Surgical management of breast cancer often results in the absence of the breast. However, existing breast reconstruction methods may not meet the need for a replacement tissue. Tissue engineering with the use of emerging materials offers the promise of generating appropriate replacements. Three-dimensional (3D) printing technology has seen a significantly increased interest and application in medically-related fields in the recent years. This has been especially true in complex medical situations particularly when abnormal or complicated anatomical surgical considerations or precise reconstructive procedures are contemplated. In addition, 3D bio-printing which combines cells with bio-material scaffolds offers an exciting technology with significant applications in the field of tissue engineering. The purpose of this manuscript was to review a number of studies in which 3D printing technology has been used in breast reconstructive surgical procedures, and future directions and applications of 3D bio-printing.

Background: Thyroid carcinoma (THCA) is the most common endocrine-related malignant tumor. Despite the good prognosis, some THCA patients may deteriorate into more aggressive diseases, leading to poor survival. This may be alleviated by developing a novel model to predict the risk of THCA, including recurrence and survival. Ferroptosis is an iron-dependent, oxidative, non-apoptotic form of cell death initially described in mammalian cells, and plays an important role in various cancers. To explore the potential prognostic value of ferroptosis in THCA, ferroptosis-related long non-coding RNAs (FRLs) were used to construct model for risk prediction of THCA.Methods: RNA-sequencing data of THCA patients and ferroptosis-related genes were downloaded from The Cancer Genome Atlas (TCGA) and FerrDb, respectively. A total of 502 patients with complete data were randomly separated into a training cohort and a validation cohort at the ratio of 2:1. The Pearson correlation coefficients were calculated to determine the correlation between ferroptosis-related genes (FRGs) and the corresponding lncRNAs, and those meeting the screening conditions were defined as FRLs. Gene Expression Omnibus (GEO) database and qRT-PCR were used to verify the expression level of FRLs in THCA tissues. Univariate and multivariate cox regression analysis were performed to construct a FRLs signature based on lowest Akaike information criterion (AIC) value in the training cohort, then further tested in the validation cohort and the entire cohort. Gene set enrichment analysis (GSEA) and functional enrichment analysis were used to analyze the biological functions and signal pathways related to differentially expressed genes between the high-risk and low-risk groups. Finally, the relative abundance of different tumor-infiltrating immune cells were calculated by CIBERSORT algorithm.Results: The patients were divided into high-risk group and low-risk group based on a 5-FRLs signature (AC055720.2, DPP4-DT, AC012038.2, LINC02454 and LINC00900) in training cohort, validation cohort and entire cohort. Through Kaplan–Meier analysis and area under ROC curve (AUC) value, patients in the high-risk group exhibited worse prognosis than patients in the low-risk group. GEO database and qRT-PCR confirmed that LINC02454 and LINC00900 were up-regulated in THCA. Univariate and multivariate cox regression analyses showed that the risk score was an independent prognostic indicator. GSEA and functional enrichment analysis confirmed that immune-related pathways against cancer were significantly activated in the low-risk THCA patients. Further analysis showed that the immune cells such as plasma cells, T cells CD8 and macrophages M1, and the expression of immune checkpoint molecules, including PD-1, PD-L1, CTLA4, and LAG3, were remarkably higher in the low-risk group.Conclusion: Our study used the TCGA THCA dataset to construct a novel FRLs prognostic model which could precisely predict the prognosis of THCA patients. These FRLs potentially mediate anti-tumor immunity and serve as therapeutic targets for THCA, which provided the novel insight into treatment of THCA.

Docetaxel (DTX)-based chemotherapy significantly eliminates rest cancerous cells and decreases the risk of death, thus remaining the mainstay of treatment for operable breast cancer (BCa). However, resistance or incomplete response to DTX occurs frequently, resulting in disease recurrence and poor prognosis. There is an urgent need to identify and understand the key factors and corresponding molecular bases driving this complicated pathogenesis. Herein, both data mining and profiling analysis using clinical BCa biopsies showed that expression levels of the nuclear receptor subfamily 2, group F, member 6 (NR2F6), a recently characterized central transcription factor for cancer immune surveillance, were significantly downregulated in DTX-resistant BCa. This downregulation, possibly regulated by leptin signaling, predicted a poor postoperative chemotherapy survival in DTX-resistant BCa. In both genetically engineered cell models and patient-derived xenograft models, we provided evidence that BCa cells with insufficient NR2F6 expression were less responsive to DTX treatment. Mechanistically, NR2F6 functioned as a potent corepressor of platelet-derived growth factor B receptor gene (PDGFRB) transcription by recruiting HDAC2 onto the PDGFRB promoter. Stable PDGFRB inhibition ameliorated NR2F6 deficiency-impaired response to DTX in BCa cells, indicating that NR2F6’s effect on DTX response is mediated, at least in part, through transcriptional repression of PDGFRB. Collectively, our findings define NR2F6 as an negative regulator of cell survival and DTX resistance, probably by serving as a convergent point linking leptin signaling and PDGF-B/PDGFRβ axis, in BCa cells.