Serine residues 726 and 780 have nonredundant roles regulating STAT5a activity in luminal breast cancer

The Human Intermediate Prolactin Receptor I-tail Contributes Breast Oncogenesis by Targeting Ras/MAPK Pathway

Prolactin and its receptor (PRLr) in humans are significantly involved in breast cancer pathogenesis. The intermediate form of human PRLr (hPRLrI) is produced by alternative splicing and has a novel 13 amino acid tail ("I-tail") gain. hPRLrI induces significant proliferation and anchorage-independent growth of normal mammary epithelia in vitro when coexpressed with the long form hPRLr (hPRLrL). hPRLrL and hPRLrI coexpression is necessary to induce the transformation of mammary epithelia in vivo. The I-tail is associated with the ubiquitin-like protein neural precursor cell expressed developmentally downregulated protein 8. Treatment with the neural precursor cell expressed developmentally downregulated protein 8-activating enzyme inhibitor pevonedistat resulted in increased hPRLrL and the death of breast cancer cells. The goal of this study was to determine the function of the hPRLrI I-tail in hPRLrL/hPRLrI-mediated mammary transformation. hPRLrL/hPRLrI and hPRLrL/hPRLrIΔ13 (I-tail removal mutant) were delivered to MCF10AT cells. Cell proliferation was decreased when hPRLrI I-tail was removed. I-tail deletion decreased anchorage-independent growth and attenuated cell migration. The I-tail was involved in Ras/MAPK signaling but not PI3K/Akt signaling pathway as shown by western blot. I-tail removal resulted in decreased hPRLrI stability. RNA-sequencing data revealed that I-tail removal resulted in differential gene expression induced by prolactin. Ingenuity Pathway Analysis revealed that the activity of ERK was attenuated. Treatment of breast cancer cells with ERK1/2 inhibitor ulixertinib resulted in decreased colony-forming ability and less proliferation. These studies suggest that the hPRLrI I-tail contributed to breast oncogenesis and may be a promising target for the development of new breast cancer therapies.

Prolactin levels and breast cancer risk by tumor expression of prolactin-related markers

BACKGROUND

Higher circulating prolactin has been associated with increased breast cancer risk. Prolactin binding to the prolactin receptor (PRLR) can activate the transcription factor STAT5, thus, we examined the association between plasma prolactin and breast cancer risk by tumor expression of PRLR, STAT5, and the upstream kinase JAK2.

METHODS

Using data from 745 cases and 2454 matched controls in the Nurses' Health Study, we conducted polytomous logistic regression to examine the association between prolactin (> 11 ng/mL vs. ≤ 11 ng/mL) measured within 10 years of diagnosis and breast cancer risk by PRLR (nuclear [N], cytoplasmic [C]), phosphorylated STAT5 (pSTAT5; N, C), and phosphorylated JAK2 (pJAK2; C) tumor expression. Analyses were conducted separately in premenopausal (n = 168 cases, 765 controls) and postmenopausal women (n = 577 cases, 1689 controls).

RESULTS

In premenopausal women, prolactin levels > 11 ng/mL were positively associated with risk of tumors positive for pSTAT5-N (OR 2.30, 95% CI 1.02-5.22) and pSTAT5-C (OR 1.64, 95% CI 1.01-2.65), but not tumors that were negative for these markers (OR 0.98, 95% CI 0.65-1.46 and OR 0.73, 95% CI 0.43-1.25; p-heterogeneity = 0.06 and 0.02, respectively). This was stronger when tumors were positive for both pSTAT5-N and pSTAT5-C (OR 2.88, 95% CI 1.14-7.25). No association was observed for PRLR or pJAK2 (positive or negative) and breast cancer risk among premenopausal women. Among postmenopausal women, plasma prolactin levels were positively associated with breast cancer risk irrespective of PRLR, pSTAT5, or pJAK2 expression (all p-heterogeneity ≥ 0.21).

CONCLUSION

We did not observe clear differences in the association between plasma prolactin and breast cancer risk by tumor expression of PRLR or pJAK2, although associations for premenopausal women were observed for pSTAT5 positive tumors only. While additional studies are needed, this suggests that prolactin may act on human breast tumor development through alternative pathways.

Integrative Analysis of Necroptosis-Related Signature for Predicting the Prognosis of Osteosarcoma.. [DOI: 10.21203/rs.3.rs-2241039/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background Osteosarcoma (OS) is the most common and malignant bone tumor among children and adolescents worldwide. Over decades, clinical treatment for osteosarcoma has proven to be intractable. Novel approaches, such as immunotherapy, face immune escape. Thus, exploring potential therapeutic targets for osteosarcoma is an urgent need. Method Gene expression data and clinical information were downloaded from Therapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO), and Univariate Cox regression analysis was used to identify prognostic necroptosis-related genes (NRGs). A non-negative matrix factorization algorithm (NMF) was used to cluster patients into various molecular subgroups with NRGs. We dealt with multi-collinearity with the least absolute shrinkage and selection operator (LASSO). Multivariate Cox regression was used to construct the prediction model that divided OS patients into two risk groups. The model's validity was assessed by time-dependent receiver operating characteristic (ROC) analysis. Different expression genes (DEGs) between these two groups were conducted for functional analysis, including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). Eight algorithms were carried out to evaluate the tumor microenvironment. These marker genes on the single-cell transcriptome were further labeled to explore whether their expression was cell-specific. Results Based on the model constructed by 5 NRGs (TLR4, STAT5A, IFNGR1, PYGM, CHMP4C), the patients were divided into two risk groups. Patients in the high-risk group suffered a poorer prognosis than those in the low-risk group. The nomogram was constructed and integrated with clinical features and gene signatures, demonstrating better predictive ability in training and testing cohorts. Immune cell infiltrations were highly associated with the risk score generated by Multivariate Cox. All 5 NRGs can be successfully marked on the feature plot of single-cell RNA-Seq, and two NRGs were associated with cell-specific genes of osteosarcoma pluripotency with statistical significance. Conclusion This study can provide a reference for diagnosing molecular subtyping and treating patients with OS.

STAT family of transcription factors in breast cancer: Pathogenesis and therapeutic opportunities and challenges

Breast cancer is the most commonly diagnosed cancer and second-leading cause of cancer deaths in women. Breast cancer stem cells (BCSCs) promote metastasis and therapeutic resistance contributing to tumor relapse. Through activating genes important for BCSCs, transcription factors contribute to breast cancer metastasis and therapeutic resistance, including the signal transducer and activator of transcription (STAT) family of transcription factors. The STAT family consists of six major isoforms, STAT1, STAT2, STAT3, STAT4, STAT5, and STAT6. Canonical STAT signaling is activated by the binding of an extracellular ligand to a cell-surface receptor followed by STAT phosphorylation, leading to STAT nuclear translocation and transactivation of target genes. It is important to note that STAT transcription factors exhibit diverse effects in breast cancer; some are either pro- or anti-tumorigenic while others maintain dual, context-dependent roles. Among the STAT transcription factors, STAT3 is the most widely studied STAT protein in breast cancer for its critical roles in promoting BCSCs, breast cancer cell proliferation, invasion, angiogenesis, metastasis, and immune evasion. Consequently, there have been substantial efforts in developing cancer therapeutics to target breast cancer with dysregulated STAT3 signaling. In this comprehensive review, we will summarize the diverse roles that each STAT family member plays in breast cancer pathobiology, as well as, the opportunities and challenges in pharmacologically targeting STAT proteins and their upstream activators in the context of breast cancer treatment.

Genomic Mutations of the STAT5 Transcription Factor Are Associated with Human Cancer and Immune Diseases

Signal transducer and activation of transcription 5 (STAT5) is a key transcription factor that regulates various biological processes in mammalian development. Aberrant regulation of STAT5 has also been causally linked to many diseases, including cancers and immune-related diseases. Although persistent activation of STAT5 due to dysregulation of the signaling cascade has been reported to be associated with the progression of solid tumors and leukemia, various genomic mutations of STAT5 have also been found to cause a wide range of diseases. The present review comprehensively summarizes results of recent studies evaluating the intrinsic function of STAT5 and the link between STAT5 mutations and human diseases. This review also describes the types of disease models useful for investigating the mechanism underlying STAT5-driven disease progression. These findings provide basic knowledge for understanding the regulatory mechanisms of STAT5 and the progression of various diseases resulting from aberrant regulation of STAT5. Moreover, this review may provide insights needed to create optimal disease models that reflect human disease associated STAT5 mutations and to design gene therapies to correct STAT5 mutations.

Prolactin receptor gene transcriptional control, regulatory modalities relevant to breast cancer resistance and invasiveness

The prolactin receptor (PRLR) is a member of the lactogen/cytokine receptor family, which mediates multiple actions of prolactin (PRL). PRL is a major hormone in the proliferation/differentiation of breast epithelium that is essential for lactation. It is also involved in breast cancer development, tumor growth and chemoresistance. Human PRLR expression is controlled at the transcriptional level by multiple promoters. Each promoter directs transcription/expression of a specific non-coding exon 1, a common non-coding exon 2 and coding exons E3-11. The identification of exon 11 of PRLR led to finding of alternative spliced products and two novel short forms (SF) that can inhibit the long form (LF) of PRLR activity with relevance in physiological regulation and breast cancer. Homo and heterodimers of LF and SF are formed in the absence of PRL that acts as a conformational modifier. Heterodimerization of SF with LF is a major mechanism through which SF inhibits some signaling pathways originating at the LF. Biochemical/molecular modeling approaches demonstrated that the human PRLR conformation stabilized by extracellular intramolecular S-S bonds and several amino acids in the extracellular D1 domain of PRLR SF are required for its inhibitory actions on PRLR LF-mediated functions. Studies in breast cancer cells demonstrated that the transcription of PRLR was directed by the preferentially utilized PIII promoter, which lacks an estrogen responsive element. Complex formation of non-DNA bound ERα dimer with Sp1 and C/EBPβ dimers bound to their sites at the PRLR promoter is required for basal activity. Estradiol induces transcriptional activation/expression of the PRLR gene, and subsequent studies revealed the essential role of autocrine PRL released by breast cancer cells and CDK7 in estradiol-induced PRLR promoter activation and upregulation. Other studies revealed stimulation of the PRLR promoter activity and PRLR LF protein by PRL in the absence of estrogen via the STAT5/phospho-ERα activation loop. Additionally, EGF/ERBB1 can induce the transcription of PRLR independent of estrogen and prolactin. The various regulatory modalities contributing to the upregulation of PRLR provide options for the development of therapeutic approaches to mitigate its participation in breast cancer progression and resistance.

Investigation of Interferon Gamma Activity Using Bioinformatics Methods

Breast cancer grows from the breast tissue and is a severe health problem worldwide. Genetics is believed to be the primary cause of all cases of breast cancer via gene mutation. Bioinformatics methodology has been used to determine the sequences and structures of bioactive substances. This study aimed to analyze the function and structure of the Interferon Gamma (IFNγ) in healthy controls and patients with breast cancer using bioinformatics methods. Blood samples were collected from 75 patients with breast cancer and 25 healthy subjects as control samples. The results showed transition mutation (30%) and transversion mutation (70%) in patients with breast cancer. Moreover, missense mutations (84%) and silent mutations (16%) were detected by BLAST. In addition, the amino acid of the IFNγ protein consisting of alpha-helical, β-sheet, and coil of secondary structure was determined in this study using BioEdit. The results of the physicochemical properties of the IFNγ protein reflect the function, stability, molecular weight, isoelectric point, and instability index of the IFNγ protein using ProtParam. Moreover, the results of mutation affected the percentage of alpha-helix, β-turns, and coil in breast cancer patients compared to healthy groups with reference of NCBI using PSIpred program. Additionally, the PHYRE2 server and RasMol program showed a tertiary structure of the IFNγ protein in breast cancer patients. Furthermore, the STRING program revealed the poly IFNγ protein interacted with other proteins to perform its functions normally. From the recorded data in the current study, it was concluded that IFNγ is considered a marker for patients with breast cancer.