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.

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.

hTERT gene methylation in circulating DNA, tumor, and surrounding tissue in breast cancer: a prospective study.

BACKGROUND: The human telomerase reverse transcriptase (hTERT) enzyme, encoded by the hTERT gene, synthesizes protective telomeric sequences on chromosomes and plays a fundamental role in cancer formation. Methylation of the hTERT gene has an upregulatory effect, increasing hTERT enzyme synthesis and allowing continuous tumor cell division. OBJECTIVE: In a group of patients with breast cancer, we aimed to analyze the methylation status of hTERT in the tumor, surrounding tissue, and circulating free deoxyribonucleic acid (cfDNA) of blood collected on the day of mastectomy and then approximately one year later. DESIGN AND SETTING: A prospective study was conducted at a university hospital in Rio de Janeiro, Brazil. METHODS: Samples were collected from 15 women with breast cancer on the day of mastectomy and approximately one year postoperatively. cfDNA was analyzed by sodium bisulfite conversion, followed by polymerase chain reaction, electrophoresis, and silver nitrate staining. RESULTS: Methylation of hTERT was detected in the tumors and surrounding tissues of all 15 patients. Five patients displayed hTERT methylation in the cfDNA from the blood of the first collection. Of the ten patients who returned for the second collection, three showed methylation. Two patients with methylation in the first collection did not display methylation in the second collection. One patient with no methylation in the first collection displayed methylation in the second collection, and one patient had a diminished level of methylation in the second collection. CONCLUSION: Only one-third of patients displayed methylation in their cfDNA, which may be related to the success of chemotherapy.

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.

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.

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.

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.

Serial Postoperative Circulating Tumor DNA Assessment Has Strong Prognostic Value During Long-Term Follow-Up in Patients With Breast Cancer.

PURPOSE: Here, we report the sensitivity of a personalized, tumor-informed circulating tumor DNA (ctDNA) assay (Signatera) for detection of molecular relapse during long-term follow-up of patients with breast cancer. METHODS: A total of 156 patients with primary breast cancer were monitored clinically for up to 12 years after surgery and adjuvant chemotherapy. Semiannual blood samples were prospectively collected, and analyzed retrospectively to detect residual disease by ultradeep sequencing using ctDNA assays, developed from primary tumor whole-exome sequencing data. RESULTS: Personalized Signatera assays detected ctDNA ahead of clinical or radiologic relapse in 30 of the 34 patients who relapsed (patient-level sensitivity of 88.2%). Relapse was predicted with a lead interval of up to 38 months (median, 10.5 months; range, 0-38 months), and ctDNA positivity was associated with shorter relapse-free survival (P < .0001) and overall survival (P < .0001). All relapsing triple-negative patients (n = 7/23) had a ctDNA-positive test within a median of 8 months (range, 0-19 months), while the 16 nonrelapsed patients with triple-negative breast cancer remained ctDNA-negative during a median follow-up of 58 months (range, 8-99 months). The four patients who had negative tests before relapse all had hormone receptor-positive (HR+) disease and conversely, five of the 122 nonrelapsed patients (all HR+) had an occasional positive test. CONCLUSION: Serial postoperative ctDNA assessment has strong prognostic value, provides a potential window for earlier therapeutic intervention, and may enable more effective monitoring than current clinical tests such as cancer antigen 15-3. Our study provides evidence that those with serially negative ctDNA tests have superior clinical outcomes, providing reassurance to patients with breast cancer. For select cases with HR+ disease, decisions about treatment management might require serial monitoring despite the ctDNA-positive result.

Mitochondrial Fraction of Circulating Cell-Free DNA as an Indicator of Human Pathology.

Circulating cell-free DNA (ccfDNA) of mitochondrial origin (ccf-mtDNA) consists of a minor fraction of total ccfDNA in blood or in other biological fluids. Aberrant levels of ccf-mtDNA have been observed in many pathologies. Here, we introduce a simple and effective standardized Taqman probe-based dual-qPCR assay for the simultaneous detection and relative quantification of nuclear and mitochondrial fragments of ccfDNA. Three pathologies of major burden, one malignancy (Breast Cancer, BrCa), one inflammatory (Osteoarthritis, OA) and one metabolic (Type 2 Diabetes, T2D), were studied. Higher levels of ccf-mtDNA were detected both in BrCa and T2D in relation to health, but not in OA. In BrCa, hormonal receptor status was associated with ccf-mtDNA levels. Machine learning analysis of ccf-mtDNA datasets was used to build biosignatures of clinical relevance. (A) a three-feature biosignature discriminating between health and BrCa (AUC: 0.887) and a five-feature biosignature for predicting the overall survival of BrCa patients (Concordance Index: 0.756). (B) a five-feature biosignature stratifying among T2D, prediabetes and health (AUC: 0.772); a five-feature biosignature discriminating between T2D and health (AUC: 0.797); and a four-feature biosignature identifying prediabetes from health (AUC: 0.795). (C) a biosignature including total plasma ccfDNA with very high performance in discriminating OA from health (AUC: 0.934). Aberrant ccf-mtDNA levels could have diagnostic/prognostic potential in BrCa and Diabetes, while the developed multiparameter biosignatures can add value to their clinical management.

Natural killer cell subsets and their functional molecules in peripheral blood of the patients with breast cancer.

BACKGROUND: Natural killer (NK) cells, CD3- lymphocytes, are critical players in cancer immune surveillance. This study aimed to assess two types of CD3- NK cell classifications (subsets), that is, convectional subsets (based on CD56 and CD16 expression) and new subsets (based on CD56, CD27, and CD11b expression), and their functional molecules in the peripheral blood of patients with breast cancer (BC) in comparison with healthy donors (HDs). METHODS: Thirty untreated females with BC and 20 age-matched healthy women were enrolled. Peripheral blood samples were collected and directly incubated with fluorochrome-conjugated antibodies against CD3, CD56, CD16, CD27, CD11b, CD96, NKG2C, NKG2D, NKp44, CXCR3, perforin, and granzyme B. Red blood cells were then lysed using lysing solution, and the stained cells were acquired on four-color flow cytometer. RESULT: Our results indicated 15% of lymphocytes in peripheral blood of patients with BC and HDs had NK cells phenotype. However, the frequency of total NK cells (CD3-CD56+), and NK subsets (based on conventional and new classifications) was not significantly different between patients and HDs. We observed mean fluorescent intensity (MFI) of CXCR3 in total NK cells (p = .02) and the conventional cytotoxic (CD3-CD56dim CD16+) NK cells (p = .03) were significantly elevated in the patients with BC compared to HDs. Despite this, the MFI of granzyme B expression in conventional regulatory (CD3-CD56brightCD16- /+) NK cells and CD3-CD56-CD16+ NK cells (p = .03 and p = .004, respectively) in the patients was lower than healthy subjects. CONCLUSION: The higher expression of chemokine receptor CXCR3 on total NK cells in patients with BC may be associated with increased chemotaxis-related NK cell infiltration. However, lower expression of granzyme B in conventional regulatory NK cells and CD3-CD56-CD16+ NK cells in the patients compared to HDs suggests reduced cytotoxic activity of the NK cells in BC. These results might demonstrate accumulating NK subsets with a dysfunctional phenotype in the peripheral blood of patients with BC.

Higher peripheral blood mitochondrial DNA copy number and relative telomere length in under 48 years Indonesian breast cancer patients.

OBJECTIVE: Breast cancer is the leading cause of cancer incidence and mortality among Indonesian women. A comprehensive investigation is required to enhance the early detection of this disease. Mitochondrial DNA copy number (mtDNA-CN) and relative telomere length (RTL) have been proposed as potential biomarkers for several cancer risks, as they are linked through oxidative stress mechanisms. We conducted a case-control study to examine peripheral blood mtDNA-CN and RTL patterns in Indonesian breast cancer patients (n = 175) and healthy individuals (n = 181). The relative ratios of mtDNA-CN and RTL were determined using quantitative real-time PCR (qPCR). RESULTS: Median values of mtDNA-CN and RTL were 1.62 and 0.70 in healthy subjects and 1.79 and 0.73 in breast cancer patients, respectively. We found a positive association between peripheral blood mtDNA-CN and RTL (p < 0.001). In under 48 years old breast cancer patients, higher peripheral blood mtDNA-CN (mtDNA-CN ≥ 1.73 (median), p = 0.009) and RTL (continuous variable, p = 0.010) were observed, compared to the corresponding healthy subjects. We also found a significantly higher 'High-High' pattern of mtDNA-CN and RTL in breast cancer patients under 48 years old (p = 0.011). Our findings suggest that peripheral blood mtDNA-CN and RTL could serve as additional minimally invasive biomarkers for breast cancer risk evaluation.

Absolute lymphocyte count and neutrophil-to-lymphocyte ratio as predictors of CDK 4/6 inhibitor efficacy in advanced breast cancer.

Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) are the standard agents for treating patients with estrogen receptor-positive and human epidermal growth factor receptor 2-negative advanced breast cancer (ER + HER2 - ABC). However, markers predicting the outcomes of CDK4/6i treatment have yet to be identified. This study was a single-center retrospective cohort study. We retrospectively evaluated 101 patients with ER + HER2 - ABC receiving CDK4/6i in combination with endocrine therapy at Fukuyama City Hospital between November 2017 and July 2021. We investigated the clinical outcomes and the safety of CDK4/6i treatment, and the absolute lymphocyte count (ALC) and neutrophil-to-lymphocyte ratio (NLR) as predictive markers for CDK4/6i. We defined the cut-off values as 1000/µL for ALC and 3 for NLR, and divided into "low" and "high" groups, respectively. We evaluated 43 and 58 patients who received abemaciclib and palbociclib, respectively. Patients with high ALC and low NLR had significantly longer overall survival than those with low ALC and high NLR (high vs. low; ALC: HR 0.29; 95% CI 0.12-0.70; NLR: HR 2.94; 95% CI 1.21-7.13). There was no significant difference in efficacy between abemaciclib and palbociclib and both had good safety profiles. We demonstrated that ALC and NLR might predict the outcomes of CDK4/6i treatment in patients with ER + HER2 - ABC.

Changes in blood metabolomes as potential markers for severity and prognosis in doxorubicin-induced cardiotoxicity: a study in HER2-positive and HER2-negative breast cancer patients.

BACKGROUND: We aimed to compare the changes in blood metabolomes and cardiac parameters following doxorubicin treatment in HER2-positive and HER2-negative breast cancer patients. Additionally, the potential roles of changes in blood metabolomes as severity and prognostic markers of doxorubicin-induced cardiotoxicity were determined. METHODS: HER2-positive (n = 37) and HER2-negative (n = 37) breast cancer patients were enrolled. Cardiac function assessment and blood collection were performed at baseline and 2 weeks after completion of doxorubicin treatment in all patients, as well as at three months after completion of doxorubicin treatment in HER2-negative breast cancer patients. Blood obtained at all three-time points was processed for measuring cardiac injury biomarkers. Blood obtained at baseline and 2 weeks after completion of doxorubicin treatment were also processed for measuring systemic oxidative stress and 85 metabolome levels. RESULTS: Cardiac injury and systolic dysfunction 2 weeks after completion of doxorubicin treatment were comparable between these two groups of patients. However, only HER2-negative breast cancer patients exhibited increased systemic oxidative stress and cardiac autonomic dysfunction at this time point. Moreover, 33 and 29 blood metabolomes were altered at 2 weeks after completion of doxorubicin treatment in HER2-positive and HER2-negative breast cancer patients, respectively. The changes in most of these metabolomes were correlated with the changes in cardiac parameters, both at 2 weeks and 3 months after completion of doxorubicin treatment. CONCLUSIONS: The changes in blood metabolomes following doxorubicin treatment were dependent on HER2 status, and these changes might serve as severity and prognostic markers of doxorubicin-induced cardiotoxicity. TRIAL REGISTRATION: The study was conducted under ethical approval from the Institutional Review Board of the Faculty of Medicine, Chiang Mai University (Registration number: MED-2563-07001; Date: April 28, 2020). The study also complied with the Declaration of Helsinki.

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.

The effect of tamoxifen on estradiol, SHBG, IGF-1, and CRP in women with breast cancer or at risk of developing breast cancer: a meta-analysis of randomized controlled trials.

BACKGROUND AND AIM: The effects of tamoxifen on the serum levels of hormones and acute phase reactants have been studied previously, but study results have been inconsistent, especially in women with breast cancer. Hence, we conducted this meta-analysis of randomized controlled trials (RCTs) to try to clarify the effects of tamoxifen on estradiol, insulin-like growth factor 1 (IGF-1), sex hormone binding globulin (SHBG), and C-reactive protein (CRP) serum levels in women with breast cancer or at risk of developing breast cancer. METHODS: Databases were systematically searched up to December 2023. The meta-analysis was generated through a random-effects model and is presented as the weighted mean difference (WMD) and 95 % confidence intervals (CI). RESULTS: Nine publications were included in the present meta-analysis. The comprehensive findings from the random-effects model revealed an elevation in estradiol (WMD: 13.04 pg/mL, 95 % CI: 0.79, 25.30, p = 0.037) and SHBG levels (WMD: 21.26 nmol/l, 95 % CI: 14.85, 27.68, p = 0.000), as well as a reduction in IGF-1 (WMD: -14.41 µg/L, 95 % CI: -24.23, -4.60, p = 0.004) and CRP concentrations (WMD: -1.17 mg/dL, 95 % CI: -2.29, -0.05, p = 0.039) following treatment with tamoxifen in women with breast cancer or at risk of developing breast cancer, with no impact on IGFBP-3 levels (WMD: 0.11 µg/mL, 95 % CI: -0.07, 0.30, p = 0.240). CONCLUSION: Tamoxifen administration seems to increase estradiol and SHBG levels and reduce CRP and IGF-1 levels in women with breast cancer or at risk of developing breast cancer. Further studies are needed to determine whether these changes have any clinical relevance.

Fragmentation patterns of cell-free DNA and somatic mutations in the urine of metastatic breast cancer patients.

BACKGROUND: Urinary cell-free deoxyribonucleic acid (DNA) (ucfDNA) holds promise as a biomarker; however, its potential remains largely unexplored. We examined the fragmentation pattern of ucfDNA and identified somatic mutations within urine samples from metastatic breast cancer (MBC) patients. METHODS: Urine and blood specimens were collected before treatment from 45 MBC patients and posttreatment urine samples from 16 of the 45 patients at the China National Cancer Center. Somatic mutations and tumor mutational burden (TMB) in the urine and plasma of 10 patients were analyzed by next-generation sequencing (NGS). Fragmentation patterns of cfDNA were displayed using electropherograms. Differences in the extracted amount of cfDNA, length of cfDNA fragments, and TMB between urine and plasma were compared using a Wilcoxon test. RESULTS: The fragmentation patterns of ucfDNA were categorized as follows: (1) profile A (n = 26) containing a short peak (100-200 bp) and a long peak (>1500 bp); (2) profile B (n = 8) containing only a long peak; and (3) profile C (n = 11) containing flat pattern. For profile A patients, the short-peaked ucfDNA circulating in the bloodstream was much shorter compared with plasma cfDNA (149 vs. 171 bp, Wilcoxon test, P = 0.023). The fragmentation patterns in lung metastasis patients exhibited a higher propensity toward profile C ( P = 0.002). After treatment, 87.5% of the patients exhibited consistent fragmentation patterns. The concordance rate for somatic mutations in the plasma and urine was 30%, and the median TMB of urine and plasma was not significantly different. CONCLUSIONS: This study established a fragmentation pattern for ucfDNA and detected somatic mutations in the urine of MBC patients. These results suggest the potential application of ucfDNA as a biomarker for MBC.

Colorimetric detection of circulating tumor cells in breast cancer based on ladder-branch hybridization chain reaction and DFs/AuNCs nanozyme.

Breast cancer is the most common malignant tumor in women, which accounts for 6.9% of all cancer-related deaths. Early diagnosis is crucial for making the best clinical decision and improving the prognosis of patients. Circulating tumor cells (CTCs) have been regarded as significant tumor biomarkers. Herein, we designed a colorimetric biosensor for breast cancer CTCs quantification based on ladder-branch hybridization chain reaction (HCR) and DNA flowers/gold nanoclusters (DFs/AuNCs) nanozyme. With the assistance of complementary DNA labeled on magnetic beads (MBs), the cleavage products of RNA-cleaving DNAzymes (RCDs) could be rapidly captured, subsequently triggering ladder-branch HCR. In addition, the DFs/AuNCs nanozyme was applied for colorimetric analysis, which further improved the sensitivity for the detection of target CTCs. Benefiting from specific RCDs, ladder-branch HCR and DFs/AuNCs, we achieved a superior detection limit of 3 cells/mL as well as a broad linear range of 10 cells/mL to 104 cells/mL. Conclusively, this colorimetric biosensor achieved sensitively and selectively detection of breast cancer CTCs without the participation of enzymes at room temperature, which might provide new insight into the early detection of breast cancer.

Adherence to the American Cancer Society guidelines on nutrition and physical activity for cancer survivors and biomarkers of inflammation among breast cancer survivors.

OBJECTIVES: This study investigated whether adherence to the overall lifestyle recommendations in the American Cancer Society (ACS) guidelines on nutrition and physical activity for cancer survivors was associated with inflammation in breast cancer survivors. METHODS: The study included 409 women who had undergone breast cancer surgery at least 1 year before enrollment. A generalized linear model was used to estimate the least square means and 95% confidence intervals of plasma levels of inflammatory markers according to lifestyle factors defined in terms of adherence to the ACS guidelines. RESULTS: Higher overall adherence scores were associated with lower levels of high-sensitivity C-reactive protein (hs-CRP) (p for trend=0.015) and higher levels of adiponectin (p for trend=0.009). Similar significant associations of hs-CRP (p for trend= 0.004) and adiponectin (p for trend=0.010) levels were observed with the score for the body mass index (BMI) component of the adherence score. A higher diet component score was associated with a higher adiponectin level (p for trend=0.020), but there was no significant association for the physical activity component score. CONCLUSIONS: The present study's findings suggest that maintaining a healthy lifestyle according to the ACS guidelines was associated with beneficial effects on inflammatory marker levels, especially hs-CRP and adiponectin, among breast cancer survivors. Among the 3 components of lifestyle guidelines, the BMI component exhibited the most similar tendency to the overall adherence score in relation to inflammatory indicators. Further prospective and intervention studies are needed to investigate longitudinal associations between lifestyle factors and inflammatory markers among breast cancer survivors.

Prognostic Value of Pretreatment Plasma C-Reactive Protein in Patients with Early-Stage Breast Cancer.

BACKGROUND: Breast cancer incidence is now the highest among all cancers and accountable for 6.6% of all cancer-related deaths worldwide. Studies of the prognostic utility of plasma C-reactive protein (CRP) measurement in early-stage breast cancer have given discrepant results. METHODS: We identified 6,942 patients in the Danish Breast Cancer Cooperative Group database with early-stage breast cancer diagnosed between 2002 and 2016 who had a measure of pretreatment plasma CRP. Outcomes were recurrence-free interval and survival for a period up to 10 years. We analyzed associations with plasma CRP using Fine-Gray proportional subdistribution hazards model with recurrence-free interval. Data on plasma CRP were analyzed per doubling of concentration and in relation to CRP levels of <3 mg/L, 3 to 10 mg/L, and >10 mg/L and stratified according to standard clinical parameters in sensitivity analyses. RESULTS: A doubling of the plasma CRP concentration was associated with increased risk of recurrence (multivariate adjusted HR, 1.05; 95% CI, 1.01-1.08) and shorter survival (HR, 1.13; 95% CI, 1.09-1.16) in multivariate analyses. Survival was shorter in patients with plasma CRP levels of 3 to 10 and >10 mg/L versus <3 mg/L, with multivariate adjusted HRs of 1.30; 95% CI, 1.17-1.45 and 1.65; 95% CI, 1.39-1.95, respectively. CONCLUSIONS: Elevated plasma CRP measured before treatment in patients with early-stage breast cancer is an independent biomarker of increased risk of recurrence and early death. IMPACT: CRP measures before treatment might be used to individualize follow-up of patients with early-stage breast cancer.