组蛋白去乙酰化酶抑制剂在HR阳性HER-2阴性晚期乳腺癌的研究进展

组蛋白去乙酰化酶(histone deacetylase,HDAC)是可调节表观遗传学改变的组蛋白修饰酶,在一些肿瘤中HDACs被异常激活,与肿瘤进展和耐药密切相关。HDAC抑制剂(HDAC inhibitor,HDACi)通过调节肿瘤细胞的表观遗传属性,靶向性控制肿瘤细胞增殖、调节肿瘤细胞周期及修复DNA损伤。HDACi可抑制多个乳腺癌致癌信号通路,从而有可能逆转激素受体(hormone receptor,HR)阳性HER-2阴性乳腺癌的治疗耐药。本文将对HDACi在HR阳性HER-2阴性晚期乳腺癌治疗方面进行综述,探讨其在乳腺癌治疗领域中的应用前景。

Dose-dense paclitaxel plus carboplatin vs.epirubicin and cyclophosphamide with paclitaxel as adjuvant chemotherapy for high-risk triple-negative breast cancer

Objective:The objective of this open-label,randomized study was to compare dose-dense paclitaxel plus carboplatin(PCdd)with dose-dense epirubicin and cyclophosphamide followed by paclitaxel(ECdd-P)as an adjuvant chemotherapy for early triple-negative breast cancer(TNBC).Methods:We included Chinese patients with high recurrence risk TNBC who underwent primary breast cancer surgery.They were randomly assigned to receive PCdd[paclitaxel 150 mg/m2 on d 1 and carboplatin,the area under the curve,(AUC)=3 on d 2]or ECdd-P(epirubicin 80 mg/m2 divided in 2 d and cyclophosphamide 600 mg/m2 on d 1 for 4 cycles followed by paclitaxel 175 mg/m2 on d 1 for 4 cycles)every 2 weeks with granulocyte colony-stimulating factor(G-CSF)support.The primary endpoint was 3-year disease-free survival(DFS);the secondary endpoints were overall survival(OS)and safety.Results:The intent-to-treat population included 143 patients(70 in the PCdd arm and 73 in the ECdd-P arm).Compared with the ECdd-P arm,the PCdd arm had significantly higher 3-year DFS[93.9%vs.79.1%;hazard ratio(HR)=0.310;95%confidence interval(95%CI),0.137-0.704;log-rank,P=0.005]and OS(98.5%vs.92.9%;HR=0.142;95%CI,0.060-0.825;log-rank,P=0.028).Worse neutropenia(grade 3/4)was found in the ECdd-P than the PCdd arm(47.9%V5.21.4%,P=0.001).Conclusions:PCdd was superior to ECdd-P as an adjuvant chemotherapy for early TNBC with respect to improving the 3-year DFS and OS.PCdd also yielded lower hematological toxicity.Thus,PCdd might be a preferred regimen for early TNBC patients with a high recurrence risk.

Efficacy and safety of duloxetine in Chinese breast cancer patients with paclitaxel-induced peripheral neuropathy

Objective： Chemotherapy with paclitaxel is associated with significant neurotoxicity that may offset patients＇ quality of life and therapeutic benefits. This prospective, non-randomized control study evaluated the efficacy and safety of an antidepressant drug, duloxetine, at 30 or 60 mg/d, in the treatment of paclitaxel-induced peripheral neuropathy（PIPN） in Chinese breast cancer patients.Methods：A total of 102 patients with a median age of 50（range,25–60）years,treated in the Department of Medical Oncology,National Cancer Center/Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,between November 2014 and January 2017 were finally enrolled.Stratified by baseline characteristics,the patients were classified into two groups,receiving either duloxetine or alternative antineurotoxicity drugs.During the course of the paclitaxel regimen,the eligibility criteria included sensory neuropathy,as evaluated by the National Cancer Institute-Common Toxicity Criteria for Adverse Events.The treatment consisted of receiving 30 mg duloxetine（for the first 4 weeks）and 60 mg duloxetine for an additional 8 weeks,or any other anti-neurotoxicity drug daily during the same crossover period.The improvement associated with PIPN from the patient’s perspective were assessed by the Functional Assessment of Cancer Therapy-Taxane（FACT-Tax）Scales,which contained questions scored from 0 to 4（0,not at all;4,very much;total score range,0–44）.Results：Duloxetine was more effective in decreasing PIPN（odds ratio=5.426;95%confidence interval,1.898–15.514;P=0.002）.Between duloxetine group and control group,the median（25th–75th percentiles）decreasing difference in the FACT-Tax pain score was 4（2–6）vs.1（0–4）（P=0.005）.Conclusions：Duloxetine is a promising and safe option with tolerable toxicity at a dose of 60 mg/d for Chinese breast cancer patients with PIPN.Non-neuropathy adverse events were mild and similar in both groups.The major toxicities of duloxetine included nausea,constipation,somnolence,dizziness and distention of the eyes.Further examination of the benefits of duloxetine in the prevention of PIPN is required.

SEMI-PROXIMAL POINT METHOD FOR NONSMOOTH CONVEX-CONCAVE MINIMAX OPTIMIZATION

Minimax optimization problems are an important class of optimization problems arising from modern machine learning and traditional research areas.While there have been many numerical algorithms for solving smooth convex-concave minimax problems,numerical algorithms for nonsmooth convex-concave minimax problems are rare.This paper aims to develop an efficient numerical algorithm for a structured nonsmooth convex-concave minimax problem.A semi-proximal point method(SPP)is proposed,in which a quadratic convex-concave function is adopted for approximating the smooth part of the objective function and semi-proximal terms are added in each subproblem.This construction enables the subproblems at each iteration are solvable and even easily solved when the semiproximal terms are cleverly chosen.We prove the global convergence of our algorithm under mild assumptions,without requiring strong convexity-concavity condition.Under the locally metrical subregularity of the solution mapping,we prove that our algorithm has the linear rate of convergence.Preliminary numerical results are reported to verify the efficiency of our algorithm.

Entinostat,a classⅠselective histone deacetylase inhibitor,plus exemestane for Chinese patients with hormone receptor-positive advanced breast cancer:A multicenter,randomized,double-blind,placebo-controlled,phase 3 trial

Entinostat plus exemestane in hormone receptor-positive(HR+)advanced breast cancer(ABC)previously showed encouraging outcomes.This multicenter phase 3 trial evaluated the efficacy and safety of entinostat plus exemestane in Chinese patients with HR+ABC that relapsed/progressed after≥1 endocrine therapy.Patients were randomized(2:1)to oral exemestane 25 mg/day plus entinostat(n=235)or placebo(n=119)5 mg/week in 28-day cycles.The primary endpoint was the independent radiographic committee(IRC)-assessed progression-free survival(PFS).The median age was 52(range,28—75)years and 222(62.7%)patients were postmenopausal.CDK4/6 inhibitors and fulvestrant were previously used in 23(6.5%)and 92(26.0%)patients,respectively.The baseline characteristics were comparable between the entinostat and placebo groups.The median PFS was 6.32(95%CI,5.30—9.11)and 3.72(95%CI,1.91—5.49)months in the entinostat and placebo groups(HR,0.76;95%CI,0.58—0.98;P=0.046),respectively.Grade≥3 adverse events(AEs)occurred in 154(65.5%)patients in the entinostat group versus 23(19.3%)in the placebo group,and the most common grade≥3 treatment-related AEs were neutropenia[103(43.8%)],thrombocytopenia[20(8.5%)],and leucopenia[15(6.4%)].Entinostat plus exemestane significantly improved PFS compared with exemestane,with generally manageable toxicities in HR+ABC(ClinicalTrials.gov#NCT03538171).

A STOCHASTIC NEWTON METHOD FOR NONLINEAR EQUATIONS

In this paper,we study a stochastic Newton method for nonlinear equations,whose exact function information is difficult to obtain while only stochastic approximations are available.At each iteration of the proposed algorithm,an inexact Newton step is first computed based on stochastic zeroth-and first-order oracles.To encourage the possible reduction of the optimality error,we then take the unit step size if it is acceptable by an inexact Armijo line search condition.Otherwise,a small step size will be taken to help induce desired good properties.Then we investigate convergence properties of the proposed algorithm and obtain the almost sure global convergence under certain conditions.We also explore the computational complexities to find an approximate solution in terms of calls to stochastic zeroth-and first-order oracles,when the proposed algorithm returns a randomly chosen output.Furthermore,we analyze the local convergence properties of the algorithm and establish the local convergence rate in high probability.At last we present preliminary numerical tests and the results demonstrate the promising performances of the proposed algorithm.

Multi-omics fusion analysis models with machine learning predict survival of HER2-negative metastatic breast cancer: a multicenter prospective observational study

To the Editor:Oncology precision medicine aims to identify patientsmostlikely torespondeffectivelytotherapies.Efforts to establish a survival prediction model using a single platform have not yet met the precision medicine goals.

Targeted therapeutic options and future perspectives for HER2-positive breast cancer

Over the past 2 decades,there has been an extraordinary progress in the regimens developed for the treatment of human epidermal growth factor receptor 2(HER2)-positive breast cancer.Trastuzumab,pertuzumab,lapatinib,and ado-trastuzumab emtansine(T-DM1)are commonly recommended anti-HER2 target agents by the U.S.Food and Drug Administration.This review summarizes the most significant and updated research on clinical scenarios related to HER2-positive breast cancer management in order to revise the guidelines of everyday clinical practices.In this article,we present the data on anti-HER2 clinical research of neoadjuvant,adjuvant,and metastatic studies from the past 2 decades.We also highlight some of the promising strategies that should be critically considered.Lastly,this review lists some of the ongoing clinical trials,findings of which may soon be available.

The molecular tumor burden index as a response evaluation criterion in breast cancer

Circulating tumor DNA(ctDNA)is a potential biomarker of prognosis and therapeutic response.We conducted this study to explore the role of the molecular tumor burden index(mTBI)in ctDNA as a therapeutic response and prognostic biomarker in a larger cohort prospective phase III randomized multicenter study.We collected 291 plasma samples from 125 metastatic breast cancer patients from the CAMELLIA study(NCT01917279).Target-capture deep sequencing of 1021 genes was performed to detect somatic variants in ctDNA from the plasma samples.The pretreatment mTBI value was correlated with tumor burden(P=0.025).Patients with high-level pretreatment mTBI had shorter overall survival than patients with low-level pretreatment mTBI,and the median overall survival was 40.9 months and 68.4 months,respectively(P=0.011).Patients with mTBI decrease to less than 0.02%at the first tumor evaluation had longer progression-free survival and overall survival(P<0.001 and P=0.007,respectively).The mTBI has good sensitivity to identify complete response/partial response and progressive disease based on computed tomography scans(88.5%and 87.5%,respectively).The patients classified as molecular responders had longer progression-free survival and overall survival than the nonmolecular responders in the overall cohort(P<0.001 and P=0.036,respectively),as well as in the cohort in which computed tomography scans were defined as representing stable disease(P=0.027 and P=0.015,respectively).The mTBI in ctDNA detected in liquid biopsies is a potential biomarker of therapeutic response and prognosis in patients with metastatic breast cancer.

Application of informatics in cancer research and clinical practice:Opportunities and challenges

Cancer informatics has significantly progressed in the big data era.We summarize the application of informatics approaches to the cancer domain from both the informatics perspective(e.g.,data management and data science)and the clinical perspective(e.g.,cancer screening,risk assessment,diagnosis,treatment,and prognosis).We discuss various informatics methods and tools that are widely applied in cancer research and practices,such as cancer databases,data standards,terminologies,high‐throughput omics data mining,machine‐learning algorithms,artificial intelligence imaging,and intelligent radiation.We also address the informatics challenges within the cancer field that pursue better treatment decisions and patient outcomes,and focus on how informatics can provide opportunities for cancer research and practices.Finally,we conclude that the interdisciplinary nature of cancer informatics and collaborations are major drivers for future research and applications in clinical practices.It is hoped that this review is instrumental for cancer researchers and clinicians with its informatics‐specific insights.