Network Structure and Variability of Recurrence Fear in Early-Stage Non-Small Cell Lung Cancer:A Symptom Network Analysis

Background:Lung cancer,one of the most prevalent and deadly malignancies worldwide,not only poses a significant physical burden but also a profound psychological challenge to patients.Among these psychological challenges,the fear of recurrence stands out as a particularly distressing issue.This fear,often rooted in the patients’past experiences with the disease and its treatment,can significantly impact their quality of life,mental health,and even compliance with follow-up care.Moreover,this fear can be exacerbated by the lack of understanding and support from healthcare professionals and family members,further isolating patients and compounding their psychological burden.Therefore,understanding and addressing the fear of recurrence in lung cancer patients is crucial for improving their overall well-being and outcomes.Aims:This study aims to develop a symptom network model for fear of recurrence in early-stage lung cancer patients,analyzing symptom correlations to enhance healthcare providers’understanding and management of these symptoms,thereby improving patient outcomes and quality of life.Design:A cross-sectional study design was used.Method:We employed convenience sampling to recruit 551 lung cancer patients from the Thoracic Surgery Department of a tertiary hospital in Beijing between January 2023 and December 2023.A cross-sectional study was conducted using the General Information Questionnaire,Fear of Disease Progression Scale,and Level of Hope Scale.Network analysis was performed with JASP 0.18.3.0 using the EBICglasso method,and centrality metrics including Betweenness,Closeness,Degree centrality,and Expected influence were calculated.Results:Symptom network analysis identified fear of family impact and future work disruption as central to recurrence fear in these patients.Gender-based analysis revealed‘fear of being unable to continue work’as central in males,while‘fear of affecting family members’was central in females.Among adolescents,concerns about future work,medication side effects,and family impact showed the highest expected influence.In contrast,older patients predominantly feared major treatment implications.One-way ANOVA indicated that older age correlated with reduced recurrence fear,and higher hope levels significantly mitigated this fear.Conclusion:This study broadens understanding of fear of recurrence across demographic variables like gender and age,elucidating symptom interrelations and impacts.Future strategies should focus on patient-specific differences in recurrence fear to formulate targeted interventions.Relevance to Clinical Practice:Through in-depth analysis of the symptom network,healthcare professionals can more comprehensively understand the psychological responses of lung cancer patients when they face the risk of recurrence,and then formulate more precise and personalized treatment plans.At the same time,doctors and nurses can adjust treatment strategies in a timely manner according to the changes in the patient’s symptom network and provide more comprehensive psychological support,thus enhancing the patient’s treatment adherence and outcome.Patient Contribution:People who were invited to participate voluntarily completed a range of questionnaires.

水田动力底盘逆向建模与质心验证——基于Geomagic Design X

针对目前农业机械仿真和优化模型精度不高的问题,提出了一种构建精确模型的逆向建模方法。应用光学扫描仪采集点云数据,基于Geomagic Design X处理点云数据并重构零部件模型,在SolidWorks中完成水田动力底盘的装配。以VP6D-CQ型水田动力底盘为例,将测得的实际质心位置与所建的模型质心位置进行比较,并对提出的逆向建模方法进行了试验验证以及误差分析。结果表明:总质量、x坐标、y坐标、z坐标的误差值分别为4.55%、3.62%、2.23%、4.81%,误差值均在5%内。此方法可构建准确的三维模型,为后续仿真优化数据精确性奠定了基础,与传统的研发相比较,可缩短农业机械研发周期、降低设计成本。

App Designer辅助教学方法探索与实践——以软件无线电课程为例

软件无线电作为通信学科的必修课程,具有承上启下的重要作用。因课程原理抽象、理论公式复杂,学员在学习过程存在理解掌握难、实践应用难等问题。通过对当前软件无线电教学过程中存在的不足与困难进行分析,提出利用MATLAB App Designer辅助课程教学,从教学准备、课堂互动、自主实验、反馈提升四个方面开展课程教学改革。实践表明,该方法对于提升学员的工程思维、系统思维具有显著效果,同时可以增强学员理论联系实际的能力。

Prediction of lymph node metastasis and sentinel node navigation surgery for patients with early-stage gastric cancer

Accurate prediction of lymph node(LN) status is crucially important for appropriate treatment planning in patients with early gastric cancer(EGC). However,consensus on patient and tumor characteristics associated with LN metastasis are yet to be reached. Through systematic search,we identified several independent variables associated with LN metastasis in EGC,which should be included in future research to assess which of these variables remain as significant predictors of LN metastasis. On the other hand,even if we use these promising parameters,we should realize the limitation and the difficulty of predicting LN metastasis accurately. The sentinel LN(SLN) is defined as first possible site to receive cancer cells along the route of lymphatic drainage from the primary tumor. The absence of metastasis in SLN is believed to correlate with the absence of metastasis in downstream LNs. In this review,we have attempted to focus on several independent parameters which have close relationship between tumor and LN metastasis in EGC. In addition,we evaluated the history of sentinel node navigation surgery and the usefulness for EGC.

Treatment patterns for adjuvant docetaxel-based chemotherapy in early-stage breast cancer in China：A pooled retrospective analysis of four observational studies

Objective：Adjuvant docetaxel-based chemotherapy is frequently used for operable early breast cancer（EBC）.This study investigated patterns of use of docetaxel（T）in real-life clinical practice in China.Methods：This was a retrospective pooled analysis of the Asia-Pacific Breast Initiatives（APBI）Ⅰ（2006–2008）and Ⅱ（2009–2011）registries,and two Chinese observational studies;BC STATE（2011–2014）and BC Local Registry（2007–2010）.Female Chinese adults（≥18 years）with operable breast cancer treated with docetaxel-based adjuvant chemotherapy were included in the analysis.Patients with metastatic disease were excluded.The primary endpoint was assessment of treatment patterns and patient profiles.A logistic regression analysis was conducted to identify factors associated with choice of adjuvant chemotherapy regimen.Results：Data from 3,020 patients were included.The most frequently used adjuvant regimen was docetaxel/anthracycline combination[n=1,421（47.1%）;of whom 52.0%received T/epirubicin（E）/cyclophosphamide（C）],followed by docetaxel/other[n=705（23.3%）;of whom 72.8%received TC],docetaxel/anthracycline sequential[n=447（14.8%）;of whom 40.9%and 39.6%received 5-Fu/EC-T and EC-T,respectively],and＂other＂[n=447（14.8%）;of whom 91.5%received T].A significant association was found between adjuvant therapy with docetaxel/anthracycline combination and patient weight,menopausal status and estrogen receptor status.Conclusions：Real-world data revealed that docetaxel/anthracycline combination is the most commonly used category of docetaxel-based adjuvant therapy for patients with operable breast cancer in China;of which TEC is the most frequently used regimen.

Prediction of early-stage hepatocellular carcinoma using Onco Scan chromosomal copy number aberration data

AIM To identify chromosomal copy number aberrations(CNAs) in early-stage hepatocellular carcinoma(HCC) and analyze whether they are correlated with patient prognosis.METHODS One hundred and twenty patients with early-stage HCC were enrolled in our study, with the collection of formalin fixed, paraffin-embedded(FFPE) specimens and clinicopathological data. Tumor areas were marked by certified pathologists on a hematoxylin and eosinstained slide, and cancer and adjacent non-cancerous tissues underwent extraction of DNA, which was analyzed with the Affymetrix Onco Scan platform to assess CNAs and loss of heterozygosity(LOH). Ten individuals with nonmalignant disease were used as the control group. Another cohort consisting of 40 patients with stage Ⅰ/Ⅱ HCC were enrolled to analyze gene expression and to correlate findings with the Onco Scan data.RESULTS Copy number amplifications occurred at chromosomes 1 q21.1-q44 and 8 q12.3-24.3 and deletions were found at 4 q13.1-q35.2, 8 p 23.2-21.1, 16 q23.3-24.3, and 17 p13.3-12, while LOH commonly occurred at 1 p32.3, 3 p21.31, 8 p23.2-21.1, 16 q22.1-24.3, and 17 p 13.3-11 in early-stage HCC. Using Cox regression analysis, we also found that a higher percentage of genome change(≥ 60%) was an independent factor for worse prognosis in early-stage HCC(P = 0.031). Among the 875 genes in the Onco Scan Gene Chip, six were independent predictors of worse disease-free survival, of which three were amplified(MYC, ELAC2, and SYK) and three were deleted(GAK, MECOM, and WRN). Further, patients with HCC who exhibited ≥ 3 CNAs involving these six genes have worse outcomes compared to those who had < 3 CNAs(P < 0.001). Similarly, Asian patients with stage I HCC from The Cancer Genome Atlas harboring CNAs with these genes were also predicted to have poorer outcomes.CONCLUSION Patients with early-stage HCC and increased genome change or CNAs involving MYC, ELAC2, SYK, GAK, MECOM, or WRN are at risk for poorer outcome after resection.

Clinicopathological analysis of early-stage breast cancer patients that meet indications for BRCA 1/2 genetic testing

Objective:To investigate the clinicopathological characteristics and prognostic factors of early-stage breast cancer patients with indications for breast cancer susceptibility genes 1/2(BRCA1/2)genetic testing in China.Methods:Based on the indication criteria for BRCA genetic testing specified in the National Comprehensive Cancer Network(NCCN)clinical practice guidelines in oncology,genetic/familial high-risk assessment:Breast and ovarian(Version 2.2019),a retrospective analysis was performed on patients with early-stage invasive breast cancer treated at Breast Disease Center,Peking University First Hospital between January 2008 and December 2016.Clinicopathological characteristics of all patients were analyzed,and prognoses were calculated using the KaplanMeier method and a Cox proportionate hazards model.Results:A total of 906 early-stage breast cancer patients who had indications for BRCA genetic testing and had complete clinicopathological data and follow-up information were included in the study group,accounting for34.7%of all breast cancer patients treated in Breast Disease Center,Peking University First Hospital during the study period.Compared with breast cancer patients without indications for BRCA genetic testing,the overall survival(OS)and disease-free survival(DFS)of patients with indications were not significantly different.In the study group,patients with premenopausal status,high T stage,lymph node positive,estrogen receptor(ER)negative,Ki-67>20%and presence of a vascular tumor thrombus had worse prognosis.There were more family histories of gastrointestinal cancer in patients with related indications than in patients without such indications.Conclusions:Single-center data showed that more than 30%of patients with early-stage breast cancer had indications for BRCA genetic testing.There was no prognostic difference in patients with or without indications for BRCA genetic testing.Premenopausal status,high T stage,lymph node positive,ER negative,Ki-67>20%,and presence of a vascular tumor thrombus were associated with poor prognosis.

Differential gene expression profiling of gastric intraepithelial neoplasia and early-stage adenocarcinoma

AIM: To investigate the differentiated whole genome expression profiling of gastric high- and low-grade intraepithelial neoplasia and early-stage adenocarcinoma.

Prediction of fibril formation by early-stage amyloid peptide aggregation

Amyloid fibrils are found in systemic amyloidosis diseases such as Alzheimer's disease,Parkinson's disease,and type II diabetes.Currently,these diseases are diagnosed by observation of fibrils or plaques,which is an ineffective method for early diagnosis and treatment of disease.The goal of this study was to develop a simple and quick method to predict the possibility and speed of fibril formation before its occurrence.Oligomers generated from seven representative peptide segments were first isolated and detected by ion-mobility mass spectrometry(IM-MS).Then,their assemblies were disrupted using formic acid(FA).Interestingly,oligomers that showed small ion intensity changes upon FA addition had rapid fibril formation.By contrast,oligomers that had large ion intensity changes generated fibrils slowly.Two control peptides(aggregation/no fibrils and no aggregation/no fibrils)did not show changes in their ion intensities,which confirmed the ability of this method to predict amyloid formation.In summary,the developed method correlated MS intensity ratio changes of peptide oligomers on FA addition with their amyloid propensities.This method will be useful for monitoring peptide/protein aggregation behavior and essential for their mechanism studies.

Alloy design for laser powder bed fusion additive manufacturing:a critical review

Metal additive manufacturing(AM)has been extensively studied in recent decades.Despite the significant progress achieved in manufacturing complex shapes and structures,challenges such as severe cracking when using existing alloys for laser powder bed fusion(L-PBF)AM have persisted.These challenges arise because commercial alloys are primarily designed for conventional casting or forging processes,overlooking the fast cooling rates,steep temperature gradients and multiple thermal cycles of L-PBF.To address this,there is an urgent need to develop novel alloys specifically tailored for L-PBF technologies.This review provides a comprehensive summary of the strategies employed in alloy design for L-PBF.It aims to guide future research on designing novel alloys dedicated to L-PBF instead of adapting existing alloys.The review begins by discussing the features of the L-PBF processes,focusing on rapid solidification and intrinsic heat treatment.Next,the printability of the four main existing alloys(Fe-,Ni-,Al-and Ti-based alloys)is critically assessed,with a comparison of their conventional weldability.It was found that the weldability criteria are not always applicable in estimating printability.Furthermore,the review presents recent advances in alloy development and associated strategies,categorizing them into crack mitigation-oriented,microstructure manipulation-oriented and machine learning-assisted approaches.Lastly,an outlook and suggestions are given to highlight the issues that need to be addressed in future work.

Web Layout Design of Large Cavity Structures Based on Topology Optimization

Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.

Design Principles and Mechanistic Understandings of Non-Noble-Metal Bifunctional Electrocatalysts for Zinc-Air Batteries

Zinc-air batteries(ZABs)are promising energy storage systems because of high theoretical energy density,safety,low cost,and abundance of zinc.However,the slow multi-step reaction of oxygen and heavy reliance on noble-metal catalysts hinder the practical applications of ZABs.Therefore,feasible and advanced non-noble-metal elec-trocatalysts for air cathodes need to be identified to promote the oxygen catalytic reaction.In this review,we initially introduced the advancement of ZABs in the past two decades and provided an overview of key developments in this field.Then,we discussed the work-ing mechanism and the design of bifunctional electrocatalysts from the perspective of morphology design,crystal structure tuning,interface strategy,and atomic engineering.We also included theoretical studies,machine learning,and advanced characterization technologies to provide a comprehensive understanding of the structure-performance relationship of electrocatalysts and the reaction pathways of the oxygen redox reactions.Finally,we discussed the challenges and prospects related to designing advanced non-noble-metal bifunctional electrocatalysts for ZABs.

Comparison of Stereotactic Body Radiotherapy Delivery Techniques for Early-Stage Lung Cancer Using Lung Toxicity Modeling

Purpose: Lung toxicity is a primary side effect in stereotactic radiotherapy (SBRT) for early-stage non-small cell lung cancer (NSCLC). We aimed to use a set of radiobiological models to evaluate and compare modern IMRT delivery techniques with three-dimensional conformal techniques for SBRT treatment of NSCLC in terms of lung toxicity, and aimed to compare the results from different radiobiologcal models. Methods: Ten early-stage NSCLC patients treated with SBRT were retrospectively selected. Five treatment plans were generated to deliver 50 Gy in five fractions to the planning target volume for each case: a helical tomotherapy (HT) plan, two three-dimensional cofnromal radiotherapy (3D-CRT) plans using 6-MV and 10-MV photon beams respectively, and two volumetric modulated arc therapy (VMAT) plans using one and two arc fields respectively. The lung RDV was calculated with three parallel functional sub-unit (FSU) models and two normal tissue complication probability (NTCP) models. Results: Both the HT and VMAT plans showed significantly higher contralateral mean lung dose and lower ipsilateral mean lung dose compared to the 3D-CRT plans. There was no statistically significant difference in terms of lung toxicities between the IMRT and 3D-CRT techniques using either the FSU models or the NTCP models. Based on both the FSU and the NTCP models, there was strong correlation between lung toxicity and the mean lung dose in SBRT treatment plans. Conclusions: Based on both the NTCP and parallel FSU models, both IMRT and traditional 3D-CRT delivery techniques could achieve comparable lung sparing inn SBRT treatment of early-stage lung cancer. However, the validity of the radiobiological model results should be checked by clinical data.

Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.

Inverse design of mechanical metamaterial achieving a prescribedconstitutive curve

Besides exhibiting excellent capabilities such as energy absorption,phase-transforming metamaterials offer a vast design space for achieving nonlinear constitutive relations.This is facilitated by switching between different patterns under deformation.However,the related inverse design problem is quite challenging,due to the lack of appropriate mathematical formulation and the convergence issue in the post-buckling analysis of intermediate designs.In this work,periodic unit cells are explicitly described by the moving morphable voids method and effectively analyzed by eliminating the degrees of freedom in void regions.Furthermore,by exploring the Pareto frontiers between error and cost,an inverse design formulation is proposed for unit cells.This formulation aims to achieve a prescribed constitutive curve and is validated through numerical examples and experimental results.The design approach presented here can be extended to the inverse design of other types of mechanical metamaterials with prescribed nonlinear effective properties.

Machine learning for membrane design and discovery

Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and environment.This review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential solutions.Through an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation membranes.Furthermore,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm proposed.The challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.

Rationally designing electrolyte additives for highly improving cyclability of LiNi_(0.5)Mn_(1.5)O_(4)/Graphite cells

High voltage is necessary for high energy lithium-ion batteries but difficult to achieve because of the highly deteriorated cyclability of the batteries.A novel strategy is developed to extend cyclability of a high voltage lithium-ion battery,LiNi_(0.5)Mn_(1.5)O_(4)/Graphite(LNMO/Graphite)cell,which emphasizes a rational design of an electrolyte additive that can effectively construct protective interphases on anode and cathode and highly eliminate the effect of hydrogen fluoride(HF).5-Trifluoromethylpyridine-trime thyl lithium borate(LTFMP-TMB),is synthesized,featuring with multi-functionalities.Its anion TFMPTMB-tends to be enriched on cathode and can be preferentially oxidized yielding TMB and radical TFMP-.Both TMB and radical TFMP can combine HF and thus eliminate the detrimental effect of HF on cathode,while the TMB dragged on cathode thus takes a preferential oxidation and constructs a protective cathode interphase.On the other hand,LTFMP-TMB is preferentially reduced on anode and constructs a protective anode interphase.Consequently,a small amount of LTFMP-TMB(0.2%)in 1.0 M LiPF6in EC/DEC/EMC(3/2/5,wt%)results in a highly improved cyclability of LNMO/Graphite cell,with the capacity retention enhanced from 52%to 80%after 150 cycles at 0.5 C between 3.5 and 4.8 V.The as-developed strategy provides a model of designing electrolyte additives for improving cyclability of high voltage batteries.

Deep Insight of Design,Mechanism,and Cancer Theranostic Strategy of Nanozymes

Since the discovery of enzyme-like activity of Fe3O4 nanoparticles in 2007,nanozymes are becoming the promising substitutes for natural enzymes due to their advantages of high catalytic activity,low cost,mild reaction conditions,good stability,and suitable for large-scale production.Recently,with the cross fusion of nanomedicine and nanocatalysis,nanozyme-based theranostic strategies attract great attention,since the enzymatic reactions can be triggered in the tumor microenvironment to achieve good curative effect with substrate specificity and low side effects.Thus,various nanozymes have been developed and used for tumor therapy.In this review,more than 270 research articles are discussed systematically to present progress in the past five years.First,the discovery and development of nanozymes are summarized.Second,classification and catalytic mechanism of nanozymes are discussed.Third,activity prediction and rational design of nanozymes are focused by highlighting the methods of density functional theory,machine learning,biomimetic and chemical design.Then,synergistic theranostic strategy of nanozymes are introduced.Finally,current challenges and future prospects of nanozymes used for tumor theranostic are outlined,including selectivity,biosafety,repeatability and stability,in-depth catalytic mechanism,predicting and evaluating activities.

Polyneuropathy organomegaly endocrinopathy M-protein and skin changes syndrome with ascites as an early-stage manifestation:A case report

BACKGROUND Polyneuropathy organomegaly endocrinopathy M-protein and skin changes(POEMS)syndrome is a rare paraneoplastic syndrome caused by a potential plasma cell tumor.The clinical manifestations of POEMS syndrome are diverse.Due to the insidious onset and lack of specific early-stage manifestations,POEMS syndrome is easily misdiagnosed or never diagnosed,leading to delayed treatment.Neurological symptoms are usually the first clinical manifestation,while ascites is a rare symptom in patients with POEMS syndrome.CASE SUMMARY A female patient presented with unexplained ascites as an initial symptom,which is a rare early-stage manifestation of the condition.After 1 year,the patient gradually developed progressive renal impairment,anemia,polyserosal effusion,edema,swollen lymph nodes on the neck,armpits,and groin,and decreased muscle strength of the lower extremities.The patient was eventually diagnosed with POEMS syndrome after multidisciplinary team discussion.Treatment comprised bortezomib+dexamethasone,continuous renal replacement therapy,chest and abdominal closed drainage,transfusions of erythrocytes and platelets,and other symptomatic and supportive treatments.The patient’s condition initially improved after treatment.However,then her symptoms worsened,and she succumbed to the illness and died.CONCLUSION Ascites is a potential early manifestation of POEMS syndrome,and this diagnosis should be considered for patients with unexplained ascites.Furthermore,multidisciplinary team discussion is helpful in diagnosing POEMS syndrome.

Detection of the <i>PIK3CA</i>Mutation in Circulating Tumor DNA as a Possible Predictive Indicator for Poor Prognosis of Early-Stage Breast Cancer

Objectives: Circulating tumor DNA (ctDNA) is shown to provide the real-time genomic information of metastatic breast cancer. This study elucidates the clinico-pathological significance of ctDNA in early-stage breast cancer using the PIK3CA mutation as an indicator. Materials and Methods: Twenty-seven primary breast cancers without metastasis were surgically resected and pathologically diagnosed at the University of Tokyo Hospital, Japan. Genomic DNA of primary tumor was extracted from formalin-fixed and paraffin-embedded specimens. ctDNA was extracted from fresh-frozen plasma from patients. The PIK3CA mutations at E542K, E545K and H1047R were examined by Sanger sequencing or droplet digital PCR in 27 tumors and pre- and post-surgery plasma. Results: The PIK3CA mutations were detected in 13 (48%) of 27 primary tumors. These mutations did not significantly correlate with specific clinico-pathological characteristics of tumors. When ctDNA was examined, 4 (33%) of 12 cases carrying the mutated PIK3CA showed the identical mutation in pre-surgery plasma and 2 (50%) of them showed the identical mutations in post-surgery plasma. Interestingly, in these 2 cases in pathological stages IIIA and IA, fractional abundance of the mutated PIK3CA alleles to the total alleles in pre-surgery ctDNA was around 1% or more and was higher than that of the other two cases without PIK3CA mutations in post-surgery ctDNA. Conclusions: The PIK3CA mutation in ctDNA is detectable even in a subset of early-stage breast cancer. Furthermore, fractional abundance of the mutated PIK3CA in pre-surgery ctDNA could provide a possible predictive indicator for tumor burden and for choosing the appropriate adjuvant treatment of breast cancer.