FGFR2 risk SNPs confer breast cancer risk by augmenting oestrogen responsiveness

FGFR2 genetic variants in women with breast cancer

Black African populations are more genetically diverse than others, but genetic variants have been studied primarily in European populations. The present study examined the association of four single nucleotide polymorphisms (SNPs) of the fibroblast growth factor receptor 2, associated with breast cancer in non‑African populations, with breast cancer in Black, southern African women. Genomic DNA was extracted from whole blood samples of 1,001 patients with breast cancer and 1,006 controls (without breast cancer), and the rs2981582, rs35054928, rs2981578, and rs11200014 polymorphisms were analyzed using allele‑specific Kompetitive allele‑specific PCR™, and the χ2 or Fisher's exact tests were used to compare the genotype frequencies. There was no association between those SNPs and breast cancer in the studied cohort, although an association was identified between the C/C homozygote genotype for rs2981578 and invasive lobular carcinoma. These results show that genetic biomarkers of breast cancer risk in European populations are not necessarily associated with risk in sub‑Saharan African populations. African populations are more heterogenous than other populations, and the information from this population can help focus genetic risks of cancer in this understudied population.

FGFR families: biological functions and therapeutic interventions in tumors

There are five fibroblast growth factor receptors (FGFRs), namely, FGFR1-FGFR5. When FGFR binds to its ligand, namely, fibroblast growth factor (FGF), it dimerizes and autophosphorylates, thereby activating several key downstream pathways that play an important role in normal physiology, such as the Ras/Raf/mitogen-activated protein kinase kinase/extracellular signal-regulated kinase, phosphoinositide 3-kinase (PI3K)/AKT, phospholipase C gamma/diacylglycerol/protein kinase c, and signal transducer and activator of transcription pathways. Furthermore, as an oncogene, FGFR genetic alterations were found in 7.1% of tumors, and these alterations include gene amplification, gene mutations, gene fusions or rearrangements. Therefore, FGFR amplification, mutations, rearrangements, or fusions are considered as potential biomarkers of FGFR therapeutic response for tyrosine kinase inhibitors (TKIs). However, it is worth noting that with increased use, resistance to TKIs inevitably develops, such as the well-known gatekeeper mutations. Thus, overcoming the development of drug resistance becomes a serious problem. This review mainly outlines the FGFR family functions, related pathways, and therapeutic agents in tumors with the aim of obtaining better outcomes for cancer patients with FGFR changes. The information provided in this review may provide additional therapeutic ideas for tumor patients with FGFR abnormalities.

Genetic variants of dipeptidyl peptidase IV are linked to the clinicopathologic development of prostate cancer

CD26/dipeptidyl peptidase IV (DPP4) is a multifunctional cell-surface glycoprotein widely found in many cell types, and a soluble form is present in body fluids. There is longstanding evidence indicating a tumour-promoting or -suppressive role of DPP4 in different cancer types. However, studies focusing on the impacts of genetic variants of DPP4 on cancers are very rare. Herein, we conducted a case-control study to evaluate whether single-nucleotide polymorphisms (SNPs) of DPP4 were associated with the risk or clinicopathologic development of prostate cancer (PCa). We genotyped four loci of DPP4 SNPs, including rs7608798 (A/G), rs3788979 (C/T), rs2268889 (T/C) and rs6741949 (G/C), using a TaqMan allelic discrimination assay in 704 PCa patients and 704 healthy controls. Our results showed that PCa patients with the DPP4 rs7608798 AG+GG genotype or rs2268889 TC+CC genotype had a higher risk of developing an advanced clinical primary tumour (cT) stage (adjusted odds ratio (AOR): 1.680, 95% confidence interval (CI): 1.062-2.659, p = 0.025; AOR: 1.693, 95% CI: 1.092-2.624, p = 0.018). Additionally, in The Cancer Genome Atlas (TCGA) database, we observed that lower DPP4 expression levels were correlated with higher Gleason scores, advanced cT and pathological stages, tumour metastasis, and shorter progression-free survival rates in PCa patients. Furthermore, overexpression of DPP4 suppressed migration/invasion of metastatic PC3 PCa cells. Our findings suggest that DPP4 levels may affect the progression of PCa, and the DPP4 rs7608798 and rs2268889 SNPs are associated with the clinicopathologic development of PCa in a Taiwanese population.

FGFR2 Controls Growth, Adhesion and Migration of Nontumorigenic Human Mammary Epithelial Cells by Regulation of Integrin β1 Degradation

The role of fibroblast growth factor receptor 2 (FGFR2), an important mediator of stromal paracrine and autocrine signals, in mammary gland morphogenesis and breast cancer has been extensively studied over the last years. However, the function of FGFR2 signalling in the initiation of mammary epithelial oncogenic transformation remains elusive. Here, FGFR2-dependent behaviour of nontumorigenic model of mammary epithelial cells was studied. In vitro analyses demonstrated that FGFR2 regulates epithelial cell communication with extracellular matrix (ECM) proteins. Silencing of FGFR2 significantly changed the phenotype of cell colonies in three-dimensional cultures, decreased integrins α2, α5 and β1 protein levels and affected integrin-driven processes, such as cell adhesion and migration. More detailed analysis revealed the FGFR2 knock-down-induced proteasomal degradation of integrin β1. Analysis of RNA-seq databases showed significantly decreased FGFR2 and ITGB1 mRNA levels in breast tumour samples, when compared to non-transformed tissues. Additionally, high risk healthy individuals were found to have disrupted correlation profiles of genes associated with FGFR2 and integrin signalling, cell adhesion/migration and ECM remodelling. Taken together, our results strongly suggest that FGFR2 loss with concomitant integrin β1 degradation is responsible for deregulation of epithelial cell-ECM interactions and this process may play an important role in the initiation of mammary gland epithelial tumorigenesis.

Transcriptional Profile of Human Pancreatic Acinar Ductal Metaplasia

BACKGROUND AND AIMS

Aberrant acinar to ductal metaplasia (ADM), one of the earliest events involved in exocrine pancreatic cancer development, is typically studied using pancreata from genetically engineered mouse models.

METHODS

We used primary, human pancreatic acinar cells from organ donors to evaluate the transcriptional and pathway profiles during the course of ADM.

RESULTS

Following 6 days of three-dimensional culture on Matrigel, acinar cells underwent morphological and molecular changes indicative of ADM. mRNA from 14 donors' paired cells (day 0, acinar phenotype and day 6, ductal phenotype) was subjected to whole transcriptome sequencing. Acinar cell specific genes were significantly downregulated in the samples from the day 6 cultures while ductal cell-specific genes were upregulated. Several regulons of ADM were identified including transcription factors with reduced activity (PTF1A, RBPJL, and BHLHA15) and those ductal and progenitor transcription factors with increased activity (HNF1B, SOX11, and SOX4). Cells with the ductal phenotype contained higher expression of genes increased in pancreatic cancer while cells with an acinar phenotype had lower expression of cancer-associated genes.

CONCLUSION

Our findings support the relevancy of human in vitro models to study pancreas cancer pathogenesis and exocrine cell plasticity.

Identification of potential target genes of honokiol in overcoming breast cancer resistance to tamoxifen

Background

Honokiol (HON) inhibits epidermal growth factor receptor (EGFR) signaling and increases the activity of erlotinib, an EGFR inhibitor, in human head and neck cancers. In this study, using a bioinformatics approach and in vitro experiments, we assessed the target genes of HON against breast cancer resistance to tamoxifen (TAM).

Materials and methods

Microarray data were obtained from GSE67916 and GSE85871 datasets to identify differentially expressed genes (DEGs). DEGs common between HON-treated and TAM-resistant cells were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and protein-protein interaction (PPI) networks were constructed. Selected genes were analyzed for genetic alterations, expression, prognostic value, and receiver operating characteristics (ROC). TAM-resistant MCF-7 (MCF-7 TAM-R) cells were generated and characterized for their resistance toward TAM. A combination of HON and TAM was used for cytotoxicity and gene expression analyses. Molecular docking was performed using the Molecular Operating Environment software.

Results

PPI network analysis revealed that FN1, FGFR2, and RET were the top three genes with the highest scores. A genetic alteration study of potential target genes revealed MMP16 and ERBB4 as the genes with the highest alterations among the breast cancer samples. Pathway enrichment analysis of FGFR2, RET, ERBB4, SOX2, FN1, and MMP16 showed that the genetic alterations herein were likely to impact the RTK-Ras pathway. The expression levels of RET, MMP16, and SOX2 were strongly correlated with prognostic power, with areas under the ROC curves (AUC) ​​of 1, 0.8, and 0.8, respectively. The HON and TAM combination increased TAM cytotoxicity in MCF-7 TAM-R cells by regulating the expression of potential target genes ret, ERBB4, SOX2, and FN1, as well as the TAM resistance regulatory genes including HES1, VIM, PCNA, TP53, and CASP7. Molecular docking results indicated that HON tended to bind RET, ErbB4, and the receptor protein Notch1 ankyrin domain more robustly than its native ligand.

Conclusion

HON could overcome breast cancer resistance to TAM, potentially by targeting FGFR2, RET, ERBB4, MMP16, FN1, and SOX2. However, further studies are required to validate these results.

CRISPRi screens in human iPSC-derived astrocytes elucidate regulators of distinct inflammatory reactive states

Astrocytes become reactive in response to insults to the central nervous system by adopting context-specific cellular signatures and outputs, but a systematic understanding of the underlying molecular mechanisms is lacking. In this study, we developed CRISPR interference screening in human induced pluripotent stem cell-derived astrocytes coupled to single-cell transcriptomics to systematically interrogate cytokine-induced inflammatory astrocyte reactivity. We found that autocrine-paracrine IL-6 and interferon signaling downstream of canonical NF-κB activation drove two distinct inflammatory reactive signatures, one promoted by STAT3 and the other inhibited by STAT3. These signatures overlapped with those observed in other experimental contexts, including mouse models, and their markers were upregulated in human brains in Alzheimer's disease and hypoxic-ischemic encephalopathy. Furthermore, we validated that markers of these signatures were regulated by STAT3 in vivo using a mouse model of neuroinflammation. These results and the platform that we established have the potential to guide the development of therapeutics to selectively modulate different aspects of inflammatory astrocyte reactivity.

Significance of the Estrogen Hormone and Single Nucleotide Polymorphisms in the Progression of Breast Cancer among Female

Breast cancer is one of the most frequent types of malignancies among women and is internationally recognized as the main reason for cancer-caused mortality. Most breast tumors are heterogeneous and genetically complicated due to the involvement of several genes. Therefore, it is clinically important to study genetic variants that increase the risk of breast cancer. It is identified that the presence of polymorphisms in genes encoding regulatory hormones is linked to a higher risk of breast cancer. Additionally, circulating estrogen levels are connected to aromatase (CYP19A1) genes, which is a recognized risk factor for breast cancer progression. In this paper, the authors present a review study on the effect of estrogen and its Single Nucleotide Polymorphisms (SNPs) in the occurrence of breast cancer. This review mainly aimed to find out the connection between CYP19A1 gene variations and the risk of breast cancer, as well as its clinical characteristics and prognosis. Due to the highly special activity of the CYP19A1 enzyme in steroid production, suppression of the targeted CYP19A1 is a focused medication for breast cancer patients, which has only minor adverse effects. Numerous clinical trials over the last decade have shown that Aromatase inhibitors (AIs) not only outperform tamoxifen in terms of effectiveness but also have a lower adverse effect profile.  The AI is now widely accepted as a routine therapy option for postmenopausal females with Estrogen receptor-positive (ER+) breast cancer. Furthermore, not only dysregulation of gene expression in different genes related to distinguished pathways, such as estrogen metabolism, is essential in the progression of breast cancer but also particular SNPs can play an essential role in particular genes, such as CYP19A1. Different studies have demonstrated that these SNPs can be located in different sites of these genes, which are collected in this review. In a nutshell, more specific clinical trials are required to demonstrate the precise meditative role of anti-estrogen drugs in the treatment of ER+ breast cancer patients. Furthermore, more genotype analyses are needed to confirm the role of SNPs in the progression of breast cancer.

FGF7/FGFR2-JunB signalling counteracts the effect of progesterone in luminal breast cancer

We have recently demonstrated that fibroblast growth factor receptor 2 (FGFR2)‐mediated signalling alters progesterone receptor (PR) activity and response of oestrogen receptor α (ER)‐positive (ER+) breast cancer (BCa) cell lines to anti‐ER agents. Little is known about whether the crosstalk between ER and PR, shown to be modulated by the hormonal background, might also be affected by FGFR2. Here, PR‐dependent behaviour of ER+ BCa cells was studied in the presence of oestrogen (E2) and progesterone (P4) and/or FGF7. In vitro analyses showed that FGF7/FGFR2 signalling: (a) abolished the effect of P4 on E2‐promoted 3D cell growth and response to tamoxifen; (b) regulated ER and PR expression and activity; (c) increased formation of ER–PR complexes; and (d) reversed P4‐triggered deregulation of ER‐dependent genes. Analysis of clinical data demonstrated that the prognostic value of FGFR2 varied between patients with different menopausal status; that is, high expression of FGFR2 was significantly associated with longer progression‐free survival (PFS) in postmenopausal patients, whereas there was no significant association in premenopausal patients. FGFR2 was found to positively correlate with the expression of JunB proto‐oncogene, AP‐1 transcription factor subunit (JUNB), an ER‐dependent gene, only in premenopausal patients. Molecular analyses revealed that the presence of JunB was a prerequisite for FGFR2‐mediated abrogation of P4‐induced inhibition of cell growth. Our results demonstrate for the first time that the FGF7/FGFR2–JunB axis abolishes the modulatory effects of PR on ER‐associated biological functions in premenopausal ER+ BCa. This may provide foundations for a better selection of patients for FGFR‐targeting therapeutic strategies.

The genomic and transcriptome characteristics of lung adenocarcinoma patients with previous breast cancer

Background

Breast cancer and lung cancer are the top two malignancies in the female population and the number of patients with breast cancer and subsequent primary lung cancer has increased significantly in recent years. However, the unique molecular characteristics of this group of patients remains unclear.

Purpose

To identify the genomic and transcriptome characteristics of primary lung adenocarcinoma patients with previous breast cancer by comparison with single primary lung adenocarcinoma (SPLA) patients.

Methods

The tumor and normal pulmonary tissue specimens of ten primary pulmonary adenocarcinoma patients with previous breast cancer (multiple primary cancer, MPC) and ten SPLA patients were prospectively collected. The whole exome sequencing (WES) and RNA sequencing (RNA-seq) were performed to analyze the gene mutation and expression differences between MPC and SPC patients.

Results

The results of WES indicated that the mutations of TRIM73, DLX6 and CNGB1 only existed in MPC patients. The results of RNA-seq manifested the occurrence of second primary lung adenocarcinoma in breast cancer patients was closely associated with cytokine-cytokine receptor action, autophagy, PI3L-Akt, cAMP and calcium ion signaling pathways. Besides, the expression levels of FGF10 and VEGFA genes were significantly increased in MPC patients.

Conclusion

The occurrence of second primary lung adenocarcinoma may be related to the cytokine-cytokine receptor action, autophagy, PI3L-Akt, cAMP and calcium ion signaling pathways. Furthermore, the mutations of TRIM73, DLX6 and CNGB1 and high expression of FGF10 and VEGFA might play an important role in the development of lung adenocarcinoma in breast cancer patients. However, more in-depth investigations are needed to verify above findings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09727-6.

Induced mammary cancer in rat models: pathogenesis, genetics, and relevance to female breast cancer

Mammary cancer, or breast cancer in women, is a polygenic disease with a complex etiopathogenesis. While much remains elusive regarding its origin, it is well established that chemical carcinogens and endogenous estrogens contribute significantly to the initiation and progression of this disease. Rats have been useful models to study induced mammary cancer. They develop mammary tumors with comparable histopathology to humans and exhibit differences in resistance or susceptibility to mammary cancer depending on strain. While some rat strains (e.g., Sprague-Dawley) readily form mammary tumors following treatment with the chemical carcinogen, 7,12-dimethylbenz[a]-anthracene (DMBA), other strains (e.g., Copenhagen) are resistant to DMBA-induced mammary carcinogenesis. Genetic linkage in inbred strains has identified strain-specific quantitative trait loci (QTLs) affecting mammary tumors, via mechanisms that act together to promote or attenuate, and include 24 QTLs controlling the outcome of chemical induction, 10 QTLs controlling the outcome of estrogen induction, and 4 QTLs controlling the outcome of irradiation induction. Moreover, and based on shared factors affecting mammary cancer etiopathogenesis between rats and humans, including orthologous risk regions between both species, rats have served as useful models for identifying methods for breast cancer prediction and treatment. These studies in rats, combined with alternative animal models that more closely mimic advanced stages of breast cancer and/or human lifestyles, will further improve our understanding of this complex disease.

Germline Variants in Angiogenesis-Related Genes Contribute to Clinical Outcome in Head and Neck Squamous Cell Carcinoma

Simple Summary

A high risk of relapse and treatment resistance are among the major challenges in locally advanced head and neck squamous cell carcinoma (HNSCC). Data show that common germline alterations in genes regulating angiogenesis may modulate treatment sensitivity, cancer progression, and prognosis, but relatively little is known about their role in HNSCC. Thus, our goal was to examine the effect of variation in these genes on survival outcomes in HNSCC patients receiving radiotherapy and cisplatin-based chemoradiotherapy. We identified genetic variants significantly affecting therapy results, constituting independent prognostic factors in these patients. Our results suggest that some polymorphisms in angiogenesis genes may be determinants of treatment efficacy and tumor aggressiveness in HNSCC, which may be of importance in standard therapy. These findings emphasize the potential value of the host genetic profile related to angiogenesis in assessing the risk of treatment failure.

Abstract

Fibroblast growth factor (FGF)/FGF receptor (FGFR), and platelet-derived growth factor (PDGF)/PDGF receptor (PDGFR) systems, as well as some matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs), are involved in various steps of angiogenesis. Data indicate that common germline variations in angiogenesis-regulating genes may modulate therapy results and cancer progression. However, whether these variants affect clinical outcome in head and neck squamous cell carcinoma (HNSCC) is unclear. Hence, we assessed the relationship between FGF/FGFR, PDGF/PDGFR, MMP, and TIMP genetic variants and treatment outcomes in HNSCC patients receiving radiotherapy (RT) alone or combined with cisplatin-based chemotherapy. In multivariate analysis, FGF2 rs1048201 CC homozygotes showed a higher risk of death (p = 0.039), while PDGFRA rs2228230 T was strongly associated with an increased risk of locoregional relapse (HR 2.49, p = 0.001) in the combination treatment subgroup. In the RT alone subset, MMP2 rs243865 TT carriers had a higher risk of locoregional recurrence (HR 2.92, p = 0.019), whereas PDGFRB rs246395 CC homozygotes were at increased risk of metastasis (HR 3.06, p = 0.041). The MMP2 rs7201 C and TIMP2 rs7501477 T were associated with a risk of locoregional failure in the entire cohort (p = 0.032 and 0.045, respectively). Furthermore, rs1048201, rs2228230, rs246395, rs243865, rs7201, and rs7201/rs7501477 were independent indicators of an unfavorable outcome. This study demonstrates that the FGF2, PDGFRA, PDGFRB, MMP2, and TIMP2 variants may contribute to treatment failure and poor prognosis in HNSCC.

Cell population-based framework of genetic epidemiology in the single-cell omics era

Genetic epidemiology is a rapidly advancing field due to the recent availability of large amounts of omics data. In recent years, it has become possible to obtain omics information at the single-cell level, so genetic epidemiological models need to be updated to integrate with single-cell expression data. In this perspective paper, we propose a cell population-based framework for genetic epidemiology in the single-cell era. In this framework, genetic diversity influences phenotypic diversity through the diversity of cell population profiles, which are defined as high-dimensional probability distributions of the state spaces of biomolecules of each omics layer. We discuss how biomolecular experimental measurement data can capture the different properties of this distribution. In particular, single-cell data constitute a sample from this population distribution where only some coordinate values are observable. From a data analysis standpoint, we introduce methodology for feature extraction from cell population profiles. Finally, we discuss how this framework can be applied not only to genetic epidemiology but also to systems biology.

A cyclic peptide retards the proliferation of DU145 prostate cancer cells in vitro and in vivo through inhibition of FGFR2

In malignancies, fibroblast growth factor receptors (FGFRs) signaling is reinforced through overexpression of fibroblast growth factors (FGFs) or their receptors. FGFR2 has been proposed as a target for cancer therapy, because both the expression and activation of FGFR2 are boosted in various malignant carcinomas. Although several chemicals have been designed against FGFR2, they did not exhibit enough specificity and might bring potential accumulated toxicity. In this study, we developed an epitope peptide (P5) and its cyclic derivative (DcP5) based on the structure of FGF2 to limit the activation of FGFR2. The anticancer activities of P5 and DcP5 were examined in vitro and in vivo. Our results demonstrated that P5 significantly inhibited the cell proliferation in FGFR2‐dependent manner in DU145 cells and retarded tumor growth in DU145 xenograft model with negligible toxicity toward normal organs. Further investigations found that the Gln4 and Glu6 residues of P5 bind to FGFR2 to abolish its activation. Moreover, we developed the P5 cyclic derivative, DcP5, which achieved reinforced stability and anticancer activity in vivo. Our findings suggest P5 and its cyclic derivative DcP5 as potential candidates for anticancer therapy.

Fibroblast growth factor receptor 2 gene (FGFR2) rs2981582T/C polymorphism and susceptibility to breast cancer in Saudi women

Fibroblast growth factor receptor 2 is a protein encoded by FGFR2 gene and plays an important role in cellular growth. This study was conducted to investigate a potential association of FGFR2 rs2981582 with breast cancer. DNA was obtained from 137 Formalin-fixed, paraffin-embedded tumors and 98 normal breast tissue samples. Genotypes were carried out with PCR-RFLP. The odds ratio and 95% confidence interval (CI) were used to evaluate the power of the associations. A significant association between FGFR2 rs2981582 C allele and susceptibility to breast cancer was found (p-value < 0.0001, Odds Ratio = 2.3, %95 CI (1.5–3.0). No significant differences in FGFR2 rs2981582 genotypes and alleles distribution among breast patients with different hormonal receptor status (p > 0.05) were detected. However, a significant difference was found in genotypes and alleles distribution in ER+, PR- and HER2 between breast cancer cases and controls. This study showed an association of FGFR2 rs2981582T/C with breast cancer in Saudi women, further large study is required to validate the results.

Single nucleotide polymorphism and expression of genes for immune competent cell proliferation and differentiation in radiation-exposed individuals

It is known that ionizing radiation influences the expression of the genes that play a key role in the mechanisms of maintaining the stability of cellular homeostasis. As a rule, changes in the transcriptome of an exposed cell occur within the first 24 hours following radiation exposure. And it predetermines early response in the case of genome damage. Later on modulations in gene transcription activity are also possible and could result in a carcinogenic effect. However, in order to find the role of exogenous factors (ionizing radiation), it is also necessary to take into account the contribution of endogenous factors that are able to modify gene transcription activity. This is especially important for long after the onset of radiation exposure. Single nucleotide polymorphisms located in regulatory regions of the genes may belong to this group of factors. The objective of the current study was to analyze the influence of ionizing radiation on the transcription activity of the STAT3, GATA3, NFkB1, PADI4 genes, which regulate proliferation and differentiation of immune competent human cells; and to assess the potential influence of single nucleotide polymorphisms located in regulatory regions of the genes on the amount of mRNA. The study involved people who had been chronically exposed due to releases of radioactive waste into the Techa River. It was observed that 60 years after the onset of radiation exposure changes in the transcription activity of the NFkB1 and PADI4 genes were registered in people with cumulative doses to RBM within the range 78–3510 mGy. In people who had been chronically exposed, the effect of allelic variations in rs1053023, rs4143094, rs28362491, rs874881 on the level of mRNAs of the STAT3, GATA3, PADI4, NFkB1 genes has not been established.

Novel lncRNAs Co-Expression Networks Identifies LINC00504 with Oncogenic Role in Luminal A Breast Cancer Cells

Long non-coding RNAs (lncRNAs) are functional transcripts with more than 200 nucleotides. These molecules exhibit great regulatory capacity and may act at different levels of gene expression regulation. Despite this regulatory versatility, the biology of these molecules is still poorly understood. Computational approaches are being increasingly used to elucidate biological mechanisms in which these lncRNAs may be involved. Co-expression networks can serve as great allies in elucidating the possible regulatory contexts in which these molecules are involved. Herein, we propose the use of the pipeline deposited in the RTN package to build lncRNAs co-expression networks using TCGA breast cancer (BC) cohort data. Worldwide, BC is the most common cancer in women and has great molecular heterogeneity. We identified an enriched co-expression network for the validation of relevant cell processes in the context of BC, including LINC00504. This lncRNA has increased expression in luminal subtype A samples, and is associated with prognosis in basal-like subtype. Silencing this lncRNA in luminal A cell lines resulted in decreased cell viability and colony formation. These results highlight the relevance of the proposed method for the identification of lncRNAs in specific biological contexts.

Gene Regulatory Network of ETS Domain Transcription Factors in Different Stages of Glioma

The ETS domain family of transcription factors is involved in a number of biological processes, and is commonly misregulated in various forms of cancer. Using microarray datasets from patients with different grades of glioma, we have analyzed the expression profiles of various ETS genes, and have identified ETV1, ELK3, ETV4, ELF4, and ETV6 as novel biomarkers for the identification of different glioma grades. We have further analyzed the gene regulatory networks of ETS transcription factors and compared them to previous microarray studies, where Elk-1-VP16 or PEA3-VP16 were overexpressed in neuroblastoma cell lines, and we identify unique and common regulatory networks for these ETS proteins.

A 'Real-Life' Experience on Automated Digital Image Analysis of FGFR2 Immunohistochemistry in Breast Cancer

We present here an assessment of a 'real-life' value of automated machine learning algorithm (AI) for examination of immunohistochemistry for fibroblast growth factor receptor-2 (FGFR2) in breast cancer (BC). Expression of FGFR2 in BC (n = 315) measured using a certified 3DHistech CaseViewer/QuantCenter software 2.3.0. was compared to the manual pathologic assessment in digital slides (PA). Results revealed: (i) substantial interrater agreement between AI and PA for dichotomized evaluation (Cohen's kappa = 0.61); (ii) strong correlation between AI and PA H-scores (Spearman r = 0.85, p < 0.001); (iii) a small constant error and a significant proportional error (Passing-Bablok regression y = 0.51 × X + 29.9, p < 0.001); (iv) discrepancies in H-score in cases of extreme (strongest/weakest) or heterogeneous FGFR2 expression and poor tissue quality. The time of AI was significantly longer (568 h) than that of the pathologist (32 h). This study shows that the described commercial machine learning algorithm can reliably execute a routine pathologic assessment, however, in some instances, human expertise is essential.

Hormonal Receptor Status Determines Prognostic Significance of FGFR2 in Invasive Breast Carcinoma

Simple Summary

FGFR2-ER-PR crosstalk leads to hormone-independent progression of breast cancer. In vitro, FGFR2 stimulates PR transcriptional activity and mediates resistance to anti-ER therapies. The postulated poor prognostic effect of FGFR2 overexpression has not been confirmed at clinical level. Our clinical data show that, counterintuitively, low expression of FGFR is linked to poor prognosis in breast cancer and its prognostic value is dependent on the hormonal receptor status, but not PR transcriptional activity. This shows, that the role of FGFR in breast cancer is more complex, which may explain unsatisfactory results of the clinical trials with FGFR inhibitors.

Abstract

Interaction between fibroblast growth factor receptor 2 (FGFR2) and estrogen/progesterone receptors (ER/PR) affects resistance to anti-ER therapies, however the prognostic value of FGFR2 in breast cancer (BCa) remains largely unexplored. We have recently showed in vitro that FGFR2-mediated signaling alters PR activity and response to anti-ER treatment. Herein, prognostic significance of FGFR2 in BCa was evaluated in relation to both ER/PR protein status and a molecular signature designed to reflect PR transcriptional activity. FGFR2 was examined in 353 BCa cases using immunohistochemistry and Nanostring-based RNA quantification. FGFR2 expression was higher in ER+PR+ and ER+PR- compared to ER−PR− cases (p < 0.001). Low FGFR2 was associated with higher grade (p < 0.001), higher Ki67 proliferation index (p < 0.001), and worse overall and disease-free survival (HR = 2.34 (95% CI: 1.26–4.34), p = 0.007 and HR = 2.22 (95% CI: 1.25–3.93), p = 0.006, respectively). The poor prognostic value of low FGFR2 was apparent in ER+PR+, but not in ER+PR− patients, and it did not depend on the expression level of PR-dependent genes. Despite the functional link between FGFR2 and ER/PR revealed by preclinical studies, the data showed a link between FGFR2 expression and poor prognosis in BCa patients.

Impact of fibroblast growth factor receptor 1 (FGFR1) amplification on the prognosis of breast cancer patients

Purpose

Various aberrations in the fibroblast growth factor receptor genes FGFR1, FGFR2, and FGFR3 are found in different cancers, including breast cancer (BC). This study analyzed the impact of FGFR amplification on the BC prognosis.

Methods

The study included 894 BC patients. The amplification rates of FGFR1, FGFR2, and FGFR3 were evaluated on tissue microarrays using fluorescence in situ hybridization (FISH). Associations between these parameters and prognosis were analyzed using multivariate Cox regression analyses.

Results

FGFR1 FISH was assessable in 503 samples, FGFR2 FISH in 447, and FGFR3 FISH in 562. The FGFR1 amplification rate was 6.6% (n = 33). Increased FGFR2 copy numbers were seen in 0.9% (n = 4); only one patient had FGFR3 amplification (0.2%). Most patients with FGFR1 amplification had luminal B-like tumors (69.7%, n = 23); only 32.6% (n = 153) of patients without FGFR1 amplification had luminal B-like BC. Other patient and tumor characteristics appeared similar between these two groups. Observed outcome differences between BC patients with and without FGFR1 amplification did not achieve statistical significance; however, there was a trend toward poorer distant metastasis-free survival in BC patients with FGFR1 amplification (HR = 2.08; 95% CI 0.98 to 4.39, P = 0.05).

Conclusion

FGFR1 amplification occurs most frequently in patients with luminal B-like BC. The study showed a nonsignificant correlation with the prognosis, probably due to the small sample size. Further research is therefore needed to address the role of FGFR1 amplifications in early BC patients. FGFR2 and FGFR3 amplifications are rare in patients with primary BC.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05865-2) contains supplementary material, which is available to authorized users.

Predicting breast cancer risk using interacting genetic and demographic factors and machine learning

Breast cancer (BC) is a multifactorial disease and the most common cancer in women worldwide. We describe a machine learning approach to identify a combination of interacting genetic variants (SNPs) and demographic risk factors for BC, especially factors related to both familial history (Group 1) and oestrogen metabolism (Group 2), for predicting BC risk. This approach identifies the best combinations of interacting genetic and demographic risk factors that yield the highest BC risk prediction accuracy. In tests on the Kuopio Breast Cancer Project (KBCP) dataset, our approach achieves a mean average precision (mAP) of 77.78 in predicting BC risk by using interacting genetic and Group 1 features, which is better than the mAPs of 74.19 and 73.65 achieved using only Group 1 features and interacting SNPs, respectively. Similarly, using interacting genetic and Group 2 features yields a mAP of 78.00, which outperforms the system based on only Group 2 features, which has a mAP of 72.57. Furthermore, the gene interaction maps built from genes associated with SNPs that interact with demographic risk factors indicate important BC-related biological entities, such as angiogenesis, apoptosis and oestrogen-related networks. The results also show that demographic risk factors are individually more important than genetic variants in predicting BC risk.

Fgf10/Fgfr2b Signaling in Mammary Gland Development, Homeostasis, and Cancer

Fibroblast growth factor 10 (Fgf10) is a secreted ligand acting via the Fibroblast growth factor receptor 2b (Fgfr2b). Fgf10/Fgfr2b signaling plays important roles both in the epithelium and in the mesenchyme during mammary gland development. Evidence in mice show that Fgf10 is critical for the induction of four out of five of the mammary placodes and for the formation of the white adipose tissue. Fgfr2b ligands also play important function in the maintenance of the terminal end buds, specialized structures at the tip of the ramified ducts during the postnatal phase of mammary gland development. Finally, in humans, FGF10 has been described to be expressed in 10% of the breast adenocarcinoma and activation of FGFR2b signaling correlates with a worse prognostic. Therefore, Fgf10 plays pleiotropic roles in both mammary gland development, homeostasis and cancer and elucidating its mechanism of action and cellular targets will be crucial to either enhance mammary gland development or to find innovative targets to treat aggressive breast cancer.

Beyond the coding genome: non-coding mutations and cancer

Latest advancements in genomics involving individuals from different races and geographical locations has led to the identification of thousands of common as well as rare genetic variants and copy number variations (CNVs). These studies have surprisingly revealed that the majority of genetic variation is not present within the coding region but rather in the non-coding region of the genome, which is also termed as "Medical Genome". This short review describes how mutations/variations within; regulatory sequences, architectural proteins and transcriptional regulators give rise to the aberrant gene expression profiles that drives cellular transformations and malignancies.

Identification of two novel breast cancer loci through large-scale genome-wide association study in the Japanese population

Genome-wide association studies (GWAS) have successfully identified about 70 genomic loci associated with breast cancer. Owing to the complexity of linkage disequilibrium and environmental exposures in different populations, it is essential to perform regional GWAS for better risk prediction. This study aimed to investigate the genetic architecture and to assess common genetic risk model of breast cancer with 6,669 breast cancer patients and 21,930 female controls in the Japanese population. This GWAS identified 11 genomic loci that surpass genome-wide significance threshold of P < 5.0 × 10⁻⁸ with nine previously reported loci and two novel loci that include rs9862599 on 3q13.11 (ALCAM) and rs75286142 on 21q22.12 (CLIC6-RUNX1). Validation study was carried out with 981 breast cancer cases and 1,394 controls from the Aichi Cancer Center. Pathway analyses of GWAS signals identified association of dopamine receptor medicated signaling and protein amino acid deacetylation with breast cancer. Weighted genetic risk score showed that individuals who were categorized in the highest risk group are approximately 3.7 times more likely to develop breast cancer compared to individuals in the lowest risk group. This well-powered GWAS is a representative study to identify SNPs that are associated with breast cancer in the Japanese population.

Long non-coding RNAs identify a subset of luminal muscle-invasive bladder cancer patients with favorable prognosis

BACKGROUND

Muscle-invasive bladder cancer (MIBC) is a heterogeneous disease, and gene expression profiling has identified several molecular subtypes with distinct biological and clinicopathological characteristics. While MIBC subtyping has primarily been based on messenger RNA (mRNA), long non-coding RNAs (lncRNAs) may provide additional resolution.

METHODS

LncRNA expression was quantified from microarray data of a MIBC cohort treated with neoadjuvant chemotherapy (NAC) and radical cystectomy (RC) (n = 223). Unsupervised consensus clustering of highly variant lncRNAs identified a four-cluster solution, which was characterized using a panel of MIBC biomarkers, regulon activity profiles, gene signatures, and survival analysis. The four-cluster solution was confirmed in The Cancer Genome Atlas (TCGA) cohort (n = 405). A single-sample genomic classifier (GC) was trained using ridge-penalized logistic regression and validated in two independent cohorts (n = 255 and n = 94).

RESULTS

NAC and TCGA cohorts both contained an lncRNA cluster (LC3) with favorable prognosis that was enriched with tumors of the luminal-papillary (LP) subtype. In both cohorts, patients with LP tumors in LC3 (LPL-C3) were younger and had organ-confined, node-negative disease. The LPL-C3 tumors had enhanced FGFR3, SHH, and wild-type p53 pathway activity. In the TCGA cohort, LPL-C3 tumors were enriched for FGFR3 mutations and depleted for TP53 and RB1 mutations. A GC trained to identify these LPL-C3 patients showed robust performance in two validation cohorts.

CONCLUSIONS

Using lncRNA expression profiles, we identified a biologically distinct subgroup of luminal-papillary MIBC with a favorable prognosis. These data suggest that lncRNAs provide additional information for higher-resolution subtyping, potentially improving precision patient management.

FGFs/FGFRs-dependent signalling in regulation of steroid hormone receptors - implications for therapy of luminal breast cancer

Stromal stimuli mediated by growth factor receptors, leading to ligand-independent activation of steroid hormone receptors, have long been implicated in development of breast cancer resistance to endocrine therapy. Mutations in fibroblast growth factor receptor (FGFR) genes have been associated with a higher incidence and progression of breast cancer. Increasing evidence suggests that FGFR-mediated interaction between luminal invasive ductal breast carcinoma (IDC) and its microenvironment contributes to the progression to hormone-independence. Therapeutic strategies based on FGFR inhibitors hold promise for overcoming resistance to the ER-targeting treatment. A series of excellent reviews discuss a potential role of FGFR in development of IDC. Here, we provide a concise updated summary of existing literature on FGFR-mediated signalling with an emphasis on an interaction between FGFR and estrogen/progesterone receptors (ER/PR) in IDC. Focusing on the regulatory role of tumour microenvironment in the activity of steroid hormone receptors, we compile the available functional data on FGFRs-mediated signalling, as a fundamental mechanism of luminal IDC progression and failure of anti-ER treatment. We also highlight the translational value of the presented findings and summarize ongoing oncologic clinical trials investigating FGFRs inhibition in interventional studies in breast cancer.

Emerging Roles of Fibroblast Growth Factor 10 in Cancer

Whilst cross-talk between stroma and epithelium is critical for tissue development and homeostasis, aberrant paracrine stimulation can result in neoplastic transformation. Chronic stimulation of epithelial cells with paracrine Fibroblast Growth Factor 10 (FGF10) has been implicated in multiple cancers, including breast, prostate and pancreatic ductal adenocarcinoma. Here, we examine the mechanisms underlying FGF10-induced tumourigenesis and explore novel approaches to target FGF10 signaling in cancer.

Breast cancer: The translation of big genomic data to cancer precision medicine

Cancer is a complex genetic disease that develops from the accumulation of genomic alterations in which germline variations predispose individuals to cancer and somatic alterations initiate and trigger the progression of cancer. For the past 2 decades, genomic research has advanced remarkably, evolving from single-gene to whole-genome screening by using genome-wide association study and next-generation sequencing that contributes to big genomic data. International collaborative efforts have contributed to curating these data to identify clinically significant alterations that could be used in clinical settings. Focusing on breast cancer, the present review summarizes the identification of genomic alterations with high-throughput screening as well as the use of genomic information in clinical trials that match cancer patients to therapies, which further leads to cancer precision medicine. Furthermore, cancer screening and monitoring were enhanced greatly by the use of liquid biopsies. With the growing data complexity and size, there is much anticipation in exploiting deep machine learning and artificial intelligence to curate integrative "-omics" data to refine the current medical practice to be applied in the near future.

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.

ERα Binding by Transcription Factors NFIB and YBX1 Enables FGFR2 Signaling to Modulate Estrogen Responsiveness in Breast Cancer

Two opposing clusters of transcription factors (TF) have been associated with the differential risks of estrogen receptor positive or negative breast cancers, but the mechanisms underlying the opposing functions of the two clusters are undefined. In this study, we identified NFIB and YBX1 as novel interactors of the estrogen receptor (ESR1). NFIB and YBX1 are both risk TF associated with progression of ESR1-negative disease. Notably, they both interacted with the ESR1-FOXA1 complex and inhibited the transactivational potential of ESR1. Moreover, signaling through FGFR2, a known risk factor in breast cancer development, augmented these interactions and further repressed ESR1 target gene expression. We therefore show that members of two opposing clusters of risk TFs associated with ESR1-positive and -negative breast cancer can physically interact. We postulate that this interaction forms a toggle between two developmental pathways affected by FGFR2 signaling, possibly offering a junction to exploit therapeutically.Significance: Binding of the transcription factors NFIB and YBX1 to the estrogen receptor can promote an estrogen-independent phenotype that can be reverted by inhibiting FGFR2 signaling. Cancer Res; 78(2); 410-21. ©2017 AACR.

Single nucleotide polymorphisms and cancer susceptibility

A large number of genes associated with various cancer types contain single nucleotide polymorphisms (SNPs). SNPs are located in gene promoters, exons, introns as well as 5'- and 3'- untranslated regions (UTRs) and affect gene expression by different mechanisms. These mechanisms depend on the role of the genetic elements in which the individual SNPs are located. Moreover, alterations in epigenetic regulation due to gene polymorphisms add to the complexity underlying cancer susceptibility related to SNPs. In this systematic review, we discuss the various genetic and epigenetic mechanisms involved in determining cancer susceptibility related to various SNPs located in different genetic elements. We also discuss the diagnostic potential of these SNPs and the focus for future studies.

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments.

Fibroblast Growth Factor Receptor 2 Signaling in Breast Cancer

Fibroblast growth factor receptor 2 (FGFR2) is a membrane-spanning tyrosine kinase that mediates signaling for FGFs. Recent studies detected various point mutations of FGFR2 in multiple types of cancers, including breast cancer, lung cancer, gastric cancer, uterine cancer and ovarian cancer, yet the casual relationship between these mutations and tumorigenesis is unclear. Here we will discuss possible interactions between FGFR2 signaling and several major pathways through which the aberrantly activated FGFR2 signaling may result in breast cancer development. We will also discuss some recent developments in the discovery and application of therapies and strategies for breast cancers by inhibiting FGFR2 activities.

Discovery of cancer common and specific driver gene sets

Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found.

Identification of Post-Transcriptional Modulators of Breast Cancer Transcription Factor Activity Using MINDy

We have recently identified transcription factors (TFs) that are key drivers of breast cancer risk. To better understand the pathways or sub-networks in which these TFs mediate their function we sought to identify upstream modulators of their activity. We applied the MINDy (Modulator Inference by Network Dynamics) algorithm to four TFs (ESR1, FOXA1, GATA3 and SPDEF) that are key drivers of estrogen receptor-positive (ER+) breast cancer risk, as well as cancer progression. Our computational analysis identified over 500 potential modulators. We assayed 189 of these and identified 55 genes with functional characteristics that were consistent with a role as TF modulators. In the future, the identified modulators may be tested as potential therapeutic targets, able to alter the activity of TFs that are critical in the development of breast cancer.