FGFR2 overexpression predicts survival outcome in patients with metastatic papillary renal cell carcinoma

Developing New Peptides and Peptide-Drug Conjugates for Targeting the FGFR2 Receptor-Expressing Tumor Cells and 3D Spheroids

In this work, we utilized a biomimetic approach for targeting KATO (III) tumor cells and 3D tumoroids. Specifically, the binding interactions of the bioactive short peptide sequences ACSAG (A-pep) and LPHVLTPEAGAT (L-pep) with the fibroblast growth factor receptor (FGFR2) kinase domain was investigated for the first time. Both peptides have been shown to be derived from natural resources previously. We then created a new fusion trimer peptide ACSAG-LPHVLTPEAGAT-GASCA (Trimer-pep) and investigated its binding interactions with the FGFR2 kinase domain in order to target the fibroblast growth factor receptor 2 (FGFR2), which is many overexpressed in tumor cells. Molecular docking and molecular dynamics simulation studies revealed critical interactions with the activation loop, hinge and glycine-rich loop regions of the FGFR2 kinase domain. To develop these peptides for drug delivery, DOX (Doxorubicin) conjugates of the peptides were created. Furthermore, the binding of the peptides with the kinase domain was further confirmed through surface plasmon resonance studies. Cell studies with gastric cancer cells (KATO III) revealed that the conjugates and the peptides induced higher cytotoxicity in the tumor cells compared to normal cells. Following confirmation of cytotoxicity against tumor cells, the ability of the conjugates and the peptides to penetrate 3D spheroids was investigated by evaluating their permeation in co-cultured spheroids grown with KATO (III) and colon tumor-associated fibroblasts (CAFs). Results demonstrated that Trimer-pep conjugated with DOX showed the highest permeation, while the ACSAG conjugate also demonstrated reasonable permeation of the drug. These results indicate that these peptides may be further explored and potentially utilized to create drug conjugates for targeting tumor cells expressing FGFR2 for developing therapeutics.

The Integrated Analyses of Driver Genes Identify Key Biomarkers in Thyroid Cancer

AIM

Thyroid cancer is the most common endocrine cancer, the incidence rate has continuously increased worldwide. However, there are still lack of effective molecular biomarkers for the diagnosis and treatment of the disease. The study was conducted to identify driver genes that may serve as potential biomarkers for the disease.

METHODS

The computational tools oncodriveCLUST, oncodriveFM, icages and drgap were used to detect driver genes in thyroid cancer using somatic mutations from The Cancer Genome Atlas database. Integrated analyses were performed on the driver genes using multiomics data from the TCGA database.

RESULTS

A set of 291 driver genes were identified in thyroid cancer. BRAF, NRAS, HRAS, OTUD4, EIF1AX were the top 5 frequently mutated genes in thyroid cancer. The weighted gene co-expression network analysis identified 4 coexpression modules. The modules 1-3 were significantly associated with patients' tumor size, residual tumor, cancer stage, distant metastasis and multifocality. SEC24B, MET and ITGAL were the hub genes in the modules 1-3 respectively. Hierarchical clustering analysis of the 20 driver genes with the most frequent copy number changes revealed 3 clusters of PRAD patients. Cluster 1 tumors exhibited significantly older age, tumor size, cancer stages, and poorer prognosis than cluster 2 and 3 tumors. 16 genes were significantly associated with number of lymph nodes, tumor size and pathologic stage, such as IL7 R, IRS1, PTK2B, MAP3K3 and FGFR2.

CONCLUSIONS

The set of cancer genes and subgroups of patients shed insight on the tumorigenesis of thyroid cancer and open up avenues for developing prognostic biomarkers and driver gene-targeted therapies in thyroid cancer.

Investigational fibroblast growth factor receptor 2 antagonists in early phase clinical trials to treat solid tumors

Introduction: Fibroblast growth factor receptor 2 (FGFR2) is a highly conserved transmembrane tyrosine kinase receptor. FGFR2 dysregulation occurs in numerous human solid tumors and overexpression is closely associated with tumor progression. FGFR2 has recently been reported as a therapeutic target for cancer. Several targeted therapies are being investigated to disrupt FGFR2 activity; these include multi-target tyrosine kinase inhibitors (TKIs), pan-FGFR targeted TKIs and FGFR2 monoclonal antibodies. Areas: This review examines FGFR2 regulation and function in cancer and its potential as a target for cancer treatment. Expert opinion: Highly specific FGFR2 blockers have not yet been developed and moreover, resistance to FGFR2-targeted therapies is a challenge. More sophisticated patient selection strategies would help improve FGFR2-targeted therapies and combination therapy is considered the most promising approach for cancer patients with FGFR2 alterations.

Comprehensive analysis of differentially expressed profiles and reconstruction of a competing endogenous RNA network in papillary renal cell carcinoma

Long noncoding RNAs (lncRNAs) function as competing endogenous RNAs (ceRNAs). ceRNA networks may serve important roles in various tumors, as demonstrated by an increasing number of studies; however, papillary renal cell carcinoma (PRCC)-associated ceRNA networks mediated by lncRNAs remain unknown. Increased knowledge of ceRNA networks in PRCC may aid the identification of novel targets and biomarkers in the treatment of PRCC. In the present study, a comprehensive investigation of mRNA, lncRNA, and microRNA (miRNA) expression in PRCC was conducted using sequencing data from The Cancer Genome Atlas. Differential expression (DE) profiles of mRNAs, lncRNAs and miRNAs were evaluated, with 1,970 mRNAs, 1,201 lncRNAs and 96 miRNAs identified as genes with significantly different expression between PRCC and control paracancerous tissues. Based on the identified DEmRNAs, a protein-protein interaction network was generated using the STRING database. Furthermore, a ceRNA network for PRCC was determined using a targeted assay combined with the DE of miRNAs, mRNAs and lncRNAs, enabling the identification of important lncRNA-miRNA and miRNA-mRNA pairs. Analysis of the ceRNA network led to the extraction of a subnetwork and the identification of lncRNA maternally expressed 3 (MEG3), lncRNA PWRN1, miRNA (miR)-508, miR-21 and miR519 as important genes. Reverse transcription-quantitative polymerase chain reaction analysis was conducted to validate the results of the bioinformatics analyses; it was revealed that lncRNA MEG3 expression levels were downregulated in PRCC tumor tissues compared with adjacent non-tumor tissues. In addition, survival analysis was conducted to investigate the association between identified genes and the prognosis of patients with PRCC, indicating the potential involvement of 13 mRNAs, 15 lncRNAs and six miRNAs. In conclusion, the present study may improve understanding of the regulatory mechanisms of ceRNA networks in PRCC and provide novel insight for future studies of prognostic biomarkers and potential therapeutic targets.

Gene expression profiling in aggressive digital papillary adenocarcinoma sheds light on the architecture of a rare sweat gland carcinoma

BACKGROUND

Sweat gland carcinomas are rare cutaneous adnexal malignancies. Aggressive digital papillary adenocarcinoma (ADPA) represents a very rare subentity, thought to arise almost exclusively from the sweat glands of the fingers and toes. The aetiology of sweat gland carcinomas and ADPA is largely unknown. ADPAs are most likely driven by somatic mutations. However, somatic mutation patterns are largely unexplored, creating barriers to the development of effective therapeutic approaches to the treatment of ADPA.

OBJECTIVES

To investigate the transcriptome profile of ADPA using a sample of eight formalin-fixed, paraffin-embedded tissue samples of ADPA and healthy control tissue.

METHODS

Transcriptome profiling was performed using the Affymetrix PrimeView Human Gene Expression Microarray and findings were validated via reverse transcription of RNA and real-time quantitative polymerase chain reaction.

RESULTS

Transcriptome analyses showed increased tumour expression of 2266 genes, with significant involvement of cell cycle, ribosomal and crucial cancer pathways. Our results point to tumour overexpression of FGFR2 (P = 0·001).

CONCLUSIONS

The results indicate the involvement of crucial oncogenic driver pathways, highlighting cell cycle and ribosomal pathways in the aetiology of ADPA. Suggested tumour overexpression of FGFR2 raises the hope that targeting the fibroblast growth factor (FGF)/FGF receptor axis might be a promising treatment for ADPA and probably for the overall group of sweat gland carcinomas.

A transcriptome-based protein network that identifies new therapeutic targets in colorectal cancer

Background

Colon cancer occurrence is increasing worldwide, making it the third most frequent cancer. Although many therapeutic options are available and quite efficient at the early stages, survival is strongly decreased when the disease has spread to other organs. The identification of molecular markers of colon cancer is likely to help understanding its course and, eventually, to uncover novel genes to be targeted by drugs. In this study, we compared gene expression in a set of 95 human colon cancer samples to that in 19 normal colon mucosae, focusing on 401 genes from 5 selected pathways (Apoptosis, Cancer, Cholesterol metabolism and lipoprotein signaling, Drug metabolism, Wnt/beta-catenin). Deregulation of mRNA levels largely matched that of proteins, leading us to build in silico protein networks, starting from mRNA levels, to identify key proteins central to network activity.

Results

Among the analyzed genes, 10.5% (42) had no reported link with colon cancer, including the SFRP1, IGF1 and ADH1B (down), and MYC and IL8 (up), whose encoded proteins were most interacting with other proteins from the same or even distinct networks. Analyzing all pathways globally led us to uncover novel functional links between a priori unrelated or rather remotely connected pathways, such as the Drug metabolism and the Cancer pathways or, even more strikingly, between the Cholesterol metabolism and lipoprotein signaling and the Cancer pathways. In addition, we analyzed the responsiveness of some of the deregulated genes essential to network activities, to chemotherapeutic agents used alone or in presence of Lovastatin, a lipid-lowering drug. Some of these treatments could oppose the deregulations occurring in cancer samples, including those of the CHECK2, CYP51A1, HMGCS1, ITGA2, NME1 or VEGFA genes.

Conclusions

Our network-based approach allowed discovering genes not previously known to play regulatory roles in colon cancer. Our results also showed that selected drug treatments might revert the cancer-specific deregulation of genes playing prominent roles within the networks operating to maintain colon homeostasis. Among those genes, some could constitute novel testable targets to eliminate colon cancer cells, either directly or, potentially, through the use of lipid-lowering drugs such as statins, in association with selected anticancer drugs.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4139-y) contains supplementary material, which is available to authorized users.

Alofanib, an allosteric FGFR2 inhibitor, has potent effects on ovarian cancer growth in preclinical studies

SUMMAY

Purpose Early data suggest that combining FGFR2 inhibitors with platinum-containing cytotoxic agents for the treatment of epithelial ovarian cancer may yield increased antitumor activity. We investigated antitumor activity of alofanib (RPT835), a novel allosteric FGFR2 inhibitor, in ovarian cancer in vitro and in vivo. Methods Equal amounts of ovarian cancer cell (SKOV3) lysates were analyzed for FGFR1-3 protein expression using Wes. To assess the efficacy of alofanib on FGF-mediated cell proliferation, SKOV3 cells were incubated and were treated with serially diluted alofanib. Basic FGF was added at a concentration of 25 ng/ml. Control wells were left untreated. Cell growth inhibition was determined using Promega's Cell Titer-Glo® assay. Immunocompromised mice were used for xenotransplantation of SKOV3 cancer cells. Seventy animals with measurable tumors were selected on day 10 and randomized into control groups (no treatment or chemotherapy alone (paclitaxel + carboplatin) and treatment groups (alofanib orally or intravenously (different dose levels) in combination with chemotherapy). Measurements of tumor volume (mm3) were performed by digital calipers every 3 days during 31 days after tumor inoculation. Number of tumor vessels and Ki-67 index were calculated. Results SKOV3 cells express FGFR1 and FGFR2 but not FGFR3. Basic FGF increased proliferation of the ovarian cancer cells in untreated control group (P = 0.001). Alofanib inhibited growth of FGFR2-expressing SKOV3 cells with GI50 value of 0.37 μmol/L. Treatment with alofanib in combination with paclitaxel/carboplatin resulted in tumor growth delay phenotype in all treatment groups compared to control non-treatment groups. Compound exhibited a dose-dependent effect on tumor growth. Daily intravenous regimen of alofanib (total maximum dose per week was 350 mg/kg) demonstrated significant effect (inhibiting growth by 80 % and by 53 % in comparison with vehicle and chemotherapy group alone, respectively (P < 0.001). Alofanib decreased number of vessels in tumor (-49 %; P < 0.0001) and number of Ki-67-positive SKOV3 cells (-42 %, P < 0.05). There were tumor necrosis and cell degeneration in alofanib group. Conclusions We suggest that FGFR2 inhibition has potent effects on ovarian cancer growth in preclinical studies.