Predictive value of lymphocyte subsets and lymphocyte-to-monocyte ratio in assessing the efficacy of neoadjuvant therapy in breast cancer.

Lymphocyte subsets are the most intuitive expression of the body's immune ability, and the lymphocyte-to-monocyte ratio (LMR) also clearly reflect the degree of chronic inflammation activity. The purpose of this study is to investigate their predictive value of lymphocyte subsets and LMR to neoadjuvant therapy (NAT) efficacy in breast cancer patients. In this study, lymphocyte subsets and LMR were compared between breast cancer patients (n = 70) and benign breast tumor female populations (n = 48). Breast cancer patients were treated with NAT, and the chemotherapy response of the breast was evaluated using established criteria. The differences in lymphocyte subsets and LMR were also compared between pathological complete response (pCR) and non-pCR patients before and after NAT. Finally, data were analyzed using SPSS. The analytical results demonstrated that breast cancer patients showed significantly lower levels of CD3 + T cells, CD4 + T cells, CD4 + /CD8 + ratio, NK cells, and LMR compared to benign breast tumor women (P < 0.05). Among breast cancer patients, those who achieved pCR had higher levels of CD4 + T cells, NK cells, and LMR before NAT (P < 0.05). NAT increased CD4 + /CD8 + ratio and decreased CD8 + T cells in pCR patients (P < 0.05). Additionally, both pCR and non-pCR patients exhibited an increase in CD3 + T cells and CD4 + T cells after treatment, but the increase was significantly higher in pCR patients (P < 0.05). Conversely, both pCR and non-pCR patients experienced a decrease in LMR after treatment. However, this decrease was significantly lower in pCR patients (P < 0.05). These indicators demonstrated their predictive value for therapeutic efficacy. In conclusion, breast cancer patients experience tumor-related immunosuppression and high chronic inflammation response. But this phenomenon can be reversed to varying degrees by NAT. It has been found that lymphocyte subsets and LMR have good predictive value for pCR. Therefore, these markers can be utilized to identify individuals who are insensitive to NAT early on, enabling the adjustment of treatment plans and achieving precise breast cancer treatment.

PPIH acts as a potential predictive biomarker for patients with common solid tumors.

BACKGROUND: Our previous studies have indicated that mRNA and protein levels of PPIH are significantly upregulated in Hepatocellular Carcinoma (LIHC) and could act as predictive biomarkers for patients with LIHC. Nonetheless, the expression and implications of PPIH in the etiology and progression of common solid tumors have yet to be explored, including its potential as a serum tumor marker. METHODS: We employed bioinformatics analyses, augmented with clinical sample evaluations, to investigate the mRNA and protein expression and gene regulation networks of PPIH in various solid tumors. We also assessed the association between PPIH expression and overall survival (OS) in cancer patients using Kaplan-Meier analysis with TCGA database information. Furthermore, we evaluated the feasibility and diagnostic efficacy of PPIH as a serum marker by integrating serological studies with established clinical tumor markers. RESULTS: Through pan-cancer analysis, we found that the expression levels of PPIH mRNA in multiple tumors were significantly different from those in normal tissues. This study is the first to report that PPIH mRNA and protein levels are markedly elevated in LIHC, Colon adenocarcinoma (COAD), and Breast cancer (BC), and are associated with a worse prognosis in these cancer patients. Conversely, serum PPIH levels are decreased in patients with these tumors (LIHC, COAD, BC, gastric cancer), and when combined with traditional tumor markers, offer enhanced sensitivity and specificity for diagnosis. CONCLUSION: Our findings propose that PPIH may serve as a valuable predictive biomarker in tumor patients, and its secreted protein could be a potential serum marker, providing insights into the role of PPIH in cancer development and progression.

Atomically Co-dispersed nitrogen-doped carbon for sensitive electrochemical immunoassay of breast cancer biomarker CA15-3.

The development of an ultrasensitive and precise measurement of a breast cancer biomarker (cancer antigen 15-3; CA15-3) in complex human serum is essential for the early diagnosis of cancer in groups of healthy populations and the treatment of patients. However, currently available testing technologies suffer from insufficient sensitivity toward CA15-3, which severely limits early large-scale screening of breast cancer patients. We report a versatile electrochemical immunoassay method based on atomically cobalt-dispersed nitrogen-doped carbon (Co-NC)-modified disposable screen-printed carbon electrode (SPCE) with alkaline phosphatase (ALP) and its metabolite, ascorbic acid 2-phosphate (AAP), as the electrochemical labeling and redox signaling unit for sensitive detection of low-abundance CA15-3. During electrochemical detection by differential pulse voltammetry (DPV), it was found that the Co-NC-SPCE electrode did not have a current signal response to the AAP substrate; however, it had an extremely favorable response current to ascorbic acid (AA). Based on the above principle, the target CA15-3-triggered immunoassay enriched ALP-catalyzed AAP produces a large amount of AA, resulting in a significant change in the system current signal, thereby realizing the highly sensitive detection of CA15-3. Under the optimal AAP substrate concentration and ALP catalysis time, the Co-NC-SPCE-based electrochemical immunoassay demonstrated a good DPV current for CA15-3 in the assay interval of 1.0 mU/mL to 10,000 mU/mL, with a calculated limit of detection of 0.38 mU/mL. Since Co-NC-SPCE has an excellent DPV current response to AA and employs split-type scheme, the constructed electrochemical immunoassay has the merits of high preciseness and anti-interference, and its clinical diagnostic results are comparable to those of commercial kits.

Longitudinal analysis of circulating tumor cell numbers improves tracking metastatic breast cancer progression.

Hormone-responsive breast cancer represents the most common type and has the best prognosis, but still approximately 40% of patients with this type can develop distant metastases, dramatically worsening the patient's survival. Monitoring metastatic breast cancer (mBC) for signs of progression is an important part of disease management. Circulating tumor cell (CTC) detection and molecular characteristics gain importance as a diagnostic tool, but do not represent a clinical standard and its value as a predictor of progression is not yet established. The main objective of this study was to estimate the prognostic value of not only the CTC numbers, but also the dynamics of the CTC numbers in the same patient during the continuous evaluation of CTCs in patients with advanced breast cancer. The other objective was to assess the molecular changes in CTCs compared to primary tumor samples by genetic analysis of the seven genes associated with estrogen signaling pathway, mutations in which are often responsible for the resistance to endocrine therapy, and subsequent progression. This approach was taken to evaluate if genetic analysis of CTCs can be used in tracking the resistance, signaling that hormonal therapy should be replaced. Consequently, this report presents the results of a longitudinal CTC study based on three subsequent blood collections from 135 patients with metastatic breast cancer, followed by molecular analysis of the isolated single CTCs. CTCs were detected and isolated using an image-based, EpCAM-independent system CytoTrack; this approach allowed evaluation of EpCAM expression in detected CTCs. Isolated CTCs were subjected to NGS analysis to assess mutational changes. The results confirm the importance of the status of the CTC for progression-free survival and overall survival and provide new data on the dynamics of the CTC during a long monitoring period and in relation to clinical progression, highlighting the advantage of constant monitoring over the single count of CTC. Furthermore, high genetic and phenotypic inter- and intrapatient heterogeneity observed in CTCs suggest that metastatic lesions are divergent. High genetic heterogeneity in the matching CTC/primary tumor samples may indicate early dissemination. The tendency towards the accumulation of activating/oncogenic mutation in CTCs, leading to anti-estrogen resistant disease, was not confirmed in this study.

Inflammation at diagnosis and cognitive impairment two years later in breast cancer patients from the Canto-Cog study.

BACKGROUND: Inflammation could be related to cancer-related cognitive impairment (CRCI) and might be used as a predictive marker of long-term CRCI. We evaluated associations between inflammatory markers assessed at diagnosis of breast cancer and CRCI two years afterwards. METHODS: Newly diagnosed stage I-III patients with breast cancer from the French CANTO-Cog (Cognitive sub-study of CANTO, NCT01993498) were included at diagnosis (baseline). Serum inflammatory markers (IL-2, IL-4, IL-6, IL-8, IL-10, TNFα, CRP) were assessed at baseline. Outcomes at year 2 post-baseline included overall cognitive impairment (≥ 2 impaired domains) and the following domains: episodic memory, working memory, attention, processing speed, and executive functions. Multivariable logistic regression models evaluated associations between markers and outcomes, controlling for age, education, and baseline cognitive impairment. RESULTS: Among 200 patients, the mean age was 54 ± 11 years, with 127 (64%) receiving chemotherapy. Fifty-three (27%) patients had overall cognitive impairment at both timepoints. Overall cognitive impairment at year 2 was associated with high (> 3 mg/L) baseline CRP (OR = 2.84, 95%CI: 1.06-7.64, p = 0.037). In addition, associations were found between high CRP and processing speed impairment (OR = 2.47, 95%CI:1.05-5.87, p = 0.039), and between high IL-6 and episodic memory impairment (OR = 5.50, 95%CI:1.43-36.6, p = 0.010). CONCLUSIONS: In this cohort, high levels of CRP and IL-6 assessed at diagnosis were associated with overall CRCI, processing speed and episodic memory impairments two years later. These findings suggest a potential inflammatory basis for long-term CRCI. CRP may represent an easily measurable marker in clinical settings and be potentially used to screen patients at greater risk of persistent CRCI.

Atypical memory B cells increase in the peripheral blood of patients with breast cancer regardless of lymph node involvement.

BACKGROUND: Breast cancer is the most common cancer in females. The immune system has a crucial role in the fight against cancer. B and T cells, the two main components of the adaptive immunity, are critical players that specifically target tumor cells. However, B cells, in contrast to T cells, and their role in cancer inhibition or progression is less investigated. Accordingly, in this study, we assessed and compared the frequency of naïve and different subsets of memory B cells in the peripheral blood of patients with breast cancer and healthy women. RESULTS: We found no significant differences in the frequencies of peripheral CD19+ B cells between the patients and controls. However, there was a significant decrease in the frequency of CD19+IgM+ B cells in patients compared to the control group (P=0.030). Moreover, the patients exhibited higher percentages of atypical memory B cells (CD19+CD27‒IgM‒, P=0.006) and a non-significant increasing trend in switched memory B cells (CD19+CD27+IgM‒, P=0.074). Further analysis revealed a higher frequency of atypical memory B cells (aMBCs) in the peripheral blood of patients without lymph node involvement as well as those with a tumor size greater than 2cm or with estrogen receptor (ER) negative/progesterone receptor (PR) negative tumors, compared with controls (P=0.030, P=0.040, P=0.031 and P=0.054, respectively). CONCLUSION: Atypical memory B cells (CD19+CD27‒IgM‒) showed a significant increase in the peripheral blood of patients with breast cancer compared to the control group. This increase seems to be associated with tumor characteristics. Nevertheless, additional research is necessary to determine the precise role of these cells during breast cancer progression.

Predictive value of pretreatment circulating inflammatory response markers in the neoadjuvant treatment of breast cancer: meta-analysis.

BACKGROUND: Systemic inflammatory response markers have been found to have a prognostic role in several cancers, but their value in predicting the response to neoadjuvant chemotherapy in breast cancer is uncertain. A systematic review and meta-analysis of the literature was carried out to investigate this. METHODS: A systematic search of electronic databases was conducted to identify studies that explored the predictive value of circulating systemic inflammatory response markers in patients with breast cancer before commencing neoadjuvant therapy. A meta-analysis was undertaken for each inflammatory marker where three or more studies reported pCR rates in relation to the inflammatory marker. Outcome data are reported as ORs and 95% confidence intervals. RESULTS: A total of 49 studies were included, of which 42 were suitable for meta-analysis. A lower pretreatment neutrophil-to-lymphocyte ratio was associated with an increased pCR rate (pooled OR 1.66 (95% c.i. 1.32 to 2.09); P < 0.001). A lower white cell count (OR 1.96 (95% c.i. 1.29 to 2.97); P = 0.002) and a lower monocyte count (OR 3.20 (95% c.i. 1.71 to 5.97); P < 0.001) were also associated with a pCR. A higher lymphocyte count was associated with an increased pCR rate (OR 0.44 (95% c.i. 0.30 to 0.64); P < 0.001). CONCLUSION: The present study found the pretreatment neutrophil-to-lymphocyte ratio, white cell count, lymphocyte count, and monocyte count of value in the prediction of a pCR in the neoadjuvant treatment of breast cancer. Further research is required to determine their value in specific breast cancer subtypes and to establish optimal cut-off values, before their adoption in clinical practice.

Circulating tumor DNA: from discovery to clinical application in breast cancer.

Breast cancer (BC) stands out as the cancer with the highest incidence of morbidity and mortality among women worldwide, and its incidence rate is currently trending upwards. Improving the efficiency of breast cancer diagnosis and treatment is crucial, as it can effectively reduce the disease burden. Circulating tumor DNA (ctDNA) originates from the release of tumor cells and plays a pivotal role in the occurrence, development, and metastasis of breast cancer. In recent years, the widespread application of high-throughput analytical technology has made ctDNA a promising biomarker for early cancer detection, monitoring minimal residual disease, early recurrence monitoring, and predicting treatment outcomes. ctDNA-based approaches can effectively compensate for the shortcomings of traditional screening and monitoring methods, which fail to provide real-time information and prospective guidance for breast cancer diagnosis and treatment. This review summarizes the applications of ctDNA in various aspects of breast cancer, including screening, diagnosis, prognosis, treatment, and follow-up. It highlights the current research status in this field and emphasizes the potential for future large-scale clinical applications of ctDNA-based approaches.

Pleiotrophin serum level and metastasis occurrence in breast cancer patients.

BACKGROUND: Breast cancer (BC) cases in Makassar, Indonesia, are on the rise, with 2723 cases recorded in 2018. Tumor cells in the blood indicate metastasis, emphasizing the need for early diagnosis and monitoring. Pleiotrophin (PTN) is associated with various human malignancies, and recent studies suggest a correlation between PTN expression and advanced BC stages; therefore, PTN could serve as an independent predictor of metastasis. This study aimed to determine the correlation between serum PTN level, histopathological grading, and metastasis occurrence in BC patients in Makassar, Indonesia. METHODS: This study used an observational cross-sectional design. Pleiotrophin serum levels were examined using enzyme-linked immunosorbent assays. This study used a t-test and ROC curve analysis for the statistical tests. RESULTS: Of the 64 samples used in this study, metastasis was present in 26 cases and absent in 38 samples. The mean PTN serum levels in metastatic and non-metastatic breast cancer patients were 4.311 and 1.253, respectively. The PTN receiver operating characteristic curve showed an area under the curve of 2.47 ng/dL, which was statistically significant (p < 0.001). A significant relationship was found between PTN level and metastasis (p < 0.001). The correlation coefficient was 0.791, indicating a positive correlation. CONCLUSION: This study revealed that the serum PTN level among breast cancer patients had a cut-off value of 2.47 ng/dL. The research established a clear correlation between PTN level and metastasis occurrence in breast cancer patients, indicating a higher likelihood of distant metastasis with elevated PTN concentration.

Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing.

Circulating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically comprises thousands of gene expression reads per cell, which artificial intelligence algorithms can accurately analyze. This work presents machine-learning-based classifiers that differentiate CTCs from peripheral blood mononuclear cells (PBMCs) based on single cell RNA sequencing data. We developed four tree-based models and we trained and tested them on a dataset consisting of Smart-Seq2 sequenced data from primary tumor sections of breast cancer patients and PBMCs and on a public dataset with manually annotated CTC expression profiles from 34 metastatic breast patients, including triple-negative breast cancer. Our best models achieved about 95% balanced accuracy on the CTC test set on per cell basis, correctly detecting 133 out of 138 CTCs and CTC-PBMC clusters. Considering the non-invasive character of the liquid biopsy examination and our accurate results, we can conclude that our work has potential application value.

Association between red cell distribution width and all-cause mortality in patients with breast cancer: A retrospective analysis using MIMIC-IV 2.0.

PURPOSE: Investigating the association between red cell distribution width (RDW) and all-cause mortality in patients with breast cancer, to evaluate the potential clinical prognostic value of RDW. METHODS: Based on the RDW index, patients with breast cancer in the Medical Information Mart for Intensive Care (MIMIC-IV) database were categorized into quartiles. The primary outcomes included in-hospital mortality from all causes during the first six months, the first year, and the first three years. Cox hazards regression and restricted cubic spline (RCS) models were developed to investigate the effects of RDW on primary outcomes. RESULTS: The study included 939 patients (female). The 6-month, 1-year, and 3-year mortality rates were 14.0%, 21.4%, and 28.4%, respectively. Multivariate Cox proportional hazards analyses demonstrated that RDW exhibited an autonomous association with an increased risk of all-cause mortality. After adjusting for confounders, higher RDW quartiles were significantly associated with 6-month mortality (adjusted hazard ratio (HR), 3.197; 95% confidence interval (CI), 1.745-5.762; P < 0.001), 1-year mortality (adjusted HR, 2.978; 95% CI, 1.867-4.748; P < 0.001), and 3-year mortality (adjusted HR, 2.526; 95% CI, 1.701-3.750; P < 0.001). The RCS curves demonstrated that high RDW (> 14.6) was associated with a greater risk of all-cause mortality. Subgroup analyses revealed no statistically significant differences in the interactions between the subgroups. CONCLUSION: The study revealed a highly pronounced relationship between RDW and overall mortality, indicating its potential as an autonomous prognostic factor for increased mortality among patients with breast cancer.

Effect of combination of Beta Glucan and Lactobacillus rhamnosus HerizI on white blood cell counts and serum levels of IL-4 and IL-12 in women with breast cancer undergoing chemotherapy: A randomized double-blind placebo-controlled clinical trial.

BACKGROUND: Aim of this study was the isolation of native probiotic and determine the effect of combination of Beta Glucan and Lactobacillus rhamnosus Heriz I on White Blood Cell Counts and serum levels of IL-4and IL-12 in breast cancer women receiving Chemotherapy. METHODS: This study was randomized double-blind placebo-controlled clinical trial in 30 women with breast cancer. Women in the intervention group received two 10-mg capsules of soluble 1-3,1-6, D-beta glucan and one capsule of Lactobacillus rhamnosus strain Heriz I (2 × 107 CFU) daily and placebo group received placebo during 21days, interval between two courses of chemotherapy. White blood cells, neuthrophil, lymphocyte and monocyte counts, serum levels of IL-4 and IL-12 were measured before and after the study. RESULTS: We isolated Lactobacillus rhamnosus Heriz I from conventional yogurt of Heriz region and registered in NCBI GeneBank. After administration, in both groups white blood cells counts decreased. At the end of study, serum level of IL-4 was decreased in combination group compared to placebo (P = 0.005). Also, serum level of IL-12 in combination group increased non-significantly (P = 0.066). CONCLUSION: The findings suggest that combination of Beta Glucan and Lactobacillus rhamnosus Heriz I may be useful as immunomodulary supplements in chemotherapy patients however further studies were needed.

Hypermethylation of the Gene Body in SRCIN1 Is Involved in Breast Cancer Cell Proliferation and Is a Potential Blood-Based Biomarker for Early Detection and a Poor Prognosis.

Breast cancer is a leading cause of cancer mortality in women worldwide. Using the Infinium MethylationEPIC BeadChip, we analyzed plasma sample methylation to identify the SRCIN1 gene in breast cancer patients. We assessed SRCIN1-related roles and pathways for their biomarker potential. To verify the methylation status, quantitative methylation-specific PCR (qMSP) was performed on genomic DNA and circulating cell-free DNA samples, and mRNA expression analysis was performed using RT‒qPCR. The results were validated in a Western population; for this analysis, the samples included plasma samples from breast cancer patients from the USA and from The Cancer Genome Atlas (TCGA) cohort. To study the SRCIN1 pathway, we conducted cell viability assays, gene manipulation and RNA sequencing. SRCIN1 hypermethylation was identified in 61.8% of breast cancer tissues from Taiwanese patients, exhibiting specificity to this malignancy. Furthermore, its presence correlated significantly with unfavorable 5-year overall survival outcomes. The levels of methylated SRCIN1 in the blood of patients from Taiwan and the USA correlated with the stage of breast cancer. The proportion of patients with high methylation levels increased from 0% in healthy individuals to 63.6% in Stage 0, 80% in Stage I and 82.6% in Stage II, with a sensitivity of 78.5%, an accuracy of 90.3% and a specificity of 100%. SRCIN1 hypermethylation was significantly correlated with increased SRCIN1 mRNA expression (p < 0.001). Knockdown of SRCIN1 decreased the viability of breast cancer cells. SRCIN1 silencing resulted in the downregulation of ESR1, BCL2 and various cyclin protein expressions. SRCIN1 hypermethylation in the blood may serve as a noninvasive biomarker, facilitating early detection and prognosis evaluation, and SRCIN1-targeted therapies could be used in combination regimens for breast cancer patients.

Dosimetry and Biochemical Comparison of Early Radiation-Induced Lung Toxicity in Breast Cancer Patients Treated with 3D-CRT and IMRT: the Role of Serum Interleukin-6 and Pulmonary Surfactant Protein-D.

BACKGROUND: Radiation-induced lung disease is a potentially fatal, dose-limiting toxicity commonly seen after radiotherapy of thoracic malignancies, including breast cancer. AIM: To evaluate and compare the early lung toxicity induced by 3D-CRT and IMRT radiotherapy treatment modalities in breast cancer female patients using biochemical, dosimetry and clinical data. SUBJECTS AND METHODS: this study included 15 normal healthy controls, 15 breast cancer patients treated with IMRT, and 15 breast cancer patients treated with 3D-CRT. One blood sample was obtained from the control group and 3 blood samples were withdrawn from cases before RT, after RT and after 3 months of RT. RESULT: IMRT delivered higher radiation dose to the breast tumor and lower doses to the lung as an organ at risk. There was a non-significant increase in the serum levels of IL-6 before IMRT and 3D-CRT compared with its levels in the control group. There were significant increases in serum levels of IL-6 after RT (IMRT and 3DCRT) compared with its levels before RT. There was a non-significant decrease in the serum levels of IL-6 after 3 months of RT (IMRT and 3D-CRT) compared with its serum levels immediately after RT. There was a non-significant increase in the serum levels of SP-D before RT (IMRT and 3D-CRT) compared with its levels in the control group. There were significant-increases in serum levels of SP-D after RT (IMRT and 3D-CRT) compared with its levels before RT. There was a non-significant decrease in the serum levels of SP-D after 3 months of radiotherapy (IMRT and 3D-CRT) compared with its serum levels immediately after RT. CONCLUSION: serum of levels IL-6 and SP-D can be used to diagnose the occurrence of early lung toxicity due to radiotherapy and the rate of recovery from radiation pneumonitis is apparent in case of IMRT than 3D-CRT.

Assessment of Untargeted Metabolomics by Hydrophilic Interaction Liquid Chromatography-Mass Spectrometry to Define Breast Cancer Liquid Biopsy-Based Biomarkers in Plasma Samples.

An early diagnosis of cancer is fundamental not only in regard to reducing its mortality rate but also in terms of counteracting the progression of the tumor in the initial stages. Breast cancer (BC) is the most common tumor pathology in women and the second deathliest cancer worldwide, although its survival rate is increasing thanks to improvements in screening programs. However, the most common techniques to detect a breast tumor tend to be time-consuming, unspecific or invasive. Herein, the use of untargeted hydrophilic interaction liquid chromatography-mass spectrometry analysis appears as an analytical technique with potential use for the early detection of biomarkers in liquid biopsies from BC patients. In this research, plasma samples from 134 BC patients were compared with 136 from healthy controls (HC), and multivariate statistical analyses showed a clear separation between four BC phenotypes (LA, LB, HER2, and TN) and the HC group. As a result, we identified two candidate biomarkers that discriminated between the groups under study with a VIP > 1 and an AUC of 0.958. Thus, targeting the specific aberrant metabolic pathways in future studies may allow for better molecular stratification or early detection of the disease.

DNA-Binding Proteins and Passenger Proteins in Plasma DNA-Protein Complexes: Imprint of Parental Cells or Key Mediators of Carcinogenesis Processes?

Knowledge of the composition of proteins that interact with plasma DNA will provide a better understanding of the homeostasis of circulating nucleic acids and the various modes of interaction with target cells, which may be useful in the development of gene targeted therapy approaches. The goal of the present study is to shed light on the composition and architecture of histone-containing nucleoprotein complexes (NPCs) from the blood plasma of healthy females (HFs) and breast cancer patients (BCPs) and to explore the relationship of proteins with crucial steps of tumor progression: epithelial-mesenchymal transition (EMT), cell proliferation, invasion, cell migration, stimulation of angiogenesis, and immune response. MALDI-TOF mass spectrometric analysis of NPCs isolated from blood samples using affine chromatography was performed. Bioinformatics analysis showed that the shares of DNA-binding proteins in the compositions of NPCs in normal and cancer patients are comparable and amount to 40% and 33%, respectively; in total, we identified 38 types of DNA-binding motifs. Functional enrichment analysis using FunRich 3.13 showed that, in BCP blood, the share of DNA-binding proteins involved in nucleic acid metabolism increased, while the proportion of proteins involved in intercellular communication and signal transduction decreased. The representation of NPC passenger proteins in breast cancer also changes: the proportion of proteins involved in transport increases and the share of proteins involved in energy biological pathways decreases. Moreover, in the HF blood, proteins involved in the processes of apoptosis were more represented in the composition of NPCs and in the BCP blood-in the processes of active secretion. For the first time, bioinformatics approaches were used to visualize the architecture of circulating NPCs in the blood and to show that breast cancer has an increased representation of passenger proteins involved in EMT, cell proliferation, invasion, cell migration, and immune response. Using breast cancer protein data from the Human Protein Atlas (HPA) and DEPC, we found that 86% of NPC proteins in the blood of BCPs were not previously annotated in these databases. The obtained data may indirectly indicate directed protein sorting in NPCs, which, along with extracellular vesicles, can not only be diagnostically significant molecules for liquid biopsy, but can also carry out the directed transfer of genetic material from donor cells to recipient cells.

Unlocking the complete blood count as a risk stratification tool for breast cancer using machine learning: a large scale retrospective study.

Optimizing early breast cancer (BC) detection requires effective risk assessment tools. This retrospective study from Brazil showcases the efficacy of machine learning in discerning complex patterns within routine blood tests, presenting a globally accessible and cost-effective approach for risk evaluation. We analyzed complete blood count (CBC) tests from 396,848 women aged 40-70, who underwent breast imaging or biopsies within six months after their CBC test. Of these, 2861 (0.72%) were identified as cases: 1882 with BC confirmed by anatomopathological tests, and 979 with highly suspicious imaging (BI-RADS 5). The remaining 393,987 participants (99.28%), with BI-RADS 1 or 2 results, were classified as controls. The database was divided into modeling (including training and validation) and testing sets based on diagnostic certainty. The testing set comprised cases confirmed by anatomopathology and controls cancer-free for 4.5-6.5 years post-CBC. Our ridge regression model, incorporating neutrophil-lymphocyte ratio, red blood cells, and age, achieved an AUC of 0.64 (95% CI 0.64-0.65). We also demonstrate that these results are slightly better than those from a boosting machine learning model, LightGBM, plus having the benefit of being fully interpretable. Using the probabilistic output from this model, we divided the study population into four risk groups: high, moderate, average, and low risk, which obtained relative ratios of BC of 1.99, 1.32, 1.02, and 0.42, respectively. The aim of this stratification was to streamline prioritization, potentially improving the early detection of breast cancer, particularly in resource-limited environments. As a risk stratification tool, this model offers the potential for personalized breast cancer screening by prioritizing women based on their individual risk, thereby indicating a shift from a broad population strategy.

Exploring the Immunological Profile in Breast Cancer: Recent Advances in Diagnosis and Prognosis through Circulating Tumor Cells.

This review offers a comprehensive exploration of the intricate immunological landscape of breast cancer (BC), focusing on recent advances in diagnosis and prognosis through the analysis of circulating tumor cells (CTCs). Positioned within the broader context of BC research, it underscores the pivotal role of the immune system in shaping the disease's progression. The primary objective of this investigation is to synthesize current knowledge on the immunological aspects of BC, with a particular emphasis on the diagnostic and prognostic potential offered by CTCs. This review adopts a thorough examination of the relevant literature, incorporating recent breakthroughs in the field. The methodology section succinctly outlines the approach, with a specific focus on CTC analysis and its implications for BC diagnosis and prognosis. Through this review, insights into the dynamic interplay between the immune system and BC are highlighted, with a specific emphasis on the role of CTCs in advancing diagnostic methodologies and refining prognostic assessments. Furthermore, this review presents objective and substantiated results, contributing to a deeper understanding of the immunological complexity in BC. In conclusion, this investigation underscores the significance of exploring the immunological profile of BC patients, providing valuable insights into novel advances in diagnosis and prognosis through the utilization of CTCs. The objective presentation of findings emphasizes the crucial role of the immune system in BC dynamics, thereby opening avenues for enhanced clinical management strategies.

Ultrasensitive and Rapid Circulating Tumor DNA Liquid Biopsy Using Surface-Confined Gene Amplification on Dispersible Magnetic Nano-Electrodes.

Circulating tumor DNA (ctDNA) detection has been acknowledged as a promising liquid biopsy approach for cancer diagnosis, with various ctDNA assays used for early detection and treatment monitoring. Dispersible magnetic nanoparticle-based electrochemical detection methods have been proposed as promising candidates for ctDNA detection based on the detection performance and features of the platform material. This study proposes a nanoparticle surface-localized genetic amplification approach by integrating Fe3O4-Au core-shell nanoparticles into polymerase chain reactions (PCR). These highly dispersible and magnetically responsive superparamagnetic nanoparticles act as nano-electrodes that amplify and accumulate target ctDNA in situ on the nanoparticle surface upon PCR amplification. These nanoparticles are subsequently captured and subjected to repetitive electrochemical measurements to induce reconfiguration-mediated signal amplification for ultrasensitive (∼3 aM) and rapid (∼7 min) metastatic breast cancer ctDNA detection in vitro. The detection platform can also detect metastatic biomarkers from in vivo samples, highlighting the potential for clinical applications and further expansion to rapid and ultrasensitive multiplex detection of various cancers.

Dysregulation of miR-122, miR-574 and miR-375 in Egyptian patients with breast cancer.

BACKGROUND: The early detection of breast cancer (BC) is receiving global attention, creating an urgent need for more sensitive and comprehensive strategies for preventive intervention, therapy assessment, and prognosis prediction. Aberrant expression of miRNAs has been observed in various malignancies and may be potential targets for therapy. Our study aims to examine the expression profiles of miR-375, miR-574-3p, and miR-122 in the sera of Egyptian women with BC, benign breast lesions, and a control group. We hope to determine if these miRNAs can serve as minimally invasive biomarkers for BC. METHODS: This is a case-control study in which 77 patients with newly diagnosed BC, 20 patients with benign breast tumors, and 30 normal healthy subjects as controls were recruited from the outpatient clinic of the National Cancer Institute. The assessment of miRNAs was conducted using RT-PCR (Applied Biosystems). RESULTS: The expression level of miRNA-122 was significantly upregulated in the BC group, while the expression levels of miRNA-574 and miRNA-375 showed significant downregulation in BC patients. Serum miR-122 and miRNA-375 were able to distinguish breast cancer from the benign and control groups in ROC curve analysis, with AUCs of 0.786 and 0.796, respectively. Our results also showed that serum miR-122 and miR-574 are significant predictor variables in the multivariate analysis, after adjusting for age. CONCLUSIONS: Our findings suggest that miR-122 may act as an onco-microRNA, while miR-574 and miR-375 may have a main tumour suppressor role. The studied miRNAs may serve as minimally invasive biomarkers for cases of breast cancer and as promising potential therapeutic targets for breast cancer.