Clinical value of next-generation sequencing in guiding decisions regarding endocrine therapy for advanced HR-positive/HER-2-negative breast cancer

Objective: The mechanism of acquired gene mutation plays a major role in resistance to endocrine therapy in hormone receptor(HR)-positive advanced breast cancer. Circulating tumor DNA(ctDNA) has been allowed for the assessment of the genomic profiles of patients with advanced cancer. We performed this study to search for molecular markers of endocrine therapy efficacy and to explore the clinical value of ctDNA to guide precise endocrine therapy for HR-positive/human epidermal growth factor receptor-2(HER-2)-negative metastatic breast cancer patients.Methods: In this open-label, multicohort, prospective study, patients were assigned to four parallel cohorts and matched according to mutations identified in ctDNA: 1) activation of the phosphatidylinositol-3-kinase(PI3K)/AKT/mammalian target of rapamycin(mTOR) signaling pathway preferred mTOR inhibitor combined with endocrine therapy;2) estrogen receptor 1(ESR1) mutation preferred fulvestrant;3) HER-2 mutations preferred pyrotinib;and 4) no actionable mutations received treatment according to the clinical situation. In all cohorts, patients were divided into compliance group and violation group. The primary outcome measure was progression-free survival(PFS), and the secondary outcome measure was overall survival(OS).Results: In all cohorts, the combined median PFS was 4.9 months, and median PFS for the compliance and violation groups was 6.0 and 3.0 months, respectively [P=0.022, hazard ratio(HR)=0.57]. Multivariate Cox regression model showed the risk of disease progression was lower in compliance group than in violation group(P=0.023, HR=0.55). Among the patients with HER-2 mutations, the median PFS was 11.1 months in the compliance group and 2.2 months in the violation group(P=0.011, HR=0.20). There was no significant difference in the median PFS between patients who did and did not comply with the treatment protocol in patients with activation of the PI3K/AKT/mTOR or ESR1 mutation.Conclusions: The results suggest that ctDNA may help to guide the optimal endocrine therapy strategy for metastatic breast cancer patients and to achieve a better PFS. Next-generation sequencing(NGS) detection could aid in distinguishing patients with HER-2 mutation and developing new treatment strategies.

Hypotheses explaining cancer metastasis

Cancer metastasis is the most important factor causing patients death. Cancer diseases will be controllable if metastasis does not happen. Concerning the mechanism of cancer metastasis, there are still many points to be clarified. Currently, the mechanism of cancer metastasis has been explained from several aspects of its biological behaviors. Here we briefly summarized some newly-developed metastasis models to provide a global glance at this topic.

The therapy and mechanisms of replication-deficient recombinant adenovirus Ad-p14ARF in hepatocellular carcinoma

Objective: To study the therapeutic effect and mechanisms of recombinant adenovirus Ad-p14ARF in hepatocel- lular carcinoma cell lines. Methods: Morphology and trypan blue assay were adopted to evaluate the proliferation of different liver cancer cells after Ad-p14ARF infection. Cell apoptosis was confirmed by detecting phosphatidylserine (PS) externaliza- tion with Annexin V/PI double staining. Western blotting assay analyzed the expression of related proteins. Subcutaneous tumor model of BEL7402 was established to evaluate the therapeutic ability of Ad-p14ARF. Results: Ad-p14ARF suppressed cell growth, proliferation and promoted cell apoptosis of cancer cell lines with different genetic background. Ad-p14ARF in- hibited growth of liver cancer cells (HepG2, BEL7402) in a dose-dependent manner. Ad-p14ARF leaded to overexpression of Bax and p21, which were the downstream regulating genes of p53. Ad-p14ARF suppressed tumor growth significantly in the experimental therapy in nude mice bearing subcutaneous tumor of BEL7402. Conclusion: P14ARF gene is a powerful tumor suppressor gene to be used in cancer gene therapy. It may play an important role in gene therapy against the malignancies in the future.

Bioinformatic exploration of MTAl-regulated gene networks in colon cancer

Metastasis-associated gene 1 （MTA1） controls a series of biological processes in tumor progression. Tumor progression is a complex process regulated by a gene network. The global cancer gene regulatory network must be analyzed to determine the position of MTA1 in the molecular network and its cooperative genes by further exploring the biological functions of this gene. We used TCGA data sets and GeneCards database to screen MTA1- related genes. GO and KEGG pathway analyses were conducted with DAVID and gene network analysis via STRING and Cytoscape. Results showed that in the development of colon cancer, MTA1 is linked to certain signal pathways, such as Wnt/Notch/nucleotide excision repair pathways. The findings also suggested that MTA1 demonstrates the closest relationship in a coregulation process with the key molecules AKT1, EP300, CREBBP, SMARCA4, RHOA, and CAD. These results lead MTAI exploration to an in-depth investigation in different directions, such as Wnt, Notch, and DNA repair.

Extracellular matrix-derived mechanical force governs breast cancer cell stemness and quiescence transition through integrin-DDR signaling

The extracellular matrix(ECM)serves as signals that regulate specific cell states in tumor tissues.Increasing evidence suggests that extracellular biomechanical force signals are critical in tumor progression.In this study,we aimed to explore the influence of ECM-derived biomechanical force on breast cancer cell status.Experiments were conducted using 3D collagen,fibrinogen.

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.

3D printing robot:model optimization and image compensation

A novel 7-axis robot for industrial large 3D printing applications is presented in this paper, which is developed by Institute of Robotics and Automatic Information System, Nankai University. Base on the prototype, the mechanism on three-dimensional printing is deeply dissected. By investigating the reason of color distortions in 3D printing, a novel multistep compensation algorithm based on model optimization and image compensation is developed. Finally, the experimental results show the performance of the 3D printing robot platform and the proposed algorithms.

A hidden translatome in tumors——the coding lncRNAs

Long noncoding RNAs(lncRNAs)have been extensively identified in eukaryotic genomes and have been shown to play critical roles in the development of multiple cancers.Through the application and development of ribosome analysis and sequencing technologies,advanced studies have discovered the translation of lncRNAs.Although lncRNAs were originally defined as noncoding RNAs,many lncRNAs actually contain small open reading frames that are translated into peptides.This opens a broad area for the functional investigation of lncRNAs.Here,we introduce prospective methods and databases for screening lncRNAs with functional polypeptides.We also summarize the specific lncRNA-encoded proteins and their molecular mechanisms that promote or inhibit cancerous.Importantly,the role of lncRNA-encoded peptides/proteins holds promise in cancer research,but some potential challenges remain unresolved.This review includes reports on lncRNA-encoded peptides or proteins in cancer,aiming to provide theoretical basis and related references to facilitate the discovery of more functional peptides encoded by lncRNA,and to further develop new anti-cancer therapeutic targets as well as clinical biomarkers of diagnosis and prognosis.

Mesoscience in cell biology and cancer research

Mesoscale characteristics and their interdimensional correlation are the focus of contemporary interdisciplinary research.Mesoscience is a discipline that has the potential to radically update the existing knowledge structure,which differs from the conventional unit-scale and system-scale research models,revealing a previously untouchable area for scientific research.Integrative biology research aims to dissect the complex problems of life systems by conducting comprehensive research and integrating various disciplines from all biological levels of the living organism.However,the mesoscientific issues between different research units are neglected and challenging.Mesoscale research in biology requires the integration of research theories and methods from other disciplines(mathematics,physics,engineering,and even visual imaging)to investigate theoretical and frontier questions of biological processes through experiments,computations,and modeling.We reviewed integrative paradigms and methods for the biological mesoscale problems(focusing on oncology research)and prospected the potential of their multiple dimensions and upcoming challenges.We expect to establish an interactive and collaborative theoretical platform for further expanding the depth and width of our understanding on the nature of biology.