Local dose-dense chemotherapy for triple-negative breast cancer via minimally invasive implantation of 3D printed devices

Dose-dense chemotherapy is the preferred first-line therapy for triple-negative breast cancer(TNBC),a highly aggressive disease with a poor prognosis.This treatment uses the same drug doses as conventional chemotherapy but with shorter dosing intervals,allowing for promising clinical outcomes with intensive treatment.However,the frequent systemic administration used for this treatment results in systemic toxicity and low patient compliance,limiting therapeutic efficacy and clinical benefit.Here,we report local dose-dense chemotherapy to treat TNBC by implanting 3D printed devices with timeprogrammed pulsatile release profiles.The implantable device can control the time between drug releases based on its internal microstructure design,which can be used to control dose density.The device is made of biodegradable materials for clinical convenience and designed for minimally invasive implantation via a trocar.Dose density variation of local chemotherapy using programmable release enhances anti-cancer effects in vitro and in vivo.Under the same dose density conditions,device-based chemotherapy shows a higher anticancer effect and less toxic response than intratumoral injection.We demonstrate local chemotherapy utilizing the implantable device that simulates the drug dose,number of releases,and treatment duration of the dose-dense AC(doxorubicin and cyclophosphamide)regimen preferred for TNBC treatment.Dose density modulation inhibits tumor growth,metastasis,and the expression of drug resistance-related proteins,including p-glycoprotein and breast cancer resistance protein.To the best of our knowledge,local dose-dense chemotherapy has not been reported,and our strategy can be expected to be utilized as a novel alternative to conventional therapies and improve anti-cancer efficiency.

Bibliometric analysis of phosphoglycerate kinase 1 expression in breast cancer and its distinct upregulation in triple-negative breast cancer

BACKGROUND Phosphoglycerate kinase 1(PGK1)has been identified as a possible biomarker for breast cancer(BC)and may play a role in the development and advancement of triple-negative BC(TNBC).AIM To explore the PGK1 and BC research status and PGK1 expression and mecha-nism differences among TNBC,non-TNBC,and normal breast tissue.METHODS PGK1 and BC related literature was downloaded from Web of Science Core Co-llection Core Collection.Publication counts,key-word frequency,cooperation networks,and theme trends were analyzed.Normal breast,TNBC,and non-TNBC mRNA data were gathered,and differentially expressed genes obtained.Area under the summary receiver operating characteristic curves,sensitivity and specificity of PGK1 expression were determined.Kaplan Meier revealed PGK1’s prognostic implication.PGK1 co-expressed genes were explored,and Gene Onto-logy,Kyoto Encyclopedia of Genes and Genomes,and Disease Ontology applied.Protein-protein interaction networks were constructed.Hub genes identified.RESULTS PGK1 and BC related publications have surged since 2020,with China leading the way.The most frequent keyword was“Expression”.Collaborative networks were found among co-citations,countries,institutions,and authors.PGK1 expression and BC progression were research hotspots,and PGK1 expression and BC survival were research frontiers.In 16 TNBC vs non-cancerous breast and 15 TNBC vs non-TNBC datasets,PGK1 mRNA levels were higher in 1159 TNBC than 1205 non-cancerous breast cases[standardized mean differences(SMD):0.85,95%confidence interval(95%CI):0.54-1.16,I²=86%,P<0.001].PGK1 expression was higher in 1520 TNBC than 7072 non-TNBC cases(SMD:0.25,95%CI:0.03-0.47,I²=91%,P=0.02).Recurrence free survival was lower in PGK1-high-expression than PGK1-low-expression group(hazard ratio:1.282,P=0.023).PGK1 co-expressed genes were concentrated in ATP metabolic process,HIF-1 signaling,and glycolysis/gluconeogenesis pathways.CONCLUSION PGK1 expression is a research hotspot and frontier direction in the BC field.PGK1 may play a strong role in promoting cancer in TNBC by mediating metabolism and HIF-1 signaling pathways.

Tumor deposits in axillary adipose tissue in patients with breast cancer:Do they matter?

Tumor deposits(TDs)are defined as discrete,irregular clusters of tumor cells lying in the soft tissue adjacent to but separate from the primary tumor,and are usually found in the lymphatic drainage area of the primary tumor.By definition,no residual lymph node structure should be identified in these tumor masses.At present,TDs are mainly reported in colorectal cancer,with a few reports in gastric cancer.There are very few reports on breast cancer(BC).For TDs,current dominant theories suggest that these are the result of lymph node metastasis of the tumor with complete destruction of the lymph nodes by the tumor tissue.Even some pathologists classify a TD as two lymph node metastases for calculation.Some pathologists also believe that TDs belong to the category of disseminated metastasis.Therefore,regardless of the origin,TDs are an indicator of poor prognosis.Moreover,for BC,sentinel lymph node biopsy is generally used at present.Whether radical axillary lymph node dissection should be adopted for BC with TDs in axillary lymph nodes is still inconclusive.The present commentary of this clinical issue has certain guiding significance.It is aimed to increase the awareness of the scientific community towards this under-recognized problem in BC pathology.

Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer

BACKGROUND Ferroptosis has recently been associated with multiple degenerative diseases.Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases.However,the association of iron proliferation-related genes with prognosis in HER2+breast cancer(BC)patients is unclear.AIM To identify and evaluate fresh ferroptosis-related biomarkers for HER2+BC.METHODS First,we obtained the mRNA expression profiles and clinical information of HER2+BC patients from the TCGA and METABRIC public databases.A four gene prediction model comprising PROM2,SLC7A11,FANCD2,and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort.Patients were stratified into high-risk and low-risk groups based on their median risk score,an independent predictor of overall survival(OS).Based on these findings,immune infiltration,mutations,and medication sensitivity were analyzed in various risk groupings.Additionally,we assessed patient prognosis by combining the tumor mutation burden(TMB)with risk score.Finally,we evaluated the expression of critical genes by analyzing single-cell RNA sequencing(scRNA-seq)data from malignant vs normal epithelial cells.RESULTS We found that the higher the risk score was,the worse the prognosis was(P<0.05).We also found that the immune cell infiltration,mutation,and drug sensitivity were different between the different risk groups.The highrisk subgroup was associated with lower immune scores and high TMB.Moreover,we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses.HRisk-HTMB patients had the worst prognosis,whereas LRisk-LTMB patients had the best prognosis(P<0.0001).Analysis of the scRNAseq data showed that PROM2,SLC7A11,and FANCD2 were significantly differentially expressed,whereas FH was not,suggesting that these genes are expressed mainly in cancer epithelial cells(P<0.01).CONCLUSION Our model helps guide the prognosis of HER2+breast cancer patients,and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.

Targeting triple-negative breast cancer:A clinical perspective

Triple-negative breast cancer(TNBC)is a disease with often an aggressive course and a poor prognosis compared to other subtypes of breast cancer.TNBC accounts for approximately 10%–15%of all diagnosed breast cancer cases and represents a high unmet need in the field.Up to just a few years ago,chemotherapy was the only systemic treatment option for this subtype(1).To date,TNBC is considered a heterogeneous disease.One of the existing classifications is based on the analysis of mRNA expression in 587 TNBC cases,in which Lehman et al.proposed six subtypes of TNBC as follows:two basal-like(BL1 and BL2)subtypes,a mesenchymal(M)subtype,a mesenchymal stem-like(MSL)subtype,an immunomodulatory(IM)subtype,and a luminal androgen receptor(LAR)subtype(2).Later studies have demonstrated that the IM and MSL subtypes do not correlate with independent subtypes but reflect background expression by dense infiltration of tumor-infiltrating lymphocytes(TILs)or stromal cells.According to this finding,the classification of TNBC has been revised into the following four subtypes:basal 1,basal 2,LAR,and mesenchymal subtypes(3).Over the last years,several new strategies have been investigated for the treatment of patients with TNBC.Among them,immunotherapy,antibody drug conjugates,new chemotherapy agents,and targeted therapy have been and are currently being developed.The present article aims to provide an updated overview on the different treatment options that are now available or are still under investigation for patients with TNBC.

Association between homologous recombination deficiency and outcomes with platinum and platinum-free chemotherapy in patients with triple-negative breast cancer

Objective:The choice of chemotherapeutic regimen for triple-negative breast cancer(TNBC)remains controversial.Homologous recombination deficiency(HRD)has attracted increasing attention in informing chemotherapy treatment.This study was aimed at investigating the feasibility of HRD as a clinically actionable biomarker for platinum-containing and platinum-free therapy.Methods:Chinese patients with TNBC who received chemotherapy between May 1,2008 and March 31,2020 were retrospectively analyzed with a customized 3D-HRD panel.HRD positivity was defined by an HRD score≥30 or deleterious BRCA1/2 mutation.A total of 386 chemotherapy-treated patients with TNBC were screened from a surgical cohort(NCT01150513)and a metastatic cohort,and 189 patients with available clinical and tumor sequencing data were included.Results:In the entire cohort,49.2%(93/189)of patients were identified as HRD positive(40 with deleterious BRCA1/2 mutations and 53 with BRCA1/2 intact with an HRD score of≥30).In the first-line metastatic setting,platinum therapy was associated with longer median progression-free survival(mPFS)than platinum-free therapy[9.1 vs.3.0 months;hazard ratio(HR),0.43;95%confidence interval 0.22–0.84;P=0.01].Among HRD-positive patients,the mPFS was significantly longer in those treated with platinum rather than platinum-free therapy(13.6 vs.2.0 months;HR,0.11;P=0.001).Among patients administered a platinum-free regimen,HRD-negative patients showed a PFS significantly superior to that of HRD-positive patients(P=0.02;treatment-biomarker P-interaction=0.001).Similar results were observed in the BRCA1/2-intact subset.In the adjuvant setting,HRD-positive patients tended to benefit more from platinum chemotherapy than from platinum-free chemotherapy(P=0.05,P-interaction=0.02).Conclusions:HRD characterization may guide decision-making regarding the use of platinum treatment in patients with TNBC in both adjuvant and metastatic settings.

Decreased LDHB expression in breast tumor cells causes NK cell activation and promotes tumor progression

Objective: Abnormal metabolism is the underlying reason for breast cancer progression. Decreased lactate dehydrogenase B(LDHB) has been detected in breast cancer but the function of LDHB remains unknown.Methods: Western blot was used to analyze LDHB expression in breast cancer cells. The impact of LDHB on tumor cell migration and invasion was determined using Transwell assays, wound healing assays, and a mouse lung metastasis model. Subcutaneous tumor formation, a natural killer(NK) cell cytotoxicity assay, and flow cytometry evaluated NK cell activation. Immunofluorescence and quantitative real-time PCR detected NK cell activation markers. Kaplan-Meier analysis evaluated the effect of immune cell infiltration on prognosis. Single-sample gene set enrichment analysis determined NK cell activation scores. A support vector machine predicted the role of LDHB in NK cell activation.Results: In this study we showed that LDHB inhibits the breast cancer cell metastasis and orchestrates metabolic reprogramming within tumor cells. Our results revealed that LDHB-mediated lactic acid clearance in breast cancer cells triggers NK cell activation within the tumor microenvironment. Our findings, which were confirmed in a murine model, demonstrated that LDHB in tumor cells promotes NK cell activation and ultimately results in the eradication of malignant cells. Clinically, our study further validated that LDHB affects immune cell infiltration and function. Specifically, its expression has been linked to enhanced NK cell-mediated cytotoxicity and improved patient survival. Furthermore, we identified LDHB expression in tumors as an important predictor of NK cell activation, with strong predictive ability in some cancers.Conclusions: Our results suggest that LDHB is a promising target for activating the tumor immune microenvironment in breast cancer, where LDHB-associated lactic acid clearance leads to increased NK cell activity. This study highlights the critical role of LDHB in regulating immune responses and its potential as a therapeutic target for breast cancer.

A Novel Approach to Breast Tumor Detection: Enhanced Speckle Reduction and Hybrid Classification in Ultrasound Imaging

Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effectivetreatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breastcancer fromultrasound images. The primary challenge is accurately distinguishing between malignant and benigntumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentationand classification. The main objective of the research paper is to develop an advanced methodology for breastultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, andmachine learning-based classification. A unique approach is introduced that combines Enhanced Speckle ReducedAnisotropic Diffusion (SRAD) filters for speckle noise reduction, U-NET-based segmentation, Genetic Algorithm(GA)-based feature selection, and Random Forest and Bagging Tree classifiers, resulting in a novel and efficientmodel. To test and validate the hybrid model, rigorous experimentations were performed and results state thatthe proposed hybrid model achieved accuracy rate of 99.9%, outperforming other existing techniques, and alsosignificantly reducing computational time. This enhanced accuracy, along with improved sensitivity and specificity,makes the proposed hybrid model a valuable addition to CAD systems in breast cancer diagnosis, ultimatelyenhancing diagnostic accuracy in clinical applications.

Research progress in tumor angiogenesis and drug resistance in breast cancer

Angiogenesis is considered a hallmark pathophysiological process in tumor development. Aberrant vasculature resulting from tumor angiogenesis plays a critical role in the development of resistance to breast cancer treatments, via exacerbation of tumor hypoxia, decreased effective drug concentrations within tumors, and immune-related mechanisms. Antiangiogenic therapy can counteract these breast cancer resistance factors by promoting tumor vascular normalization. The combination of antiangiogenic therapy with chemotherapy, targeted therapy, or immunotherapy has emerged as a promising approach for overcoming drug resistance in breast cancer. This review examines the mechanisms associated with angiogenesis and the interactions among tumor angiogenesis, the hypoxic tumor microenvironment, drug distribution, and immune mechanisms in breast cancer. Furthermore, this review provides a comprehensive summary of specific antiangiogenic drugs, and relevant studies assessing the reversal of drug resistance in breast cancer. The potential mechanisms underlying these interventions are discussed, and prospects for the clinical application of antiangiogenic therapy to overcome breast cancer treatment resistance are highlighted.

Two Stages Segmentation Algorithm of Breast Tumor in DCE-MRI Based on Multi-Scale Feature and Boundary Attention Mechanism

Nuclearmagnetic resonance imaging of breasts often presents complex backgrounds.Breast tumors exhibit varying sizes,uneven intensity,and indistinct boundaries.These characteristics can lead to challenges such as low accuracy and incorrect segmentation during tumor segmentation.Thus,we propose a two-stage breast tumor segmentation method leveraging multi-scale features and boundary attention mechanisms.Initially,the breast region of interest is extracted to isolate the breast area from surrounding tissues and organs.Subsequently,we devise a fusion network incorporatingmulti-scale features and boundary attentionmechanisms for breast tumor segmentation.We incorporate multi-scale parallel dilated convolution modules into the network,enhancing its capability to segment tumors of various sizes through multi-scale convolution and novel fusion techniques.Additionally,attention and boundary detection modules are included to augment the network’s capacity to locate tumors by capturing nonlocal dependencies in both spatial and channel domains.Furthermore,a hybrid loss function with boundary weight is employed to address sample class imbalance issues and enhance the network’s boundary maintenance capability through additional loss.Themethod was evaluated using breast data from 207 patients at RuijinHospital,resulting in a 6.64%increase in Dice similarity coefficient compared to the benchmarkU-Net.Experimental results demonstrate the superiority of the method over other segmentation techniques,with fewer model parameters.

Cost analysis of radical resection of malignant breast tumors under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health.Therefore,this study examined patients who underwent breast cancer surgery,analyzed hospitalization costs and structure,and explored the impact of China Healthcare Security Diagnosis Related Groups(CHS-DRG)management on patient costs.It aimed to provide medical institutions with ways to reduce costs,optimize cost structures,reduce patient burden,and improve service efficiency.AIM To study the CHS-DRG payment system’s impact on breast cancer surgery costs.METHODS Using the CHS-DRG(version 1.1)grouping criteria,4073 patients,who underwent the radical resection of breast malignant tumors from January to December 2023,were included in the JA29 group;1028 patients were part of the CHS-DRG payment system,unlike the rest.Through an independent sample t-test,the length of hospital stay as well as total hospitalization,medicine and consumables,medical,nursing,medical technology,and management expenses were compared.Pearson’s correlation coefficient was used to test the cost correlation.RESULTS In terms of hospitalization expenses,patients in the CHS-DRG payment group had lower medical,nursing,and management expenses than those in the diagnosis-related group(DRG)non-payment group.For patients in the DRG payment group,the factors affecting the total hospitalization cost,in descending order of relevance,were medicine and consumable costs,consumable costs,medicine costs,medical costs,medical technology costs,management costs,nursing costs,and length of hospital stay.For patients in the DRG nonpayment group,the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses,consumable expenses,medical technology expenses,the cost of medicines,medical expenses,nursing expenses,length of hospital stay,and management expenses.CONCLUSION The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs,medical consumable costs,and the length of hospital stay while ensuring medical safety.

Identification of an immune classifier for predicting the prognosis and therapeutic response in triple-negative breast cancer

Triple-negative breast cancer(TNBC)poses a significant challenge due to the lack of reliable prognostic gene signatures and an understanding of its immune behavior.Methods:We analyzed clinical information and mRNA expression data from 162 TNBC patients in TCGA-BRCA and 320 patients in METABRIC-BRCA.Utilizing weighted gene coexpression network analysis,we pinpointed 34 TNBC immune genes linked to survival.The least absolute shrinkage and selection operator Cox regression method identified key TNBC immune candidates for prognosis prediction.We calculated chemotherapy sensitivity scores using the“pRRophetic”package in R software and assessed immunotherapy response using the Tumor Immune Dysfunction and Exclusion algorithm.Results:In this study,34 survival-related TNBC immune gene expression profiles were identified.A least absolute shrinkage and selection operator-Cox regression model was used and 15 candidates were prioritized,with a concomitant establishment of a robust risk immune classifier.The high-risk TNBC immune groups showed increased sensitivity to therapeutic agents like RO-3306,Tamoxifen,Sunitinib,JNK Inhibitor VIII,XMD11-85h,BX-912,and Tivozanib.An analysis of the Search Tool for Interaction of Chemicals database revealed the associations between the high-risk group and signaling pathways,such as those involving Rap1,Ras,and PI3K-Akt.The low-risk group showed a higher immunotherapy response rate,as observed through the tumor immune dysfunction and exclusion analysis in the TCGA-TNBC and METABRIC-TNBC cohorts.Conclusion:This study provides insights into the immune complexities of TNBC,paving the way for novel diagnostic approaches and precision treatment methods that exploit its immunological intricacies,thus offering hope for improved management and outcomes of this challenging disease.

Identification of a seven-gene signature and establishment of a prognostic nomogram predicting overall survival of triple-negative breast

Background: Triple-negative breast cancer (TNBC) is a highly heterogeneous breast cancersubtype characterized by the absence of expression of estrogen receptor (ER), progesteronereceptor (PR), and human epidermal growth factor receptor 2 (HER2). TNBC exhibitsresistance to hormone and HER2-targeted therapy, along with a higher incidence ofrecurrence and poorer prognosis. Therefore, exploring the molecular features of TNBC andconstructing prognostic models are of significant importance for personalized treatmentstrategies. Methods: In this research, bioinformatics approaches were utilized to screendifferentially expressed genes in 405 TNBC cases and 128 normal tissue samples from 8 GEOdatasets. Key core genes and signaling pathways were further identified. Additionally, aprognostic model incorporating seven genes was established using clinical and pathologicalinformation from 169 TNBC cases in the TCGA dataset, and its predictive performance wasevaluated. Results: Functional analysis revealed dysregulated biological processes such asDNA replication, cell cycle, and mitotic chromosome separation in TNBC. Protein-proteininteraction network analysis identified ten core genes, including BUB1, BUB1B, CDK1,CDC20, CDCA8, CCNB1, CCNB2, KIF2C, NDC80, and CENPF. A prognostic model consistingof seven genes (EXO1, SHCBP1, ABRACL, DMD, THRB, DCDC2, and APOD) was establishedusing a step-wise Cox regression analysis. The model demonstrated good predictiveperformance in distinguishing patients' risk. Conclusion: This research provides importantinsights into the molecular characteristics of TNBC and establishes a reliable prognosticmodel for understanding its pathogenesis and predicting prognosis. These findingscontribute to the advancement of personalized treatment for TNBC.

Role of tumor microenvironment in triple-negative breast cancer and its prognostic significance

Breast cancer has been shown to live in the tumor microenvironment, which consists of not only breast cancer cells themselves but also a significant amount of pathophysiologically altered surrounding stroma and cells. Diverse components of the breast cancer microenvironment, such as suppressive immune cells, re-programmed fibroblast cells, altered extracellular matrix (ECM) and certain soluble factors, synergistically impede an effective anti-tumor response and promote breast cancer progression and metastasis. Among these components, stromal cells in the breast cancer microenvironment are characterized by molecular alterations and aberrant signaling pathways, whereas the ECM features biochemical and biomechanical changes. However, triple-negative breast cancer (TNBC), the most aggressive subtype of this disease that lacks effective therapies available for other subtypes, is considered to feature a unique microenvironment distinct from that of other subtypes, especially compared to Luminal A subtype. Because these changes are now considered to significantly impact breast cancer development and progression, these unique alterations may serve as promising prognostic factors of clinical outcome or potential therapeutic targets for the treatment of TNBC. In this review, we focus on the composition of the TNBC microenvironment, concomitant distinct biological alteration, specific interplay between various cell types and TNBC cells, and the prognostic implications of these findings.

Clinical Value of cfDNA Content in Peripheral Blood of Patients with Triple-Negative Breast Cancer

Objective:To explore the value of circulating free(cfDNA)content in the clinical diagnosis and treatment of triple-negative breast cancer(TNBC).Methods:A total of 39 TNBC patients,45 non-TNBC patients,and 50 healthy individuals admitted to the Baoding First Central Hospital during 2019-2022 were recruited.The clinical data,peripheral blood cfDNA concentration,and clinicopathological indicators of the patients were observed and analyzed.Results:The difference in clinical indicators such as age,age range,tumor size,clinical stage,and lymph node metastasis between patients with TNBC and non-TNBC was insignificant(P>0.05).The cfDNA concentrations(ng/mL)of the TNBC group,non-TNBC group,and healthy group were 24.12±4.98,15.36±4.12,and 3.12±1.02,respectively,and they are statistically different(P<0.05).The difference in cfDNA concentration was insignificant between TNBC patients with tumors≤2 cm and>2 cm(P>0.05)but was significant between TNBC patients with clinical stages I+II and III+IV(P<0.05).The cfDNA concentration in TNBC patients with lymph node metastasis was significantly higher than those without lymph node metastasis(P<0.05).Conclusion:cfDNA has an important application value in the diagnosis and treatment of breast cancer.By detecting the cfDNA level and its gene variation,valuable information about the progress and treatment effects of breast cancer can be obtained.This non-invasive detection method has a wide range of applications and can be used for early screening,auxiliary diagnosis,efficacy evaluation,and recurrence monitoring of breast cancer.

Ultra-sensitive Nanoprobe Modified with Tumor Cell Membrane for UCL/MRI/PET Multimodality Precise Imaging of Triple-Negative Breast Cancer

Triple-negative breast cancer(TNBC)is a subtype of breast cancer in which the estrogen receptor and progesterone receptor are not expressed,and human epidermal growth factor receptor 2 is not amplified or overexpressed either,which make the clinical diagnosis and treatment very challenging.Molecular imaging can provide an effective way to diagnose TNBC.Upconversion nanoparticles(UCNPs),are a promising new generation of molecular imaging probes.However,UCNPs still need to be improved for tumor-targeting ability and biocompatibility.This study describes a novel probe based on cancer cell membrane-coated upconversion nanoparticles(CCm-UCNPs),owing to the low immunogenicity and homologous-targeting ability of cancer cell membranes,and modified multifunctional UCNPs.This probe exhibits excellent performance in breast cancer molecular classification and TNBC diagnosis through UCL/MRI/PET tri-modality imaging in vivo.By using this probe,MDA-MB-231 was successfully differentiated between MCF-7 tumor models in vivo.Based on the tumor imaging and molecular classification results,the probe is also expected to be modified for drug delivery in the future,contributing to the treatment of TNBC.The combination of nanoparticles with biomimetic cell membranes has the potential for multiple clinical applications.

Combined peripheral natural killer cell and circulating tumor cell enumeration enhance prognostic efficiency in patients with metastatic triple-negative breast cancer

Objective：Triple-negative breast cancer（TNBC）is a heterogeneous disease with poor prognosis.Circulating tumor cells（CTCs）are a promising predictor for breast cancer prognoses but their reliability regarding progression-free survival（PFS）is controversial.We aim to verify their predictive value in TNBC.Methods：In present prospective cohort study,we used the Pep@MNPs method to enumerate CTCs in baseline blood samples from 75 patients with TNBC（taken at inclusion in this study）and analyzed correlations between CTC numbers and outcomes and other clinical parameters.Results：Median PFS was 6.0（range：1.0–25.0）months for the entire cohort,in whom we found no correlations between baseline CTC status and initial tumor stage（P=0.167）,tumor grade（P=0.783）or histological type（P=0.084）.However,among those getting first-line treatment,baseline CTC status was positively correlated with ratio of peripheral natural killer（NK）cells（P=0.032）,presence of lung metastasis（P=0.034）and number of visceral metastatic site（P=0.037）.Baseline CTC status was predictive for PFS in first-line TNBC（P=0.033）,but not for the cohort as a whole（P=0.118）.This prognostic limitation of CTC could be ameliorated by combining CTC and NK cell enumeration（P=0.049）.Conclusions：Baseline CTC status was predictive of lung metastasis,peripheral NK cell ratio and PFS in TNBC patients undergoing first-line treatment.We have developed a combined CTC-NK enumeration strategy that allows us to predict PFS in TNBC without any preconditions.

Clinical Value of Peripheral Blood Circulating Tumor Cells and Cell-Free DNA Combined Detection in Triple-Negative Breast Cancer

Objective:To determine the clinical value of combined detection of circulating tumor cells(CTCs)and cell-free DNA(cfDNA)in peripheral blood of patients with triple-negative breast cancer.Method:41 patients with breast cancer admitted to the First Central Hospital of Baoding from January 2020 to December 2021 were selected and recruited into the experimental group,42 patients with benign breast cancer admitted during the same period were recruited into the conditional control group,and 41 healthy patients admitted during the same period were recruited into the blank control group.The positive rate of peripheral blood CTCs,the level of cfDNA,and the diagnostic efficacy of peripheral blood CTCs,cfDNA alone and the combination thereof for breast cancer were analyzed.Result:The positive rates of peripheral blood CTCs in the experimental group,the conditional control group,and the blank control group were 43.90%,11.90%,and 9.74%,respectively,and there was significant difference among the groups.The levels of cfDNA in peripheral blood of the experimental group,the conditional control group,and the blank control group were 0.26±0.08 bp,0.17±0.03 bp,and 0.15±0.04 bp,respectively,which were statistically significant.The detection levels of 100 bp hTERT/ng mT1 and 241 bp hTERT/ng-mT1 in the experimental group were significantly higher than those in the conditional control group and the blank control group.The accuracy of peripheral blood CTCs detection in the three groups was 66.21%,the accuracy of cfDA241 bp/100 hp hTERT detection was 80.41%,and the accuracy of combined detection of peripheral blood CTCs and cfDNA was 94.03%.Conclusion:The clinical application of peripheral blood CTCs combined with cfDNA level detection can increase detection accuracy,provide data support for clinicians,and improve the clinical diagnostic effect of triple-negative breast cancer.

Circulating tumor cells and circulating tumor DNA in breast cancer diagnosis and monitoring

Liquid biopsy,including both circulating tumor cells and circulating tumor DNA,is becoming more popular as a diagnostic tool in the clinical management of breast cancer.Elevated concentrations of these biomarkers during cancer treatment may be used as markers for cancer progression as well as to understand the mechanisms underlying metastasis and treatment resistance.Thus,these circulating markers serve as tools for cancer assessing and monitoring through a simple,non-invasive blood draw.However,despite several study results currently noting a potential clinical impact of ctDNA mutation tracking,the method is not used clinically in cancer diagnosis among patients and more studies are required to confirm it.This review focuses on understanding circulating tumor biomarkers,especially in breast cancer.

Understanding the mechanisms underlying obesity in remodeling the breast tumor immune microenvironment:from the perspective of inflammation

Obesity is a well-known modifiable risk factor for breast cancer and is considered a poor prognostic factor in pre-and post-menopausal women.While the systemic effects of obesity have been extensively studied,less is known about the mechanisms underlying obesityassociated cancer risk and the local consequences of obesity.Thus,obesity-induced inflammation has become the focus of research interest.Biologically,the development of cancer involves a complex interaction with numerous components.As the tumor immune microenvironment changes due to obesity-triggered inflammation,an increase in infiltration occurs for proinflammatory cytokines and adipokines,as well as adipocytes,immune cells,and tumor cells in the expanded adipose tissue.Complicated cellular-molecular crosstalk networks change critical pathways,mediate metabolic and immune function reprogramming,and have a significant role in tumor metastasis,proliferation,resistance,angiogenesis,and tumorigenesis.This review summarizes recent research findings on how inflammatory mediators in the in situ tumor microenvironment regulate the occurrence and development of breast cancer in the context of obesity.We analyzed the heterogeneity and potential mechanisms of the breast cancer immune microenvironment from the perspective of inflammation to provide a reference for the clinical transformation of precision targeted cancer therapy.