Материал из hpluswiki
Перейти к навигации Перейти к поиску

Amphiregulin precursor (AR) (Colorectum cell-derived growth factor) (CRDGF) [AREGB] [SDGF]


Targeting amphiregulin (AREG) derived from senescent stromal cells diminishes cancer resistance and averts programmed cell death 1 ligand (PD-L1)-mediated immunosuppression.

Aging is characterized by a progressive loss of physiological integrity, while cancer represents one of the primary pathological factors that severely threaten human lifespan and healthspan. In clinical oncology, drug resistance limits the efficacy of most anticancer treatments, and identification of major mechanisms remains a key to solve this challenging issue. Here, we highlight the multifaceted senescence-associated secretory phenotype (SASP), which comprises numerous soluble factors including amphiregulin (AREG). Production of AREG is triggered by DNA damage to stromal cells, which passively enter senescence in the tumor microenvironment (TME), a process that remarkably enhances cancer malignancy including acquired resistance mediated by EGFR. Furthermore, paracrine AREG induces programmed cell death 1 ligand (PD-L1) expression in recipient cancer cells and creates an immunosuppressive TME via immune checkpoint activation against cytotoxic lymphocytes. Targeting AREG not only minimized chemoresistance of cancer cells, but also restored immunocompetency when combined with classical chemotherapy in humanized animals. Our study underscores the potential of in vivo SASP in driving the TME-mediated drug resistance and shaping an immunosuppressive niche, and provides the proof of principle of targeting major SASP factors to improve therapeutic outcome in cancer medicine, the success of which can substantially reduce aging-related morbidity and mortality.

MeSH Terms

  • Amphiregulin
  • Animals
  • Antineoplastic Agents
  • B7-H1 Antigen
  • Cells, Cultured
  • Cellular Senescence
  • Drug Resistance, Neoplasm
  • Humans
  • Mice
  • Mice, Inbred NOD
  • Mice, SCID
  • Stromal Cells
  • Tumor Microenvironment


  • aging
  • amphiregulin
  • cancer resistance
  • clinical biomarker
  • combinational treatment
  • programmed cell death 1 ligand
  • senescence-associated secretory phenotype
  • stroma

Regulatory T-cells regulate neonatal heart regeneration by potentiating cardiomyocyte proliferation in a paracrine manner.

The neonatal mouse heart is capable of transiently regenerating after injury from postnatal day (P) 0-7 and macrophages are found important in this process. However, whether macrophages alone are sufficient to orchestrate this regeneration; what regulates cardiomyocyte proliferation; why cardiomyocytes do not proliferate after P7; and whether adaptive immune cells such as regulatory T-cells (Treg) influence neonatal heart regeneration have less studied.  : We employed both loss- and gain-of-function transgenic mouse models to study the role of Treg in neonatal heart regeneration. In loss-of-function studies, we treated mice with the lytic anti-CD25 antibody that specifically depletes Treg; or we treated FOXP3 with diphtheria toxin that specifically ablates Treg. In gain-of-function studies, we adoptively transferred hCD2 Treg from NOD.[i]Foxp3[/i] to NOD/SCID that contain Treg as the only T-cell population. Furthermore, we performed single-cell RNA-sequencing of Treg to uncover paracrine factors essential for cardiomyocyte proliferation.  : Unlike their wild type counterparts, NOD/SCID mice that are deficient in T-cells but harbor macrophages fail to regenerate their injured myocardium at as early as P3. During the first week of injury, Treg are recruited to the injured cardiac muscle but their depletion contributes to more severe cardiac fibrosis. On the other hand, adoptive transfer of Treg results in mitigated fibrosis and enhanced proliferation and function of the injured cardiac muscle. Mechanistically, single-cell transcriptomic profiling reveals that Treg could be a source of regenerative factors. Treg directly promote proliferation of both mouse and human cardiomyocytes in a paracrine manner; and their secreted factors such as CCL24, GAS6 or AREG potentiate neonatal cardiomyocyte proliferation. By comparing the regenerating P3 and non-regenerating P8 heart, there is a significant increase in the absolute number of intracardiac Treg but the whole transcriptomes of these Treg do not differ regardless of whether the neonatal heart regenerates. Furthermore, even adult Treg, given sufficient quantity, possess the same regenerative capability.  : Our results demonstrate a regenerative role of Treg in neonatal heart regeneration. Treg can directly facilitate cardiomyocyte proliferation in a paracrine manner.

MeSH Terms

  • Adoptive Transfer
  • Aging
  • Animals
  • Animals, Newborn
  • Cell Proliferation
  • Fibrosis
  • Forkhead Transcription Factors
  • Gene Expression Regulation, Developmental
  • Heart
  • Humans
  • Immunity, Innate
  • Loss of Function Mutation
  • Macrophages
  • Mice, Inbred NOD
  • Mice, SCID
  • Myocardial Infarction
  • Myocytes, Cardiac
  • Paracrine Communication
  • Regeneration
  • T-Lymphocytes, Regulatory
  • Transcriptome
  • Up-Regulation


  • CD4 regulatory T-cells
  • cardiac fibrosis
  • cardiomyocyte proliferation
  • heart regeneration
  • macrophages
  • single-cell RNA-seq

Effects of aging on gene expression and mitochondrial DNA in the equine oocyte and follicle cells.

We hypothesised that advanced mare age is associated with follicle and oocyte gene alterations. The aims of the study were to examine quantitative and temporal differences in mRNA for LH receptor (LHR), amphiregulin (AREG) and epiregulin (EREG) in granulosa cells, phosphodiesterase (PDE) 4D in cumulus cells and PDE3A, G-protein-coupled receptor 3 (GPR3), growth differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15) and mitochondrial (mt) DNA in oocytes. Samples were collected from dominant follicles of Young (3-12 years) and Old (≥20 years) mares at 0, 6, 9 and 12h after administration of equine recombinant LH. LHR mRNA declined after 0h in Young mares, with no time effect in Old mares. For both ages, gene expression of AREG was elevated at 6 and 9h and EREG was expression was elevated at 9h, with higher expression in Old than Young mares. Cumulus cell PDE4D expression increased by 6h (Old) and 12h (Young). Oocyte GPR3 expression peaked at 9 and 12h in Young and Old mares, respectively. Expression of PDE3A increased at 6h, with the increase greater in oocytes from Old than Young mares at 6 and 9h. Mean GDF9 and BMP15 transcripts were higher in Young than Old, with a peak at 6h. Copy numbers of mtDNA did not vary over time in oocytes from Young mares, but a temporal decrease was observed in oocytes from Old mares. The results support an age-associated asynchrony in the expression of genes that are essential for follicular and oocyte maturation before ovulation.

MeSH Terms

  • Aging
  • Amphiregulin
  • Animals
  • Bone Morphogenetic Protein 15
  • Cumulus Cells
  • Cyclic Nucleotide Phosphodiesterases, Type 4
  • DNA, Mitochondrial
  • Epiregulin
  • Female
  • Gene Expression
  • Growth Differentiation Factor 9
  • Horses
  • Oocytes
  • Ovarian Follicle
  • Receptors, LH
  • Transcriptome

Aging impacts transcriptomes but not genomes of hormone-dependent breast cancers.

Age is one of the most important risk factors for human malignancies, including breast cancer; in addition, age at diagnosis has been shown to be an independent indicator of breast cancer prognosis. Except for inherited forms of breast cancer, however, there is little genetic or epigenetic understanding of the biological basis linking aging with sporadic breast cancer incidence and its clinical behavior. DNA and RNA samples from matched estrogen receptor (ER)-positive sporadic breast cancers diagnosed in either younger (age <or= 45 years) or older (age >or= 70 years) Caucasian women were analyzed by array comparative genomic hybridization and by expression microarrays. Array comparative genomic hybridization data were analyzed using hierarchical clustering and supervised age cohort comparisons. Expression microarray data were analyzed using hierarchical clustering and gene set enrichment analysis; differential gene expression was also determined by conditional permutation, and an age signature was derived using prediction analysis of microarrays. Hierarchical clustering of genome-wide copy-number changes in 71 ER-positive DNA samples (27 younger women, 44 older women) demonstrated two age-independent genotypes; one with few genomic changes other than 1q gain/16q loss, and another with amplifications and low-level gains/losses. Age cohort comparisons showed no significant differences in total or site-specific genomic breaks and amplicon frequencies. Hierarchical clustering of 5.1 K genes variably expressed in 101 ER-positive RNA samples (53 younger women, 48 older women) identified six transcriptome subtypes with an apparent age bias (P < 0.05). Samples with higher expression of a poor outcome-associated proliferation signature were predominantly (65%) younger cases. Supervised analysis identified cancer-associated genes differentially expressed between the cohorts; with younger cases expressing more cell cycle genes and more than threefold higher levels of the growth factor amphiregulin (AREG), and with older cases expressing higher levels of four different homeobox (HOX) genes in addition to ER (ESR1). An age signature validated against two other independent breast cancer datasets proved to have >80% accuracy in discerning younger from older ER-positive breast cancer cases with characteristic differences in AREG and ESR1 expression. These findings suggest that epigenetic transcriptome changes, more than genotypic variation, account for age-associated differences in sporadic breast cancer incidence and prognosis.

MeSH Terms

  • Adult
  • Aged
  • Aging
  • Biomarkers, Tumor
  • Breast Neoplasms
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Genome, Human
  • Humans
  • Middle Aged
  • Neoplasms, Hormone-Dependent
  • Nucleic Acid Hybridization
  • Oligonucleotide Array Sequence Analysis
  • Prognosis
  • Receptor, ErbB-2
  • Receptors, Estrogen