acid against three body fluids at spectra peaks were at 442, 712, 802, 1000, 1086, 1206, 1343, 1436 and 1560 cm^-1. The features at 560, 640, 803, 1206, 1290 and 1620 cm^-1 from hypoxanthine were common to serum, saliva and urine. There is no statistical difference between HPLC and SERS for determination of the concentration of uric acid and hypoxanthine (p > 0.05). For clinical applications, 3 kDa centrifugal filtration followed by SERS can be used for uric acid and hypoxanthine screening is, which can be used to reveal the subtle abnormalities enhancing the great potential of vibrational spectroscopy as an analytical tool. Our work supports the hypnosis that it is possible to obtain the specific concentration of uric acid and hypoxanthine by comparing the SER signals of serum, saliva and urine. In the future, the analysis of other biofluids can be employed to detect biomarkers for the diagnosis of systemic pathologies.

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.

Clinical application and detection techniques of liquid biopsy in gastric cancer

Gastric cancer (GC) is one of the most common tumors worldwide and the leading cause of tumor-related mortality. Endoscopy and serological tumor marker testing are currently the main methods of GC screening, and treatment relies on surgical resection or chemotherapy. However, traditional examination and treatment methods are more harmful to patients and less sensitive and accurate. A minimally invasive method to respond to GC early screening, prognosis monitoring, treatment efficacy, and drug resistance situations is urgently needed. As a result, liquid biopsy techniques have received much attention in the clinical application of GC. The non-invasive liquid biopsy technique requires fewer samples, is reproducible, and can guide individualized patient treatment by monitoring patients' molecular-level changes in real-time. In this review, we introduced the clinical applications of circulating tumor cells, circulating free DNA, circulating tumor DNA, non-coding RNAs, exosomes, and proteins, which are the primary markers in liquid biopsy technology in GC. We also discuss the current limitations and future trends of liquid biopsy technology as applied to early clinical biopsy technology.

The Role of miRNAs in the Prognosis of Triple-Negative Breast Cancer: A Systematic Review and Meta-Analysis

Breast cancer is one of the most common malignancies among women around the world. The basal or triple-negative subtype (TNBC) is a heterogeneous group of tumors, characterized by its aggressive and metastatic nature, with low survival and worse prognosis. Research on genetic biomarkers, such as microRNAs (miRs) in TNBC, demonstrate their relevance in the prognosis of the disease. Therefore, the objective of this research was to verify the role of miRs in the prognosis of TNBC. A search was carried out in the PubMed (MEDLINE), Web of Science, and Scopus databases, with articles in the English language from 2010 to 2022. Only articles that analyzed the role of miRNAs in the prognosis of TNBC and that met the criteria of the MOOSE method were included. For the preparation and planning of this systematic review, a PRISMA checklist and the MOOSE method were used. The Newcastle-Ottawa Scale was used to analyze the quality of the included studies. The excluded criteria considered were: (1) studies that presented duplication in the databases; (2) reviews of the literature, clinical case reports, meta-analyses, conference abstracts, letters to the editor, theses, dissertations, and book chapters; (3) studies that stratified only women diagnosed with other subtypes of breast cancer subtypes; (4) experiments without a control or comparison group. After the bibliographic survey of the 2.274 articles found, 43 articles met the inclusion criteria, totaling 5421 patients with TNBC analyzed for this review. Six miRs (miR-155, miR-21, miR-27a/b/, miR-374a/b, miR-30a/c/e, and miR-301a) were included in the meta-analysis. A low expression of miR-155 was associated with reduced overall survival (OS) (HR: 0.68, 95% CI: 0.58-0.81). A high expression of miR-21 was a predictor of OS reduction (HR: 2.56; 95% CI: 1.49-4.40). In addition, high levels of miR-27a/b and miR-301a/b were associated with lower OS, while the decreased expression levels of miR-30 and miR-374a/b were associated with worse relapse-free survival (RFS) and shorter disease-free survival (DFS), respectively. The present study revealed that miRs play essential roles in the development of metastases, in addition to acting as suppressors of the disease, thus improving the prognosis of TNBC. However, the clinical application of these findings has not yet been investigated.

Cancer Genomics

In the past decade, genomics has fundamentally changed our view of cancer biology, allowing comprehensive analyses of mutations, copy number alterations, structural variants, gene expression and DNA methylation profiles in large-scale studies across different cancer types. Efforts like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) have fostered international collaborations for cancer genomic analyses and have generated public databases that give scientists around the world access to thoroughly curated data, which have been extensively used as a tool for further hypothesis driven research on several aspects of cancer biology. In parallel, some of these findings are being translated into specific clinical benefits for cancer patients. In this review, we provide a brief historical description of the evolution of international public cancer genome projects and related databases, as well as we discuss about their impact on general cancer research.

The role and application of small extracellular vesicles in breast cancer

Breast cancer (BC) is the most common malignancy and the leading cause of cancer-related deaths in women worldwide. Currently, patients’ survival remains a challenge in BC due to the lack of effective targeted therapies and the difficult condition of patients with higher aggressiveness, metastasis and drug resistance. Small extracellular vesicles (sEVs), which are nanoscale vesicles with lipid bilayer envelopes released by various cell types in physiological and pathological conditions, play an important role in biological information transfer between cells. There is growing evidence that BC cell-derived sEVs may contribute to the establishment of a favorable microenvironment that supports cancer cells proliferation, invasion and metastasis. Moreover, sEVs provide a versatile platform not only for the diagnosis but also as a delivery vehicle for drugs. This review provides an overview of current new developments regarding the involvement of sEVs in BC pathogenesis, including tumor proliferation, invasion, metastasis, immune evasion, and drug resistance. In addition, sEVs act as messenger carriers carrying a variety of biomolecules such as proteins, nucleic acids, lipids and metabolites, making them as potential liquid biopsy biomarkers for BC diagnosis and prognosis. We also described the clinical applications of BC derived sEVs associated MiRs in the diagnosis and treatment of BC along with ongoing clinical trials which will assist future scientific endeavors in a more organized direction.

Potential utility of miRNAs for liquid biopsy in breast cancer

Breast cancer (BC) remains the most prevalent malignancy due to its incidence rate, recurrence, and metastasis in women. Conventional strategies of cancer detection– mammography and tissue biopsy lack the capacity to detect the complete cancer genomic landscape. Besides, they often give false- positive or negative results. The presence of this and other disadvantages such as invasiveness, high-cost, and side effects necessitates developing new strategies to overcome the BC burden. Liquid biopsy (LB) has been brought to the fore owing to its early detection, screening, prognosis, simplicity of the technique, and efficient monitoring. Remarkably, microRNAs (miRNAs)– gene expression regulators seem to play a major role as biomarkers detected in the samples of LB. Particularly, miR-21 and miR-155 among other possible candidates seem to serve as favorable biomarkers in the diagnosis and prognosis of BC. Hence, this review will assess the potential utility of miRNAs as biomarkers and will highlight certain promising candidates for the LB approach in the diagnosis and management of BC that may optimize the patient outcome.

Circulating tumor DNA for breast cancer: Review of active clinical trials

BACKGROUND

The new diagnostic concept of liquid biopsy is based on the analysis of circulating tumor cells (CTCs) and cell-free DNA (ctDNA). In addition to providing a more comprehensive view of the tumor characteristics including molecular variations, ctDNA analysis through liquid biopsies may also allow for a non-invasive, rapid, and cost-effective identification of biomarkers for tumor detection and monitoring of tumor progression.

OBJECTIVE

In this review, we summarize key active clinical trial studies involving utilization of ctDNA derived from liquid biopsy in the early and metastatic breast cancer setting. With this, we also provide a brief overview of the potential future implementations of the LB technology and outlining how ctDNA analysis needs to be standardized through the performance of similar clinical studies.

METHODS

A review was conducted on Clinicaltrials.gov to identify active trials related to use of circulating tumor DNA (ctDNA) for breast cancer. Search terms included "breast cancer," "liquid biopsy," and "ctDNA."

CONCLUSION

While LB is gaining traction in many cancer settings, its use in BC is still early and warrants more investigation in breast cancer diagnostic and treatment settings, including early detection of disease recurrence.