Vitamin C functions as double-edge sword on cancer progression depending on ERK activation or inhibition mediated by its receptor SVCT2

The effect of Vitamin C (Vc) in oncotherapy was controversial for decades. And hyperactivation of extracellular signal-regulated kinase (ERK) drove tumorigenesis. Herein, we demonstrated that Vc activated ERK through sodium-dependent Vc transporter 2 (SVCT2), while high-dose Vc resulted in persistent ERK feedback inhibition following activation. Extracellular Vc binding to SVCT2 initiated ERK activation, then transmembrane transport of Vc induced dimerization of SVCT2. Activated ERK phosphorylated protein tyrosine phosphatase non-receptor type 12 (PTPN12) at Ser434 and inhibited PTPN12 activity, thus enhancing phosphorylation of Janus kinase 2 (JAK2), which phosphorylated growth factor receptor bound protein 2 (GRB2) at Tyr160 to promote GRB2 dimers dissociation and recruitment of GRB2 to SVCT2, leading to further ERK activation. Different cancers have different sensitivities to Vc, the dose effects of Vc on cancer phenotypes depended on that ERK was activated or inhibited. These findings suggest SVCT2 is a Vc receptor mediating the ERK-PTPN12-JAK2-GRB2-ERK positive feedback loop and a potential target for oncotherapy.

CRISPR screens identify gene targets and drug repositioning opportunities at breast cancer risk loci

Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association and identifying the phenotype it mediates is a major challenge in the interpretation and translation of GWAS. Here, we used pooled CRISPR activation and suppression screens to evaluate predicted GWAS target genes, and to define the cancer phenotypes they mediate. We measured proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on DNA repair. We performed 60 CRISPR screens and identified 21 genes predicted with high confidence to be GWAS targets that drive a cancer phenotype by driving a proliferation or DNA damage response in breast cells. We validated the regulation of a subset of these genes by BC-risk variants, and show the utility of expression profiling for drug repurposing. We provide a platform for identifying gene targets of risk variants, and present a blueprint of interventions for BC risk reduction and treatment.

Managing of Unassigned Mass Spectrometric Data by Neural Network for Cancer Phenotypes Classification

Mass spectrometric profiling provides information on the protein and metabolic composition of biological samples. However, the weak efficiency of computational algorithms in correlating tandem spectra to molecular components (proteins and metabolites) dramatically limits the use of “omics” profiling for the classification of nosologies. The development of machine learning methods for the intelligent analysis of raw mass spectrometric (HPLC-MS/MS) measurements without involving the stages of preprocessing and data identification seems promising. In our study, we tested the application of neural networks of two types, a 1D residual convolutional neural network (CNN) and a 3D CNN, for the classification of three cancers by analyzing metabolomic-proteomic HPLC-MS/MS data. In this work, we showed that both neural networks could classify the phenotypes of gender-mixed oncology, kidney cancer, gender-specific oncology, ovarian cancer, and the phenotype of a healthy person by analyzing ‘omics’ data in ‘mgf’ data format. The created models effectively recognized oncopathologies with a model accuracy of 0.95. Information was obtained on the remoteness of the studied phenotypes. The closest in the experiment were ovarian cancer, kidney cancer, and prostate cancer/kidney cancer. In contrast, the healthy phenotype was the most distant from cancer phenotypes and ovarian and prostate cancers. The neural network makes it possible to not only classify the studied phenotypes, but also to determine their similarity (distance matrix), thus overcoming algorithmic barriers in identifying HPLC-MS/MS spectra. Neural networks are versatile and can be applied to standard experimental data formats obtained using different analytical platforms.

Targeting PI3K/Akt signal transduction for cancer therapy

The phosphatidylinositol 3-kinase (PI3K)/Akt pathway plays a crucial role in various cellular processes and is aberrantly activated in cancers, contributing to the occurrence and progression of tumors. Examining the upstream and downstream nodes of this pathway could allow full elucidation of its function. Based on accumulating evidence, strategies targeting major components of the pathway might provide new insights for cancer drug discovery. Researchers have explored the use of some inhibitors targeting this pathway to block survival pathways. However, because oncogenic PI3K pathway activation occurs through various mechanisms, the clinical efficacies of these inhibitors are limited. Moreover, pathway activation is accompanied by the development of therapeutic resistance. Therefore, strategies involving pathway inhibitors and other cancer treatments in combination might solve the therapeutic dilemma. In this review, we discuss the roles of the PI3K/Akt pathway in various cancer phenotypes, review the current statuses of different PI3K/Akt inhibitors, and introduce combination therapies consisting of signaling inhibitors and conventional cancer therapies. The information presented herein suggests that cascading inhibitors of the PI3K/Akt signaling pathway, either alone or in combination with other therapies, are the most effective treatment strategy for cancer.

First person – Jun-yi Zhu and Xiaohu Huang

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Disease Models & Mechanisms, helping early-career researchers promote themselves alongside their papers. Jun-yi Zhu and Xiaohu Huang are first authors on ‘ Pharmacological or genetic inhibition of hypoxia signaling attenuates oncogenic RAS-induced cancer phenotypes’, published in DMM. Jun-yi is an assistant professor in the lab of Zhe Han at the University of Maryland School of Medicine, Baltimore, MD, USA, investigating the use of Drosophila as a model to study human disease mechanisms and treatment approaches. Xiaohu is a postdoc in the same lab, investigating gene functions in cardiovascular development and genetic diseases.

NKX2-1 re-expression induces cell death through apoptosis and necrosis in dedifferentiated thyroid carcinoma cells

NK2 homeobox 1 (NKX2-1) is a thyroid transcription factor essential for proper thyroid formation and maintaining its physiological function. In thyroid cancer, NKX2-1 expression decreases in parallel with declined differentiation. However, the molecular pathways and mechanisms connecting NKX2-1 to thyroid cancer phenotypes are largely unknown. This study aimed to examine the effects of NKX2-1 re-expression on dedifferentiated thyroid cancer cell death and explore the underlying mechanisms. A human papillary thyroid carcinoma cell line lacking NKX2-1 expression was infected with an adenoviral vector containing Nkx2-1. Cell viability decreased after Nkx2-1 transduction and apoptosis and necrosis were detected. Arginase 2 (ARG2), regulator of G protein signaling 4 (RGS4), and RGS5 mRNA expression was greatly increased in Nkx2-1-transducted cells. After suppressing these genes by siRNA, cell death, apoptosis, and necrosis decreased in RGS4 knockdown cells. These findings demonstrated that cell death was induced via apoptosis and necrosis by NKX2-1 re-expression and involves RGS4.

Decoding the Genetic Alterations in Genes of Fibroblast Growth Factor Family and Their Possible Association with HNSCC

Introduction: HNSCC is a type of cancer in the oral and pharynx region. Several mutations/variations are observed in these cancer phenotypes. Fibroblast growth factor belongs to the family of heparin binding growth factors. FGFs are multifunctional proteins with a wide variety of effects; they are most commonly mitogens. Their expression pattern correlates with invasion of HNSCC. Aim: To assess the genetic alterations in genes of the fibroblast growth factor family and their association with HNSCC. Materials and Methods: The demographic data and samples of 528 HNSCC patients was collected from the cBioportal database. Oncoprint analysis was done to assess the amplification and genetic alterations of the members of the FGF gene family. String analysis was performed to evaluate the protein-protein interaction. The information about previous reported mutation and correlation with novel and reported mutation was obtained using GnomAD analysis. Results and Discussion: FGF3,4 and 19 genes showed maximum variation (25%). FGF4 and FGF19 genes showed maximum amplification in addition to deletion mutation. Excitingly FGF3, FGF4 and FGF19 genes showed similar amplification patterns in most of the HNSCC patients. Statistical significant difference in the gene expression of FGF3 9.578 x 10-3 observed between normal and primary tumour. S. Findings showed many novel mutations and also 4 reported mutations ie:FGF1, FGF12, FGF20, FGF21 Conclusion: Our present study concludes that more evidence is required to confirm their association with HNSCC.

HMGA2 Supports Cancer Hallmarks in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that exhibits a high proliferation rate and early metastasis leading to a poor prognosis. HMGA2 is a DNA binding transcriptional regulator implicated in tumorigenesis. Here, we demonstrate that the HMGA2 promoter is demethylated in TNBC tumors, leading to increased expression of HMGA2 at both mRNA and protein levels. Importantly, high HMGA2 levels in TNBC tumors are correlated with poor prognosis. To detail the role of HMGA2 in TNBC development and progression, we studied its effect on core cancer phenotypes. Stable knockdown of HMGA2 in TNBC cells revealed that HMGA2 may support cell proliferation, cell migration and invasion. In addition, HMGA2 knockdown decreased cancer stem cell (CSC) features. Importantly, we found that silencing HMGA2 inhibited NF-kB signaling and lead to decreased expression of the downstream molecules IL-6 and IL-8 and reduced STAT3 pathway activation. Our results demonstrate that HMGA2 supports cancer hallmarks in TNBC and may represent a promising target for TNBC treatment.

Increased glucosylceramide production leads to decreased cell energy metabolism and lowered tumor marker expression in non-cancerous liver cells

Hepatocellular carcinoma (HCC) is one of the most difficult cancer types to treat. Liver cancer is often diagnosed at late stages and therapeutic treatment is frequently accompanied by development of multidrug resistance. This leads to poor outcomes for cancer patients. Understanding the fundamental molecular mechanisms leading to liver cancer development is crucial for developing new therapeutic approaches, which are more efficient in treating cancer. Mice with a liver specific UDP-glucose ceramide glucosyltransferase (UGCG) knockout (KO) show delayed diethylnitrosamine (DEN)-induced liver tumor growth. Accordingly, the rationale for our study was to determine whether UGCG overexpression is sufficient to drive cancer phenotypes in liver cells. We investigated the effect of UGCG overexpression (OE) on normal murine liver (NMuLi) cells. Increased UGCG expression results in decreased mitochondrial respiration and glycolysis, which is reversible by treatment with EtDO-P4, an UGCG inhibitor. Furthermore, tumor markers such as FGF21 and EPCAM are lowered following UGCG OE, which could be related to glucosylceramide (GlcCer) and lactosylceramide (LacCer) accumulation in glycosphingolipid-enriched microdomains (GEMs) and subsequently altered signaling protein phosphorylation. These cellular processes lead to decreased proliferation in NMuLi/UGCG OE cells. Our data show that increased UGCG expression itself does not induce pro-cancerous processes in normal liver cells, which indicates that increased GlcCer expression leads to different outcomes in different cancer types. Graphic abstract