Cytokeratin 19 <i>(KRT19)</i> has a Role in the Reprogramming of Cancer Stem Cell-Like Cells to Less Aggressive and More Drug-Sensitive Cells. Int J Mol Sci. 2018;19. [PMID: 29747452 PMCID: PMC5983664 DOI: 10.3390/ijms19051423]

Intermediate Filaments in Breast Cancer Progression, and Potential Biomarker for Cancer Therapy: A Narrative Review

Intermediate filaments are one of the three components of the cytoskeletons, along with actin and microtubules. The intermediate filaments consist of extensive variations of structurally related proteins with specific expression patterns in cell types. The expression pattern alteration of intermediate filaments is frequently correlated with cancer progression, specifically with the epithelial-to-mesenchymal transition process closely related to increasing cellular migration and invasion. This review will discuss the involvement of cytoplasmic intermediate filaments, specifically vimentin, nestin, and cytokeratin (CK5/CK6, CK7, CK8/CK18, CK17, CK19, CK20, CSK1), in breast cancer progression and as prognostic or diagnostic biomarkers. The potential for drug development targeting intermediate filaments in cancer will be reviewed.

Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics

Embeddings derived from cell graphs hold significant potential for exploring spatial transcriptomics (ST) datasets. Nevertheless, existing methodologies rely on a graph structure defined by spatial proximity, which inadequately represents the diversity inherent in cell-cell interactions (CCIs). This study introduces STAGUE, an innovative framework that concurrently learns a cell graph structure and a low-dimensional embedding from ST data. STAGUE employs graph structure learning to parameterize and refine a cell graph adjacency matrix, enabling the generation of learnable graph views for effective contrastive learning. The derived embeddings and cell graph improve spatial clustering accuracy and facilitate the discovery of novel CCIs. Experimental benchmarks across 86 real and simulated ST datasets show that STAGUE outperforms 15 comparison methods in clustering performance. Additionally, STAGUE delineates the heterogeneity in human breast cancer tissues, revealing the activation of epithelial-to-mesenchymal transition and PI3K/AKT signaling in specific sub-regions. Furthermore, STAGUE identifies CCIs with greater alignment to established biological knowledge than those ascertained by existing graph autoencoder-based methods. STAGUE also reveals the regulatory genes that participate in these CCIs, including those enriched in neuropeptide signaling and receptor tyrosine kinase signaling pathways, thereby providing insights into the underlying biological processes.

Combined PET Radiotracer Approach Reveals Insights into Stromal Cell-Induced Metabolic Changes in Pancreatic Cancer In Vitro and In Vivo

Background/Objective Pancreatic stellate cells (PSCs) in pancreatic adenocarcinoma (PDAC) are producing extracellular matrix, which promotes the formation of a dense fibrotic microenvironment. This makes PDAC a highly heterogeneous tumor-stroma-driven entity, associated with reduced perfusion, limited oxygen supply, high interstitial fluid pressure, and limited bioavailability of therapeutic agents. Methods In this study, spheroid and tumor xenograft models of human PSCs and PanC-1 cells were characterized radiopharmacologically using a combined positron emission tomography (PET) radiotracer approach. [18F]FDG, [18F]FMISO, and [18F]FAPI-74 were employed to monitor metabolic activity, hypoxic metabolic state, and functional expression of fibroblast activation protein alpha (FAPα), a marker of activated PSCs. Results In vitro, PanC-1 and multi-cellular tumor spheroids demonstrated comparable glucose uptake and hypoxia, whereas FAPα expression was significantly higher in PSC spheroids. In vivo, glucose uptake as well as the transition to hypoxia were comparable in PanC-1 and multi-cellular xenograft models. In mice injected with PSCs, FAPα expression decreased over a period of four weeks post-injection, which was attributed to the successive death of PSCs. In contrast, FAPα expression increased in both PanC-1 and multi-cellular xenograft models over time due to invasion of mouse fibroblasts. Conclusion The presented models are suitable for subsequently characterizing stromal cell-induced metabolic changes in tumors using noninvasive molecular imaging techniques.

KRT19 is regulated by miR-642a-5p and promotes pancreatic cancer progression through the Wnt/β-catenin pathway

Pancreatic cancer (PC) has a really poor prognosis, and we urgently need to delve deeper into its molecular mechanisms. In this study, we found that KRT19 expression was significantly increased in PC tissues and cell lines and it was linked to unfavorable outcomes for patients. Overexpression of KRT19 boosted the proliferation, migration, and invasion of PC cells. Additionally, miR-374b-5p targets KRT19, inhibiting the activation of the Wnt/β-catenin pathway (WBC), which in turn suppresses epithelial-to-mesenchymal transition (EMT) and the progression of PC. Further experiments showed that under hypoxic conditions, HIF1α was positively correlated with KRT19, promoting its expression. The loss of miR-642a-5p and the upregulation of KRT19 induced by hypoxia can significantly favor PC progression. Plus, the increased expression of KRT19 might act as a predictive marker and potential target for PC treatment.

STAU1-mediated CNBP mRNA degradation by LINC00665 alters stem cell characteristics in ovarian cancer

BACKGROUND

To investigate the role of lncRNA LINC00665 in modulating ovarian cancer stemness and its influence on treatment resistance and cancer development.

METHODS

We isolated ovarian cancer stem cells (OCSCs) from the COC1 cell line using a combination of chemotherapeutic agents and growth factors, and verified their stemness through western blotting and immunofluorescence for stem cell markers. Employing bioinformatics, we identified lncRNAs associated with ovarian cancer, with a focus on LINC00665 and its interaction with the CNBP mRNA. In situ hybridization, immunohistochemistry, and qPCR were utilized to examine their expression and localization, alongside functional assays to determine the effects of LINC00665 on CNBP.

RESULTS

LINC00665 employs its Alu elements to interact with the 3'-UTR of CNBP mRNA, targeting it for degradation. This molecular crosstalk enhances stemness by promoting the STAU1-mediated decay of CNBP mRNA, thereby modulating the Wnt and Notch signaling cascades that are pivotal for maintaining CSC characteristics and driving tumor progression. These mechanistic insights were corroborated by a series of in vitro assays and validated in vivo using tumor xenograft models. Furthermore, we established a positive correlation between elevated CNBP levels and increased disease-free survival in patients with ovarian cancer, underscoring the prognostic value of CNBP in this context.

CONCLUSIONS

lncRNA LINC00665 enhances stemness in ovarian cancer by mediating the degradation of CNBP mRNA, thereby identifying LINC00665 as a potential therapeutic target to counteract drug resistance and tumor recurrence associated with CSCs.

RNA-Seq transcriptome profiling of Nile rat livers reveals novel insights on the anti-diabetic mechanisms of Water-Soluble Palm Fruit Extract

Water-Soluble Palm Fruit Extract (WSPFE) has been shown to confer anti-diabetic effects in the Nile rat (NR) (Arvicanthis niloticus). Liquid and powder WSPFE both deterred diabetes onset in NRs fed a high-carbohydrate (hiCHO) diet, but the liquid form provided better protection. In this study, NRs were fed either a hiCHO diet or the same diet added with liquid or powder WSPFE. Following feeding of the diets for 8 weeks, random blood glucose levels were measured to categorize NRs as either diabetes-resistant or diabetes-susceptible, based on a cut-off value of 75 mg/dL. Livers were then obtained for Illumina HiSeq 4000 paired end RNA-sequencing (RNA-Seq) and the data were mapped to the reference genome. Consistent with physiological and biochemical parameters, the gene expression data obtained indicated that WSPFE was associated with protection against diabetes. Among hepatic genes upregulated by WSPFE versus controls, were genes related to insulin-like growth factor binding protein, leptin receptor, and processes of hepatic metabolism maintenance, while those downregulated were related to antigen binding, immunoglobulin receptor, inflammation- and cancer-related processes. WSPFE supplementation thus helped inhibit diabetes progression in NRs by increasing insulin sensitivity and reducing both the inflammatory effects of a hiCHO diet and the related DNA-damage compensatory mechanisms contributing to liver disease progression. In addition, the genetic permissiveness of susceptible NRs to develop diabetes was potentially associated with dysregulated compensatory mechanisms involving insulin signaling and oxidative stress over time. Further studies on other NR organs associated with diabetes and its complications are warranted.

Unraveling metabolic characteristics and clinical implications in gastric cancer through single-cell resolution analysis

Background: Gastric cancer is a highly prevalent malignant neoplasm. Metabolic reprogramming is intricately linked to both tumorigenesis and cancer immune evasion. The advent of single-cell RNA sequencing technology provides a novel perspective for evaluating cellular metabolism. This study aims to comprehensively investigate the metabolic pathways of various cell types in tumor and normal samples at high resolution and delve into the intricate regulatory mechanisms governing the metabolic activity of malignant cells in gastric cancer. Methods: Utilizing single-cell RNA sequencing data from gastric cancer, we constructed metabolic landscape maps for different cell types in tumor and normal samples. Employing unsupervised clustering, we categorized malignant cells in tumor samples into high and low metabolic subclusters and further explored the characteristics of these subclusters. Results: Our research findings indicate that epithelial cells in tumor samples exhibit significantly higher activity in most KEGG metabolic pathways compared to other cell types. Unsupervised clustering, based on the scores of metabolic pathways, classified malignant cells into high and low metabolic subclusters. In the high metabolic subcluster, it demonstrated the potential to induce a stronger immune response, correlating with a relatively favorable prognosis. In the low metabolic subcluster, a subset of cells resembling cancer stem cells (CSCs) was identified, and its prognosis was less favorable. Furthermore, a set of risk genes associated with this subcluster was discovered. Conclusion: This study reveals the intricate regulatory mechanisms governing the metabolic activity of malignant cells in gastric cancer, offering new perspectives for improving prognosis and treatment strategies.

Identification and Pharmacological Targeting of Treatment-Resistant, Stem-like Breast Cancer Cells for Combination Therapy

Tumors frequently harbor isogenic yet epigenetically distinct subpopulations of multi-potent cells with high tumor-initiating potential-often called Cancer Stem-Like Cells (CSLCs). These can display preferential resistance to standard-of-care chemotherapy. Single-cell analyses can help elucidate Master Regulator (MR) proteins responsible for governing the transcriptional state of these cells, thus revealing complementary dependencies that may be leveraged via combination therapy. Interrogation of single-cell RNA sequencing profiles from seven metastatic breast cancer patients, using perturbational profiles of clinically relevant drugs, identified drugs predicted to invert the activity of MR proteins governing the transcriptional state of chemoresistant CSLCs, which were then validated by CROP-seq assays. The top drug, the anthelmintic albendazole, depleted this subpopulation in vivo without noticeable cytotoxicity. Moreover, sequential cycles of albendazole and paclitaxel-a commonly used chemotherapeutic -displayed significant synergy in a patient-derived xenograft (PDX) from a TNBC patient, suggesting that network-based approaches can help develop mechanism-based combinatorial therapies targeting complementary subpopulations.

Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies

BACKGROUND

Pancreatic cancer (PC) stands out as one of the most formidable malignancies and exhibits an exceptionally unfavorable clinical prognosis due to the absence of well-defined diagnostic indicators and its tendency to develop resistance to therapeutic interventions. The primary objective of this present study was to identify extracellular matrix (ECM)-related hub genes (HGs) and their corresponding molecular signatures, with the intent of potentially utilizing them as biomarkers for diagnostic, prognostic, and therapeutic applications.

METHODS

Three microarray datasets were sourced from the NCBI database to acquire upregulated differentially expressed genes (DEGs), while MatrisomeDB was employed for filtering ECM-related genes. Subsequently, a protein-protein interaction (PPI) network was established using the STRING database. The created network was visually inspected through Cytoscape, and HGs were identified using the CytoHubba plugin tool. Furthermore, enrichment analysis, expression pattern analysis, clinicopathological correlation, survival analysis, immune cell infiltration analysis, and examination of chemical compounds were carried out using Enrichr, GEPIA2, ULCAN, Kaplan Meier plotter, TIMER2.0, and CTD web platforms, respectively. The diagnostic and prognostic significance of HGs was evaluated through the ROC curve analysis.

RESULTS

Ten genes associated with ECM functions were identified as HGs among 131 DEGs obtained from microarray datasets. Notably, the expression of these HGs exhibited significantly (p < 0.05) higher in PC, demonstrating a clear association with tumor advancement. Remarkably, higher expression levels of these HGs were inversely correlated with the likelihood of patient survival. Moreover, ROC curve analysis revealed that identified HGs are promising biomarkers for both diagnostic (AUC > 0.75) and prognostic (AUC > 0.64) purposes. Furthermore, we observed a positive correlation between immune cell infiltration and the expression of most HGs. Lastly, our study identified nine compounds with significant interaction profiles that could potentially act as effective chemical agents targeting the identified HGs.

CONCLUSION

Taken together, our findings suggest that COL1A1, KRT19, MMP1, COL11A1, SDC1, ITGA2, COL1A2, POSTN, FN1, and COL5A1 hold promise as innovative biomarkers for both the diagnosis and prognosis of PC, and they present as prospective targets for therapeutic interventions aimed at impeding the progression PC.

EM-transcriptomic signature predicts drug response in advanced stages of high-grade serous ovarian carcinoma based on ascites-derived primary cultures

Introduction: High-grade serous ovarian carcinoma (HGSOC) remains a medical challenge despite considerable improvements in the treatment. Unfortunately, over 75% of patients have already metastasized at the time of diagnosis. Advances in understanding the mechanisms underlying how ascites cause chemoresistance are urgently needed to derive novel therapeutic strategies. This study aimed to identify the molecular markers involved in drug sensitivity and highlight the use of ascites as a potential model to investigate HGSOC treatment options. Methods: After conducting an in silico analysis, eight epithelial-mesenchymal (EM)-associated genes related to chemoresistance were identified. To evaluate differences in EM-associated genes in HGSOC samples, we analyzed ascites-derived HGSOC primary cell culture (AS), tumor (T), and peritoneal nodule (NP) samples. Moreover, in vitro experiments were employed to measure tumor cell proliferation and cell migration in AS, following treatment with doxorubicin (DOX) and cisplatin (CIS) and expression of these markers. Results: Our results showed that AS exhibits a mesenchymal phenotype compared to tumor and peritoneal nodule samples. Moreover, DOX and CIS treatment leads to an invasive-intermediate epithelial-to-mesenchymal transition (EMT) state of the AS by different EM-associated marker expression. For instance, the treatment of AS showed that CDH1 and GATA6 decreased after CIS exposure and increased after DOX treatment. On the contrary, the expression of KRT18 has an opposite pattern. Conclusion: Taken together, our study reports a comprehensive investigation of the EM-associated genes after drug exposure of AS. Exploring ascites and their associated cellular and soluble components is promising for understanding the HGSOC progression and treatment response at a personalized level.

Molecular biomarkers in prostate cancer tumorigenesis and clinical relevance

Prostate cancer (PCa) is the second most frequent type of cancer in men and assessing circulating tumor cells (CTCs) by liquid biopsy is a promising tool to help in cancer early detection, staging, risk of recurrence evaluation, treatment prediction and monitoring. Blood-based liquid biopsy approaches enable the enrichment, detection and characterization of CTCs by biomarker analysis. Hence, comprehending the molecular markers, their role on each stage of cancer development and progression is essential to provide information that can help in future implementation of these biomarkers in clinical assistance. In this review, we studied the molecular markers most associated with PCa CTCs to better understand their function on tumorigenesis and metastatic cascade, the methodologies utilized to analyze these biomarkers and their clinical significance, in order to summarize the available information to guide researchers in their investigations, new hypothesis formulation and target choice for the development of new diagnostic and treatment tools.

Molecular data representation based on gene embeddings for cancer drug response prediction

Cancer drug response prediction is a crucial task in precision medicine, but existing models have limitations in effectively representing molecular profiles of cancer cells. Specifically, when these models represent molecular omics data such as gene expression, they employ a one-hot encoding-based approach, where a fixed gene set is selected for all samples and omics data values are assigned to specific positions in a vector. However, this approach restricts the utilization of embedding-vector-based methods, such as attention-based models, and limits the flexibility of gene selection. To address these issues, our study proposes gene embedding-based fully connected neural networks (GEN) that utilizes gene embedding vectors as input data for cancer drug response prediction. The GEN allows for the use of embedding-vector-based architectures and different gene sets for each sample, providing enhanced flexibility. To validate the efficacy of GEN, we conducted experiments on three cancer drug response datasets. Our results demonstrate that GEN outperforms other recently developed methods in cancer drug prediction tasks and offers improved gene representation capabilities. All source codes are available at https://github.com/DMCB-GIST/GEN/ .

Entrectinib a Plausible Inhibitor for Osteopontin (SPP1) in Cervical Cancer-Integrated Bioinformatic Approach

Cervical cancer is one of the major causes of death in women, especially in developing countries bearing more than a quarter of the global burden. Secreted phosphoprotein-1, also known as OPN (osteopontin), is an integrin-binding glycophosphoprotein that is overexpressed in a variety of tumors. OPN is a chemokine-like calcified ECM-associated protein that plays a crucial role in evaluating the metastatic potential of various cancers. However, the role of SPP1 in the tumor microenvironment and associated signaling pathways in CC is still unclear. In our study, three CC microarray datasets (GSE9750, GSE46857, and GSE67522) were obtained from the GEO database to identify the differentially expressed genes. Enrichment analysis was carried out by Enrichr and ShinyGO and the PPI interaction network was created by using String and Cytoscape. GEPIA datasets were used to validate the top 10 hub genes, and virtual screening, docking, and dynamic simulation studies were used to identify a suitable inhibitor against the OPN protein using MVD, PyRx, and GROMACS respectively. Our results show that a total of 11 DEGs were common for three datasets and gene ontology pathway enrichment analysis revealed that 2 biological processes i.e. programmed cell death and animal organ development commonly affected mechanisms in all three datasets. Docking and dynamic studies revealed that Entrectinib showed excellent binding affinity against OPN protein. Based on the results, we conclude that OPN is one of the most upregulated genes in cervical cancer and Entrectinib emerges to be a promising potential OPN inhibitor to curtail cervical cancer progression. Schematic representation: The schematic representation of methodology steps is illustrated in the graphical abstract. Schematic representation of methodology.

E3 ubiquitin ligase RNF187 promotes growth of spermatogonia via lysine 48-linked polyubiquitination-mediated degradation of KRT36/KRT84

Ubiquitination is the most common post-translational modification and is essential for various cellular regulatory processes. RNF187, which is known as RING domain AP1 coactivator-1, is a member of the RING finger family. RNF187 can promote the proliferation and migration of various tumor cells. However, whether it has a similar role in regulating spermatogonia is not clear. This study explored the role and molecular mechanism of RNF187 in a mouse spermatogonia cell line (GC-1). We found that RNF187 knockdown reduced the proliferation and migration of GC-1 cells and promoted their apoptosis. RNF187 overexpression significantly increased the proliferation and migration of GC-1 cells. In addition, we identified Keratin36/Keratin84 (KRT36/KRT84) as interactors with RNF187 by co-immunoprecipitation and mass spectrometry analyses. RNF187 promoted GC-1 cell growth by degrading KRT36/KRT84 via lysine 48-linked polyubiquitination. Subsequently, we found that KRT36 or KRT84 overexpression significantly attenuated proliferation and migration of RNF187-overexpressing GC-1 cells. In summary, our study explored the involvement of RNF187 in regulating the growth of spermatogonia via lysine 48-linked polyubiquitination-mediated degradation of KRT36/KRT84. This may provide a promising new strategy for treating infertility caused by abnormal spermatogonia development.

DNA methylation-associated allelic inactivation regulates Keratin 19 gene expression during pancreatic development and carcinogenesis

Within the pancreas, Keratin 19 (KRT19) labels the ductal lineage and is a determinant of pancreatic ductal adenocarcinoma (PDAC). To investigate KRT19 expression dynamics, we developed a human pluripotent stem cell (PSC)-based KRT19-mCherry reporter system in different genetic backgrounds to monitor KRT19 expression from its endogenous gene locus. A differentiation protocol to generate mature pancreatic duct-like organoids was applied. While KRT19/mCherry expression became evident at the early endoderm stage, mCherry signal was present in nearly all cells at the pancreatic endoderm (PE) and pancreatic progenitor (PP) stages. Interestingly, despite homogenous KRT19 expression, mCherry positivity dropped to 50% after ductal maturation, indicating a permanent switch from biallelic to monoallelic expression. DNA methylation profiling separated the distinct differentiation intermediates, with site-specific DNA methylation patterns occurring at the KRT19 locus during ductal maturation. Accordingly, the monoallelic switch was partially reverted upon treatment with a DNA-methyltransferase inhibitor. In human PDAC cohorts, high KRT19 levels correlate with low locus methylation and decreased survival. At the same time, activation of oncogenic KRASG12D signalling in our reporter system reversed monoallelic back to biallelic KRT19 expression in pancreatic duct-like organoids. Allelic reactivation was also detected in single-cell transcriptomes of human PDACs, which further revealed a positive correlation between KRT19 and KRAS expression. Accordingly, KRAS mutant PDACs had higher KRT19 mRNA but lower KRT19 gene locus DNA methylation than wildtype counterparts. KRT19 protein was additionally detected in plasma of PDAC patients, with higher concentrations correlating with shorter progression-free survival in gemcitabine/nabPaclitaxel-treated and opposing trends in FOLFIRINOX-treated patients. Apart from being an important pancreatic ductal lineage marker, KRT19 appears tightly controlled via a switch from biallelic to monoallelic expression during ductal lineage entry and is aberrantly expressed after oncogenic KRASG12D expression, indicating a role in PDAC development and malignancy. Soluble KRT19 might serve as a relevant biomarker to stratify treatment. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Targeting the KRT16-vimentin axis for metastasis in lung cancer

Lung cancer is the most diagnosed malignant cancer and the leading cause of cancer-related deaths worldwide, with advanced stage and metastasis being a major issue. The mechanism leading to metastasis is not yet understood. Here, we found that KRT16 is upregulated in metastatic lung cancer tissues and correlated with poor overall survival. Knockdown of KRT16 inhibits metastasis of lung cancer both in vitro and in vivo. Mechanistically, KRT16 interacts with vimentin, and depletion of KRT16 leads to downregulation of vimentin. KRT16 acquired its oncogenic ability by stabilizing vimentin, and vimentin is required for KRT16-driven metastasis. FBXO21 mediates the polyubiquitination and degradation of KRT16, and vimentin inhibits KRT16 ubiquitination and degradation by impairing its interaction with FBXO21. Significantly, IL-15 inhibits metastasis of lung cancer in a mouse model through upregulation of FBXO21, and the level of IL-15 in circulating serum was significantly higher in nonmetastatic lung cancer patients than in metastatic patients. Our findings indicate that targeting the FBXO21/KRT16/vimentin axis may benefit lung cancer patients with metastasis.

Proteomics-Based Identification of Dysregulated Proteins and Biomarker Discovery in Invasive Ductal Carcinoma, the Most Common Breast Cancer Subtype

Invasive ductal carcinoma (IDC) is the most common histological subtype of malignant breast cancer (BC), and accounts for 70-80% of all invasive BCs. IDC demonstrates great heterogeneity in clinical and histopathological characteristics, prognoses, treatment strategies, gene expressions, and proteomic profiles. Significant proteomic determinants of the progression from intraductal pre-invasive malignant lesions of the breast, which characterize a ductal carcinoma in situ (DCIS), to IDC, are still poorly identified, validated, and clinically applied. In the era of "6P" medicine, it remains a great challenge to determine which patients should be over-treated versus which need to be actively monitored without aggressive treatment. The major difficulties for designating DCIS to IDC progression may be solved by understanding the integrated genomic, transcriptomic, and proteomic bases of invasion. In this review, we showed that multiple proteomics-based techniques, such as LC-MS/MS, MALDI-ToF MS, SELDI-ToF-MS, MALDI-ToF/ToF MS, MALDI-MSI or MasSpec Pen, applied to in-tissue, off-tissue, BC cell lines and liquid biopsies, improve the diagnosis of IDC, as well as its prognosis and treatment monitoring. Classic proteomics strategies that allow the identification of dysregulated protein expressions, biological processes, and interrelated pathway analyses based on aberrant protein-protein interaction (PPI) networks have been improved to perform non-invasive/minimally invasive biomarker detection of early-stage IDC. Thus, in modern surgical oncology, highly sensitive, rapid, and accurate MS-based detection has been coupled with "proteome point sampling" methods that allow for proteomic profiling by in vivo "proteome point characterization", or by minimal tissue removal, for ex vivo accurate differentiation and delimitation of IDC. For the detection of low-molecular-weight proteins and protein fragments in bodily fluids, LC-MS/MS and MALDI-MS techniques may be coupled to enrich and capture methods which allow for the identification of early-stage IDC protein biomarkers that were previously invisible for MS-based techniques. Moreover, the detection and characterization of protein isoforms, including posttranslational modifications of proteins (PTMs), is also essential to emphasize specific molecular mechanisms, and to assure the early-stage detection of IDC of the breast.

KRT13 is upregulated in pancreatic cancer stem-like cells and associated with radioresistance

Pancreatic cancer is one of the most aggressive cancers and the seventh leading cause of cancer-associated death in the world. Radiation is performed as an adjuvant therapy as well as anti-cancer drugs. Because cancer stem-like cells (CSCs) are considered to be radioresistant and cause recurrence and metastasis, understanding their properties is required for the development of novel therapeutic strategies. To investigate the CSC properties of pancreatic cancer cells, we used a pancreatic CSC model, degron (++) cells, which have low proteasome activity. Degron (++) cells displayed radioresistance in comparison with control cells. Using Ribonucleic acid (RNA) sequencing, we successfully identified KRT13 as a candidate gene responsible for radioresistance. Knockdown of KRT13 sensitized the degron (++) cells to radiation. Furthermore, a database search revealed that KRT13 is upregulated in pancreatic cancer cell lines and that high expression of KRT13 is associated with poorer prognosis. These results indicate that a combination therapy of KRT13 knockdown and radiation could hold therapeutic promise in pancreatic cancer.

Duplex Phenotype Detection and Targeting of Breast Cancer Cells Using Nanotube Nanoprobes and Raman Imaging

We designed, synthesized, and characterized a Raman nanoprobe made of dye-sensitized single-walled carbon nanotubes (SWCNTs) that can selectively target biomarkers of breast cancer cells. The nanoprobe is composed of Raman-active dyes encapsulated inside a SWCNT, whose surface is covalently grafted with poly(ethylene glycol) (PEG) at a density of ∼0.7% per carbon. Using α-sexithiophene- and β-carotene-derived nanoprobes covalently bound to an antibody, either anti-E-cadherin (E-cad) or anti-keratin-19 (KRT19), we prepared two distinct nanoprobes that specifically recognize biomarkers on breast cancer cells. Immunogold experiments and transmission electron microscopy (TEM) images are first used to guide the synthesis protocol for higher PEG-antibody attachment and biomolecule loading capacity. The duplex of nanoprobes was then applied to target E-cad and KRT19 biomarkers in T47D and MDA-MB-231 breast cancer cell lines. Hyperspectral imaging of specific Raman bands allows for simultaneous detection of this nanoprobe duplex on target cells without the need for additional filters or subsequent incubation steps. Our results confirm the high reproducibility of the nanoprobe design for duplex detection and highlight the potential of Raman imaging for advanced biomedical applications in oncology.

PMCA inhibition reverses drug resistance in clinically refractory cancer patient-derived models

BACKGROUND

Cancer cells have developed molecular strategies to cope with evolutionary stressors in the dynamic tumor microenvironment. Peroxisome proliferator-activated receptor-γ coactivator-1α (PGC1α) is a metabolic rheostat that regulates diverse cellular adaptive behaviors, including growth and survival. However, the mechanistic role of PGC1α in regulating cancer cell viability under metabolic and genotoxic stress remains elusive.

METHODS

We investigated the PGC1α-mediated survival mechanisms in metabolic stress (i.e., glucose deprivation-induced metabolic stress condition)-resistant cancer cells. We established glucose deprivation-induced metabolic stress-resistant cells (selected cells) from parental tumor cells and silenced or overexpressed PGC1α in selected and parental tumor cells.

RESULTS

Several in vitro and in vivo mouse experiments were conducted to elucidate the contribution of PGC1α to cell viability in metabolic stress conditions. Interestingly, in the mouse xenograft model of patient-derived drug-resistant cancer cells, each group treated with an anti-cancer drug alone showed no drastic effects, whereas a group that was co-administered an anti-cancer drug and a specific PMCA inhibitor (caloxin or candidate 13) showed marked tumor shrinkage.

CONCLUSIONS

Our results suggest that PGC1α is a key regulator of anti-apoptosis in metabolic and genotoxic stress-resistant cells, inducing PMCA expression and allowing survival in glucose-deprived conditions. We have discovered a novel therapeutic target candidate that could be employed for the treatment of patients with refractory cancers.

"In the light of evolution:" keratins as exceptional tumor biomarkers

Keratins (KRTs) are the intermediate filament-forming proteins of epithelial cells, classified, according to their physicochemical properties, into "soft" and "hard" keratins. They have a key role in several aspects of cancer pathophysiology, including cancer cell invasion and metastasis, and several members of the KRT family serve as diagnostic or prognostic markers. The human genome contains both, functional KRT genes and non-functional KRT pseudogenes, arranged in two uninterrupted clusters on chromosomes 12 and 17. This characteristic renders KRTs ideal for evolutionary studies. Herein, comprehensive phylogenetic analyses of KRT homologous proteins in the genomes of major taxonomic divisions were performed, so as to fill a gap in knowledge regarding the functional implications of keratins in cancer biology among tumor-bearing species. The differential expression profiles of KRTs in diverse types of cancers were investigated by analyzing high-throughput data, as well. Several KRT genes, including the phylogenetically conserved ones, were found to be deregulated across several cancer types and to participate in a common protein-protein interaction network. This indicates that, at least in cancer-bearing species, these genes might have been under similar evolutionary pressure, perhaps to support the same important function(s). In addition, semantic relations between KRTs and cancer were detected through extensive text mining. Therefore, by applying an integrative in silico pipeline, the evolutionary history of KRTs was reconstructed in the context of cancer, and the potential of using non-mammalian species as model organisms in functional studies on human cancer-associated KRT genes was uncovered.

Multiset multicover methods for discriminative marker selection

Markers are increasingly being used for several high-throughput data analysis and experimental design tasks. Examples include the use of markers for assigning cell types in scRNA-seq studies, for deconvolving bulk gene expression data, and for selecting marker proteins in single-cell spatial proteomics studies. Most marker selection methods focus on differential expression (DE) analysis. Although such methods work well for data with a few non-overlapping marker sets, they are not appropriate for large atlas-size datasets where several cell types and tissues are considered. To address this, we define the phenotype cover (PC) problem for marker selection and present algorithms that can improve the discriminative power of marker sets. Analysis of these sets on several marker-selection tasks suggests that these methods can lead to solutions that accurately distinguish different phenotypes in the data.

The Group B Streptococcal Adhesin BspC Interacts with Host Cytokeratin 19 To Promote Colonization of the Female Reproductive Tract

Streptococcus agalactiae, otherwise known as Group B Streptococcus (GBS), is an opportunistic pathogen that vaginally colonizes approximately one third of healthy women. During pregnancy, this can lead to in utero infection, resulting in premature rupture of membranes, chorioamnionitis, and stillbirths. Furthermore, GBS causes serious infection in newborns, including sepsis, pneumonia, and meningitis. Previous studies have indicated that GBS antigen (Ag) I/II family proteins promote interaction with vaginal epithelial cells; thus, we hypothesized that the Ag I/II Group B streptococcal surface protein C (BspC) contributes to GBS colonization of the female reproductive tract (FRT). Here, we show that a ΔbspC mutant has decreased bacterial adherence to vaginal, ecto-, and endocervical cells, as well as decreased auto-aggregation and biofilm-like formation on cell monolayers. Using a murine model of vaginal colonization, we observed that the ΔbspC mutant strain exhibited a significant fitness defect compared to wild-type (WT) GBS and was less able to ascend to the cervix and uterus in vivo, resulting in reduced neutrophil chemokine signaling. Furthermore, we determined that BspC interacts directly with the host intermediate filament protein cytokeratin 19 (K19). Surface localization of K19 was increased during GBS infection, and interaction was mediated by the BspC variable (V) domain. Finally, mice treated with a drug that targets the BspC V-domain exhibited reduced bacterial loads in the vaginal lumen and reproductive tissues. These results demonstrate the importance of BspC in promoting GBS colonization of the FRT and that it may be targeted therapeutically to reduce GBS vaginal persistence and ascending infection. IMPORTANCE Group B Streptococcus (GBS) asymptomatically colonizes the female reproductive tract (FRT) of up to one third of women, but GBS carriage can lead to adverse pregnancy outcomes, including premature rupture of membranes, preterm labor, and chorioamnionitis. GBS colonization during pregnancy is also the largest predisposing factor for neonatal GBS disease, including pneumonia, sepsis, and meningitis. The molecular interactions between bacterial surface proteins and the host cell receptors that promote GBS colonization are vastly understudied, and a better understanding would facilitate development of novel therapeutics to prevent GBS colonization and disease. Here, we characterize the role of the GBS surface protein BspC in colonization of the FRT. We show for the first time that GBS infection induces cytokeratin 19 (K19) surface localization on vaginal epithelial cells; GBS then uses the BspC V-domain to interact with K19 to promote colonization and ascending infection. Furthermore, this interaction can be targeted therapeutically to reduce GBS carriage.

Comprehensive Transcriptomic and Proteomic Analyses Identify a Candidate Gene Set in Cross-Resistance for Endocrine Therapy in Breast Cancer

Endocrine therapy (ET) of selective estrogen receptor modulators (SERMs), selective estrogen receptor downregulators (SERDs), and aromatase inhibitors (AIs) has been used as the gold standard treatment for hormone-receptor-positive (HR+) breast cancer. Despite its clinical benefits, approximately 30% of patients develop ET resistance, which remains a major clinical challenge in patients with HR+ breast cancer. The mechanisms of ET resistance mainly focus on mutations in the ER and related pathways; however, other targets still exist from ligand-independent ER reactivation. Moreover, mutations in the ER that confer resistance to SERMs or AIs seldom appear in SERDs. To date, little research has been conducted to identify a critical target that appears in both SERMs/SERDs and AIs. In this study, we conducted comprehensive transcriptomic and proteomic analyses from two cohorts of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) to identify the critical targets for both SERMs/SERDs and AIs of ET resistance. From a treatment response cohort with treatment response for the initial ET regimen and an endocrine therapy cohort with survival outcomes, we identified candidate gene sets that appeared in both SERMs/SERDs and AIs of ET resistance. The candidate gene sets successfully differentiated progress/resistant groups (PD) from complete response groups (CR) and were significantly correlated with survival outcomes in both cohorts. In summary, this study provides valuable clinical implications for the critical roles played by candidate gene sets in the diagnosis, mechanism, and therapeutic strategy for both SERMs/SERDs and AIs of ET resistance for the future.

Hub Gene Screening Associated with Early Glaucoma: An Integrated Bioinformatics Analysis

Background

Primary open-angle glaucoma (POAG) is the most common type of glaucoma. The potential influence of some DEGs on the progression of POAG was still incomplete. In this study, we integrated transcriptome data with clinical data to investigate the relationship between them in POAG patients.

Methods

The gene expression profile (GSE27276) from Gene Expression Omnibus (GEO) was used to identify DEGs. The LIMMA package of R was used to identify the DEGs (Diboun et al., 2006). The adjusted P values (adj P value) were calculated instead to avoid the appearance of false-positive results. Genes with |log₂ fold change (FC)| larger than 1 and adj P value < 0.01 were taken as DEGs between PH and PC samples. GO (Gene Ontology) function and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses of the DEGs were performed. Protein-protein interactions (PPIs) of the DEGs were constructed.

Results

A total of 182 DEGs were identified through our analysis, of which 119 genes were upregulated and 63 genes were downregulated. GO enrichment analysis illustrated that these DEGs were mostly enriched into haptoglobin binding, antioxidant activity, and organic acid binding. KEGG enrichment analysis illustrated that these DEGs were mostly enriched into Staphylococcus aureus infection. The most significant module was identified by MCODE consists of 8 DEGs, and BCL11A is the seeded gene. The second most significant module consists of 5 DEGs, and IL1RN is the seeded gene.

Conclusion

Our results demonstrate the potential influence of some DEGs on the progression of POAG, providing a comprehensive bioinformatics analysis of the pathogenesis, which may contribute to future investigation into the molecular mechanisms and biomarkers.

YB-1 is a positive regulator of KLF5 transcription factor in basal-like breast cancer

Y-box binding protein 1 (YB-1) is a well-known oncogene highly expressed in various cancers, including basal-like breast cancer (BLBC). Beyond its role as a transcription factor, YB-1 is newly defined as an epigenetic regulator involving RNA 5-methylcytosine. However, its specific targets and pro-cancer functions are poorly defined. Here, based on clinical database, we demonstrate a positive correlation between Kruppel-like factor 5 (KLF5) and YB-1 expression in breast cancer patients, but a negative correlation with that of Dachshund homolog 1 (DACH1). Mechanistically, YB-1 enhances KLF5 expression not only through transcriptional activation that can be inhibited by DACH1, but also by stabilizing KLF5 mRNA in a RNA 5-methylcytosine modification-dependent manner. Additionally, ribosomal S6 kinase 2 (RSK2) mediated YB-1 phosphorylation at Ser102 promotes YB-1/KLF5 transcriptional complex formation, which co-regulates the expression of BLBC specific genes, Keratin 16 (KRT16) and lymphocyte antigen 6 family member D (Ly6D), to promote cancer cell proliferation. The RSK inhibitor, LJH685, suppressed BLBC cell tumourigenesis in vivo by disturbing YB-1-KLF5 axis. Our data suggest that YB-1 positively regulates KLF5 at multiple levels to promote BLBC progression. The novel RSK2-YB-1-KLF5-KRT16/Ly6D axis provides candidate diagnostic markers and therapeutic targets for BLBC.

MFUM-BrTNBC-1, a Newly Established Patient-Derived Triple-Negative Breast Cancer Cell Line: Molecular Characterisation, Genetic Stability, and Comprehensive Comparison with Commercial Breast Cancer Cell Lines

Triple-negative breast cancer (TNBC) is a breast cancer (BC) subtype that accounts for approximately 15–20% of all BC cases. Cancer cell lines (CLs) provide an efficient way to model the disease. We have recently isolated a patient-derived triple-negative BC CL MFUM-BrTNBC-1 and performed a detailed morphological and molecular characterisation and a comprehensive comparison with three commercial BC CLs (MCF-7, MDA-MB-231, MDA-MB-453). Light and fluorescence microscopy were used for morphological studies; immunocytochemical staining for hormone receptor, p53 and Ki67 status; RNA sequencing, qRT-PCR and STR analysis for molecular characterisation; and biomedical image analysis for comparative phenotypical analysis. The patient tissue-derived MFUM-BrTNBC-1 maintained the primary triple-negative receptor status. STR analysis showed a stable and unique STR profile up to the 6th passage. MFUM-BrTNBC-1 expressed EMT transition markers and displayed changes in several cancer-related pathways (MAPK, Wnt and PI3K signalling; nucleotide excision repair; and SWI/SNF chromatin remodelling). Morphologically, MFUM-BrTNBC-1 differed from the commercial TNBC CL MDA-MB-231. The advantages of MFUM-BrTNBC-1 are its isolation from a primary tumour, rather than a metastatic site; good growth characteristics; phenotype identical to primary tissue; complete records of origin; a unique identifier; complete, unique STR profile; quantifiable morphological properties; and genetic stability up to (at least) the 6th passage.

Spatial protein heterogeneity analysis in frozen tissues to evaluate tumor heterogeneity

A new workflow for protein-based tumor heterogeneity probing in tissues is here presented. Tumor heterogeneity is believed to be key for therapy failure and differences in prognosis in cancer patients. Comprehending tumor heterogeneity, especially at the protein level, is critical for tracking tumor evolution, and showing the presence of different phenotypical variants and their location with respect to tissue architecture. Although a variety of techniques is available for quantifying protein expression, the heterogeneity observed in the tissue is rarely addressed. The proposed method is validated in breast cancer fresh-frozen tissues derived from five patients. Protein expression is quantified on the tissue regions of interest (ROI) with a resolution of up to 100 μm in diameter. High heterogeneity values across the analyzed patients in proteins such as cytokeratin 7, β-actin and epidermal growth factor receptor (EGFR) using a Shannon entropy analysis are observed. Additionally, ROIs are clustered according to their expression levels, showing their location in the tissue section, and highlighting that similar phenotypical variants are not always located in neighboring regions. Interestingly, a patient with a phenotype related to increased aggressiveness of the tumor presents a unique protein expression pattern. In summary, a workflow for the localized extraction and protein analysis of regions of interest from frozen tissues, enabling the evaluation of tumor heterogeneity at the protein level is presented.

Differential Expression of Estrogen-Responsive Genes in Women with Psoriasis

In women, the flow of psoriasis is influenced by each phase of a woman’s life cycle. According to previous findings, significant changes in the levels of sex hormones affect the severity of the disease. Aim: The aim of this study was to identify the estrogen-responsive genes that could be responsible for the exacerbation of psoriasis in menopausal women. Methods: Skin samples of lesional skin donated by psoriasis patients (n = 5) were compared with skin samples of healthy volunteers (n = 5) using liquid chromatography–tandem mass spectrometry (LC–MS/MS). The set of differentially expressed proteins was subjected to protein ontology analysis to identify differentially expressed estrogen-responsive proteins. The expression of discovered proteins was validated by qPCR and ELISA on four groups of female participants. The first group included ten psoriasis patients without menopause; the second included eleven postmenopausal patients; the third included five healthy volunteers without menopause; and the fourth included six postmenopausal volunteers. Moreover, the participants’ blood samples were used to assess the levels of estradiol, progesterone, and testosterone. Results: We found that the levels of estradiol and progesterone were significantly lower and the levels of testosterone were significantly higher in the blood of patients compared to the control. The protein ontology analysis of LC–MS/MS data identified six proteins, namely HMOX1, KRT19, LDHA, HSPD1, MAPK1, and CA2, differentially expressed in the lesional skin of female patients compared to male patients. ELISA and qPCR experiments confirmed differential expression of the named proteins and their mRNA. The genes encoding the named proteins were differentially expressed in patients compared to volunteers. However, KRT19 and LDHA were not differentially expressed when we compared patients with and without menopause. All genes, except MAPK1, were differentially expressed in patients with menopause compared to the volunteers with menopause. HMOX1, KRT19, HSPD1, and LDHA were differentially expressed in patients without menopause compared to the volunteers without menopause. However, no significant changes were found when we compared healthy volunteers with and without menopause. Conclusion: Our experiments discovered a differential expression of six estrogen-controlled genes in the skin of female patients. Identification of these genes and assessment of the changes in their expression provide insight into the biological effects of estrogen in lesional skin. The results of proteomic analysis are available via ProteomeXchange with identifier PXD021673.

Integrative Data Analytic Framework to Enhance Cancer Precision Medicine

With the advancement of high-throughput biotechnologies, we increasingly accumulate biomedical data about diseases, especially cancer. There is a need for computational models and methods to sift through, integrate, and extract new knowledge from the diverse available data, to improve the mechanistic understanding of diseases and patient care. To uncover molecular mechanisms and drug indications for specific cancer types, we develop an integrative framework able to harness a wide range of diverse molecular and pan-cancer data. We show that our approach outperforms the competing methods and can identify new associations. Furthermore, it captures the underlying biology predictive of drug response. Through the joint integration of data sources, our framework can also uncover links between cancer types and molecular entities for which no prior knowledge is available. Our new framework is flexible and can be easily reformulated to study any biomedical problem.

Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer

Background

Contemporary deep learning approaches show cutting-edge performance in a variety of complex prediction tasks. Nonetheless, the application of deep learning in healthcare remains limited since deep learning methods are often considered as non-interpretable black-box models. However, the machine learning community made recent elaborations on interpretability methods explaining data point-specific decisions of deep learning techniques. We believe that such explanations can assist the need in personalized precision medicine decisions via explaining patient-specific predictions.

Methods

Layer-wise Relevance Propagation (LRP) is a technique to explain decisions of deep learning methods. It is widely used to interpret Convolutional Neural Networks (CNNs) applied on image data. Recently, CNNs started to extend towards non-Euclidean domains like graphs. Molecular networks are commonly represented as graphs detailing interactions between molecules. Gene expression data can be assigned to the vertices of these graphs. In other words, gene expression data can be structured by utilizing molecular network information as prior knowledge. Graph-CNNs can be applied to structured gene expression data, for example, to predict metastatic events in breast cancer. Therefore, there is a need for explanations showing which part of a molecular network is relevant for predicting an event, e.g., distant metastasis in cancer, for each individual patient.

Results

We extended the procedure of LRP to make it available for Graph-CNN and tested its applicability on a large breast cancer dataset. We present Graph Layer-wise Relevance Propagation (GLRP) as a new method to explain the decisions made by Graph-CNNs. We demonstrate a sanity check of the developed GLRP on a hand-written digits dataset and then apply the method on gene expression data. We show that GLRP provides patient-specific molecular subnetworks that largely agree with clinical knowledge and identify common as well as novel, and potentially druggable, drivers of tumor progression.

Conclusions

The developed method could be potentially highly useful on interpreting classification results in the context of different omics data and prior knowledge molecular networks on the individual patient level, as for example in precision medicine approaches or a molecular tumor board.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13073-021-00845-7).

Prognostic significance of KRT19 in Lung Squamous Cancer

Backgroud: Keratin 19 (KRT19) is the intermediate filament that constitutes the cytoskeleton and regulates cell-cycle and cell death. Objective: We aimed to assess whether KRT19 was involved in lung cancer development. Methods: The expression of KRT19 in lung cancer was evaluated from mRNA expression on open databse and protein abundance on tumor tissue array. Results: Using open microarray gene expression datasets and differential expression analysis, we found that KRT19 was upregulated in lung cancer compared with normal tissue. Further analysis suggested that KRT19 mRNA expression was correlated with tumor progression and overall survival in lung cancer patients. As KRT19 was overexpressed in adenocarcinoma (AC) and squamous cell carcinoma (SCC), we examined the prognostic value of KRT19 protein abundance by tissue microarray (TMA). The results suggested that protein expression of KRT19 was significantly associated with overall survival of SCC. Conclusions: Giving the prognostic role of KRT19 in lung cancer, KRT19 could be considered as an potential molecular marker in lung cancer, especially in SCC.

The Signaling Duo CXCL12 and CXCR4: Chemokine Fuel for Breast Cancer Tumorigenesis

Simple Summary

Breast cancer remains the most common malignancy in women. In this review, we explore the role of the CXCL12/CXCR4 pathway in breast cancer. We show that the CXCL12/CXCR4 cascade is involved in nearly every aspect of breast cancer tumorigenesis including proliferation, cell motility and distant metastasis. Moreover, we summarize current knowledge about the CXCL12/CXCR4-targeted therapies. Due to the critical roles of this pathway in breast cancer and other malignancies, we believe that audiences in different fields will find this overview helpful.

Abstract

The CXCL12/CXCR4 signaling pathway has emerged in the recent years as a key player in breast cancer tumorigenesis. This pathway controls many aspects of breast cancer development including cancer cell proliferation, motility and metastasis to all target organs. Moreover, the CXCL12/CXCR4 cascade affects both immune and stromal cells, creating tumor-supporting microenvironment. In this review, we examine state-of-the-art knowledge about detrimental roles of the CXCL12/CXCR4 signaling, discuss its therapeutic potential and suggest further research directions beneficial both for basic research and personalized medicine in breast cancer.

GPR50 Promotes Hepatocellular Carcinoma Progression via the Notch Signaling Pathway through Direct Interaction with ADAM17

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, and it is thus critical to identify novel molecular biomarkers of HCC prognosis and elucidate the molecular mechanisms underlying HCC progression. Here, we show that G-protein-coupled receptor 50 (GPR50) in HCC is overexpressed and that GPR50 knockdown may downregulate cancer cell progression through attenuation of the Notch signaling pathway. GPR50 knockdown was found to reduce HCC progression by inactivating Notch signaling in a ligand-independent manner through a disintegrin and metalloproteinase metallopeptidase domain 17 (ADAM17), a proteolytic enzyme that cleaves the Notch receptor, which was corroborated by GPR50 overexpression in hepatocytes. GPR50 silencing also downregulated transcription and translation of ADAM17 through the AKT/specificity protein-1 (SP1) signaling axis. Notably, GPR50 was found to directly interact with ADAM17. Overall, we demonstrate a novel GPR50-mediated regulation of the ADAM17-Notch signaling pathway, which can provide insights into HCC progression and prognosis and development of Notch-based HCC treatment strategies.

Molecular Insights Into Therapeutic Potential of Autophagy Modulation by Natural Products for Cancer Stem Cells

Autophagy, a cellular self-digestion process that is activated in response to stress, has a functional role in tumor formation and progression. Cancer stem cells (CSCs) accounting for a minor proportion of total cancer cells-have distinct self-renewal and differentiation abilities and promote metastasis. Researchers have shown that a numeral number of natural products using traditional experimental methods have been revealed to target CSCs. However, the specific role of autophagy with respect to CSCs and tumorigenesis using natural products are still unknown. Currently, CSCs are considered to be one of the causative reasons underlying the failure of anticancer treatment as a result of tumor recurrence, metastasis, and chemo- or radio-resistance. Autophagy may play a dual role in CSC-related resistance to anticancer treatment; it is responsible for cell fate determination and the targeted degradation of transcription factors via growth arrest. It has been established that autophagy promotes drug resistance, dormancy, and stemness and maintenance of CSCs. Surprisingly, numerous studies have also suggested that autophagy can facilitate the loss of stemness in CSCs. Here, we review current progress in research related to the multifaceted connections between autophagy modulation and CSCs control using natural products. Overall, we emphasize the importance of understanding the role of autophagy in the maintenance of different CSCs and implications of this connection for the development of new strategies for cancer treatment targeting natural products.

Enhanced hepatic differentiation in the subpopulation of human amniotic stem cells under 3D multicellular microenvironment

BACKGROUND

To solve the problem of liver transplantation donor insufficiency, an alternative cell transplantation therapy was investigated. We focused on amniotic epithelial cells (AECs) as a cell source because, unlike induced pluripotent stem cells, they are cost-effective and non-tumorigenic. The utilization of AECs in regenerative medicine, however, is in its infancy. A general profile for AECs has not been comprehensively analyzed. Moreover, no hepatic differentiation protocol for AECs has yet been established. To this end, we independently compiled human AEC libraries, purified amniotic stem cells (ASCs), and co-cultured them with mesenchymal stem cells (MSCs) and human umbilical vein endothelial cell (HUVECs) in a 3D system which induces functional hepatic organoids.

AIM

To characterize AECs and generate functional hepatic organoids from ASCs and other somatic stem cells

METHODS

AECs, MSCs, and HUVECs were isolated from the placentae and umbilical cords of cesarean section patients. Amnion and primary AEC stemness characteristics and heterogeneity were analyzed by immunocytochemistry, Alkaline phosphatase (AP) staining, and flow cytometry. An adherent AEC subpopulation was selected and evaluated for ASC purification quality by a colony formation assay. AEC transcriptomes were compared with those for other hepatocytes cell sources by bioinformatics. The 2D and 3D culture were compared by relative gene expression using several differentiation protocols. ASCs, MSCs, and HUVECs were combined in a 3D co-culture system to generate hepatic organoids whose structure was compared with a 3D AEC sphere and whose function was elucidated by immunofluorescence imaging, periodic acid Schiff, and an indocyanine green (ICG) test.

RESULTS

AECs have certain stemness markers such as EPCAM, SSEA4, and E-cadherin. One AEC subpopulation was also either positive for AP staining or expressed the TRA-1-60 and TRA-1-81 stemness markers. Moreover, it could form colonies and its frequency was enhanced ten-fold in the adherent subpopulation after selective primary passage. Bioinformatics analysis of ribose nucleic acid sequencing revealed that the total AEC gene expression was distant from those of pluripotent stem cells and hepatocytes but some gene expression overlapped among these cells. TJP1, associated with epidermal growth factor receptor, and MET, associated with hepatocyte growth factor receptor, were upregulated and may be important for hepatic differentiation. In conventional flat culture, the cells turned unviable and did not readily differentiate into hepatocytes. In 3D culture, however, hepatic gene expression of the AEC sphere was elevated even under a two-step differentiation protocol. Furthermore, the organoids derived from the MSC and HUVEC co-culture showed 3D structure with polarity, hepatic-like glycogen storage, and ICG absorption/elimination.

CONCLUSION

Human amniotic epithelial cells are heterogeneous and certain subpopulations have high stemness. Under a 3D co-culture system, functional hepatic organoids were generated in a multicellular microenvironment.

Epithelial-mesenchymal plasticity-engaging stemness in an interplay of phenotypes

Cancer is a genetic disease which results in a functional imbalance between tumour-repressive and oncogenic signals. The WHO highlights the burden of this indomitable disease, listing it as the second leading cause of death globally. The major cause of cancer-related death is rarely the effect of the primary tumour itself, but rather, the devastating spread of cancer cells in metastases. Epithelial-mesenchymal plasticity (EMP)-termed as the ability of cells to maintain its plasticity and transit between epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states-plays a fundamental role in cancer metastasis. These cell transitions allow them migrate from the primary tumour and invade the secondary site. EMP is associated with migration, invasion, colonisation, self-renewal and drug resistance. This review briefly elucidates the mechanism of EMP and the association between cancer stem cells (CSCs) and circulating tumour cells (CTCs), biomarkers and signalling pathways involved in EMP as well as drug resistance and therapeutic targeting.

TFAP2A Induced KRT16 as an Oncogene in Lung Adenocarcinoma via EMT

Objectives: keratin 16 (KRT16) is a type I cytokeratin that overexpressed in many kinds of cancers, but unlike other keratins, KRT16 was poorly studied, so the aim of current study was to determine the biological role of KRT16 in lung adenocarcinoma (LUAD).

Materials and Methods: by utilizing open access data, we determined KRT16 expression in LUAD. After that we evaluated the biological role of KRT16 in-vitro and in-vivo. We also explored the reason for KRT16 overexpression. Last, we explored the clinical significance of KRT16 in LUAD.

Results: we found KRT16 is overexpressed in LUAD and positively correlated with lymph node metastasis. Knockdown of KRT16 significantly influenced the LUAD cells' migration, invasion, proliferation and epithelial-mesenchymal transition (EMT). Moreover, TFAP2A could transcriptionally overexpress KRT16, which contributed to the TFAP2A tumorigenicity. Last, we determined that high level of KRT16 predicts poor prognosis of LUAD patients.

Conclusions: our data indicate that, TFAP2A induced KRT16 overexpression promotes tumorigenicity in LUAD via EMT, and KRT16 expression could serve as an independent prognosis marker.

Cell Reprogramming in Tumorigenesis and Its Therapeutic Implications for Breast Cancer

Breast cancer is the most common malignancy in women worldwide and can be categorized into several subtypes according to histopathological parameters or genomic signatures. Such heterogeneity of breast cancer can arise from the reactivation of mammary stem cells in situ during tumorigenesis. Moreover, different breast cancer subtypes exhibit varieties of cancer incidence, therapeutic response, and patient prognosis, suggesting that a specific therapeutic protocol is required for each breast cancer subtype. Recent studies using molecular and cellular assays identified a link between specific genetic/epigenetic alterations and distinct cells of origin of breast cancer subtypes. These alterations include oncogenes, tumor suppressor genes, and cell-lineage determinants, which can induce cell reprogramming (dedifferentiation and transdifferentiation) among two lineage-committed mammary epithelial cells, namely basal and luminal cells. The interconversion of cell states through cell reprogramming into the intermediates of mammary stem cells can give rise to heterogeneous breast cancers that complicate effective therapies of breast cancer. A better understanding of mechanisms underlying cell reprogramming in breast cancer can help in not only elucidating tumorigenesis but also developing therapeutics for breast cancer. This review introduces recent findings on cancer gene-mediated cell reprogramming in breast cancer and discusses the therapeutic potential of targeting cell reprogramming.

Opposing Regulation of Cancer Properties via KRT19-Mediated Differential Modulation of Wnt/β-Catenin/Notch Signaling in Breast and Colon Cancers

Although Keratin 19 (KRT19) has been reported as a tumor cell marker and found to interact with other proteins that modulate cancer properties, its role in cancer prognosis remains to be fully elucidated. We found that KRT19 expression was increased in both colon and breast cancer, but that knockdown of KRT19 showed opposing effects on cancer properties. In colon cancer, KRT19 knockdown resulted in suppression of cancer via downregulation of Wnt/Notch signaling without altering NUMB transcription. In breast cancer, KRT19 knockdown led to an increase in cancer properties because of attenuated Wnt and enhanced Notch signaling. In colon cancer, KRT19 interacted with β-catenin but not with RAC1, allowing the LEF/TCF transcription factor to bind primarily to the LEF1 and TCF7 promoter regions, whereas in breast cancer, KRT19 interacted with the β-catenin/RAC1 complex and led to apparent upregulation of NUMB expression and NUMB-mediated suppression of Notch signaling. These results reveal a novel differential role of KRT19 in carcinogenesis, due to differential modulation of Wnt/β-catenin/Notch signaling crosstalk through various interactions of KRT19 with only β-catenin or with the β-catenin/RAC1 complex, which might have implications for clinical cancer research.