Metabolic regulation of EGFR effector and feedback signaling in pancreatic cancer cells requires K-Ras

Nectin-4 as Blood-Based Biomarker Enables Detection of Early Ovarian Cancer Stages

Ovarian cancer is the third most common gynecological malignancy and has the highest mortality rate. Owing to unspecific symptoms, ovarian cancer is not detected until an advanced stage in about two-thirds of cases. Therefore, it is crucial to establish reliable biomarkers for the early stages to improve the patients’ prognosis. The aim of this study is to investigate whether the ADAM17 substrates Nectin-4, Heparin-binding EGF-like growth factor (HB-EGF) and Amphiregulin (AREG) could function as potential tumor markers for ovarian cancer. In this study a set of 231 sera consisting of 131 ovarian cancer patients and 100 healthy age-matched controls were assembled. Nectin-4, HB-EGF and AREG levels of preoperatively collected sera were determined by enzyme-linked immunosorbent assay (ELISA). Our analysis revealed that Nectin-4 and HB-EGF were significantly increased compared to the age-matched control group (p < 0.0001, p = 0.016). Strikingly, significantly higher Nectin-4 and HB-EGF levels were detected in early-stage FIGO I/II (p <0.001; p = 0.025) compared to healthy controls. Eighty-four percent (16/19) of patients with low Ca-125 levels showed increased Nectin-4 levels. Our study proposes Nectin-4 and HB-EGF as promising blood-based biomarkers for the detection of early stages of ovarian cancer patients that would not have been detected by Ca-125.

Tensor decomposition based on the potential low-rank and [Formula: see text]-shrinkage generalized threshold algorithm for analyzing cancer multiomics data

Tensor Robust Principal Component Analysis (TRPCA) has achieved promising results in the analysis of genomics data. However, the TRPCA model under the existing tensor singular value decomposition ([Formula: see text]-SVD) framework insufficiently extracts the potential low-rank structure of the data, resulting in suboptimal restored components. Simultaneously, the tensor nuclear norm (TNN) defined based on [Formula: see text]-SVD uses the same standard to handle various singular values. TNN ignores the difference of singular values, leading to the failure of the main information that needs to be well preserved. To preserve the heterogeneous structure in the low-rank information, we propose a novel TNN and extend it to the TRPCA model. Potential low-rank space may contain important information. We learn the low-rank structural information from the core tensor. The singular value space contains the association information between genes and cancers. The [Formula: see text]-shrinkage generalized threshold function is utilized to preserve the low-rank properties of larger singular values. The optimization problem is solved by the alternating direction method of the multiplier (ADMM) algorithm. Clustering and feature selection experiments are performed on the TCGA data set. The experimental results show that the proposed model is more promising than other state-of-the-art tensor decomposition methods.

KRASG12R-Independent Macropinocytosis in Pancreatic Cancer

Macropinocytosis is a critical route of nutrient acquisition in pancreatic cancer cells. Constitutive macropinocytosis is promoted by mutant KRAS, which activates the PI3Kα lipid kinase and RAC1, to drive membrane ruffling, macropinosome uptake and processing. However, our recent study on the KRAS^G12R mutant indicated the presence of a KRAS-independent mode of macropinocytosis in pancreatic cancer cell lines, thereby increasing the complexity of this process. We found that KRAS^G12R-mutant cell lines promote macropinocytosis independent of KRAS activity using PI3Kγ and RAC1, highlighting the convergence of regulation on RAC signaling. While macropinocytosis has been proposed to be a therapeutic target for the treatment of pancreatic cancer, our studies have underscored how little we understand about the activation and regulation of this metabolic process. Therefore, this review seeks to highlight the differences in macropinocytosis regulation in the two cellular subtypes while also highlighting the features that make the KRAS^G12R mutant atypical.

Immunosuppression Induced by Glutamine Deprivation Occurs via Activating PD-L1 Transcription in Bladder Cancer

Few studies have reported whether nutrients in the tumor microenvironment can regulate the expression of PD-L1. Since tumor cells are often situated in a low-glutamine environment, we investigated PD-L1 expression under glutamine deprivation in bladder cancer cells. PD-L1 expression and the activation of the EGFR/MEK/ERK/c-Jun signaling pathway under glutamine deprivation were investigated by qPCR, Western blot, and immunofluorescence analyses. C-Jun-mediated transcriptional regulation of the PD-L1 gene was assessed by ChIP. PD-L1 expression and activation of the EGFR/MEK/ERK/c-Jun signaling pathway were assessed in T24 cells, TCCSUP cells and BALB/c mice with or without glutamine supplementation. Additionally, the impact of PD-L1 expression under glutamine deprivation on the function of T cells was investigated by ELISA. The expression of PD-L1 and EGFR/MEK/ERK/c-Jun pathway activation were elevated by glutamine deprivation, and c-Jun was enriched in the enhancer region of PD-L1. The expression of PD-L1 was considerably impaired by inhibiting the EGFR/MEK/ERK/c-Jun pathway and was elevated by activating this signaling pathway. In addition, the elevated PD-L1 expression and MEK/ERK/c-Jun signaling pathway activation were reduced by glutamine supplementation in vitro and in vivo. PD-L1 upregulation by glutamine deprivation in bladder cancer cells could reduce IFN-γ production by T cells. The expression of PD-L1 was upregulated under glutamine deprivation through the EGFR/MEK/ERK/c-Jun pathway to impair T cell function.

MicroRNA-Regulated Signaling Pathways: Potential Biomarkers for Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most aggressive and invasive type of pancreatic cancer (PCa) and is expected to be the second most common cause of cancer-associated deaths. The high mortality rate is due to the asymptomatic progression of the clinical features until the advanced stages of the disease and the limited effectiveness of the current therapeutics. Aberrant expression of several microRNAs (miRs/miRNAs) has been related to PDAC progression and thus they could be potential early diagnostic, prognostic, and/or therapeutic predictors for PDAC. miRs are small (18 to 24 nucleotides long) non-coding RNAs, which regulate the expression of key genes by targeting their 3′-untranslated mRNA region. Increased evidence has also suggested that the chemoresistance of PDAC cells is associated with metabolic alterations. Metabolic stress and the dysfunctionality of systems to compensate for the altered metabolic status of PDAC cells is the foundation for cellular damage. Current data have implicated multiple systems as hallmarks of PDAC development, such as glutamine redox imbalance, oxidative stress, and mitochondrial dysfunction. Hence, both the aberrant expression of miRs and dysregulation in metabolism can have unfavorable effects in several biological processes, such as apoptosis, cell proliferation, growth, survival, stress response, angiogenesis, chemoresistance, invasion, and migration. Therefore, due to these dismal statistics, it is crucial to develop beneficial therapeutic strategies based on an improved understanding of the biology of both miRs and metabolic mediators. This review focuses on miR-mediated pathways and therapeutic resistance mechanisms in PDAC and evaluates the impact of metabolic alterations in the progression of PDAC.