Hair keratin KRT81 is expressed in normal and breast cancer cells and contributes to their invasiveness

The prognostic marker KRT81 is involved in suppressing CD8 + T cells and predicts immunotherapy response for triple-negative breast cancer

Triple-negative breast Cancer (TNBC) is an aggressive subtype lacking estrogen, progesterone, and HER2 receptors. Known for limited targeted therapies, it poses challenges and requires personalized treatment strategies. Differential analysis revealed a significant decrease in keratin 81 (KRT81) expression in non-TNBC samples and an increase in TNBC samples, lower KRT81 expression correlated with better TNBC patient outcomes. It emerged as an independent predictive factor for TNBC, with associations found between its expression and clinically relevant features. We further developed a nomogram for survival probability assessment based on Cox regression results, demonstrating its accuracy through calibration curves. Gene annotation analysis indicated that KRT81 is involved in immune-related pathways and tumor cell adhesion. KRT81 is associated with immune cell infiltration of Follicular helper T cells (Tfh) and CD8 + T cells, suggesting its potential impact on the immunological microenvironment. The study delved into KRT81's predictive value for immunotherapy responses, high expression of KRT81 was associated with greater potential for immune evasion. Single-cell RNA sequencing analysis pinpointed KRT81 expression within a specific malignant subtype which was a risk factor for TNBC. Furthermore, KRT81 promoted TNBC cell proliferation, migration, invasion, and adhesion was confirmed by gene knockout or overexpression assay. Co-culture experiments further indicated KRT81's potential role in inhibiting CD8 + T cells, and correlation analysis implied KRT81 was highly correlated with immune checkpoint CD276, providing insights into its involvement in the immune microenvironment via CD276. In conclusion, this comprehensive study positions KRT81 as a promising prognostic marker for predicting tumor progression and immunotherapy responses in TNBC.

scVAG: Unified single-cell clustering via variational-autoencoder integration with Graph Attention Autoencoder

Single-cell RNA sequencing (scRNA-seq) enables high-resolution transcriptional profiling of cell heterogeneity. However, analyzing this noisy, high-dimensional matrix remains challenging. We present scVAG, an integrated deep learning framework combining Variational-Autoencoder (VAE) and Graph Attention Autoencoder (GATE) for enhanced single-cell clustering. Building upon scGAC, our approach replaces its restrictive linear principal component analysis (PCA) with nonlinear dimensionality reduction better suited for scRNA-seq data. Specifically, we integrate VAE and GATE to enable more flexible latent space encoding. Extensive experiments on 20 datasets demonstrate scVAG's superior performance over previous state-of-the-art methods including scGAC, SCEA, SC3, Seurat, scGNN, scASGC, DESC, NIC, scLDS2, DRJCC, sLMIC, and jSRC. On average, scVAG improves clustering accuracy by 5 percent in ARI and 4 percent in NMI parameters. Visualizations highlight scVAG's capacity to recover interpretable biological structures. Our VAE-GATE pipeline extracts intricate expression patterns into compact representations that precisely delineate cell subpopulations consistent with ground truth labels. Overall, scVAG establishes a robust architecture for elucidating cell taxonomies from noisy transcriptomic inputs.

Single-cell RNA and T-cell receptor sequencing unveil mycosis fungoides heterogeneity and a possible gene signature

Background

Mycosis fungoides (MF) is the most common subtype of cutaneous T-cell lymphoma (CTCL). Comprehensive analysis of MF cells in situ and ex vivo is complicated by the fact that is challenging to distinguish malignant from reactive T cells with certainty.

Methods

To overcome this limitation, we performed combined single-cell RNA (scRNAseq) and T-cell receptor TCR sequencing (scTCRseq) of skin lesions of cutaneous MF lesions from 12 patients. A sufficient quantity of living T cells was obtained from 9 patients, but 2 had to be excluded due to unclear diagnoses (coexisting CLL or revision to a fixed toxic drug eruption).

Results

From the remaining patients we established single-cell mRNA expression profiles and the corresponding TCR repertoire of 18,630 T cells. TCR clonality unequivocally identified 13,592 malignant T cells. Reactive T cells of all patients clustered together, while malignant cells of each patient formed a unique cluster expressing genes typical of naive/memory, such as CD27, CCR7 and IL7R, or cytotoxic T cells, e.g., GZMA, NKG7 and GNLY. Genes encoding classic CTCL markers were not detected in all clusters, consistent with the fact that mRNA expression does not correlate linearly with protein expression. Nevertheless, we successfully pinpointed distinctive gene signatures differentiating reactive malignant from malignant T cells: keratins (KRT81, KRT86), galectins (LGALS1, LGALS3) and S100 genes (S100A4, S100A6) being overexpressed in malignant cells.

Conclusions

Combined scRNAseq and scTCRseq not only allows unambiguous identification of MF cells, but also revealed marked heterogeneity between and within patients with unexpected functional phenotypes. While the correlation between mRNA and protein abundance was limited with respect to established MF markers, we were able to identify a single-cell gene expression signature that distinguishes malignant from reactive T cells.

KRT81 and HNF1A expression in pancreatic ductal adenocarcinoma: investigation of predictive and prognostic value of immunohistochemistry-based subtyping

Even after decades of research, pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal disease and responses to conventional treatments remain mostly poor. Subclassification of PDAC into distinct biological subtypes has been proposed by various groups to further improve patient outcome and reduce unnecessary side effects. Recently, an immunohistochemistry (IHC)-based subtyping method using cytokeratin-81 (KRT81) and hepatocyte nuclear factor 1A (HNF1A) could recapitulate some of the previously established molecular subtyping methods, while providing significant prognostic and, to a limited degree, also predictive information. We refined the KRT81/HNF1A subtyping method to classify PDAC into three distinct biological subtypes. The prognostic value of the IHC-based method was investigated in two primary resected cohorts, which include 269 and 286 patients, respectively. In the second cohort, we also assessed the predictive effect for response to erlotinib + gemcitabine. In both PDAC cohorts, the new HNF1A-positive subtype was associated with the best survival, the KRT81-positive subtype with the worst, and the double-negative with an intermediate survival (p < 0.001 and p < 0.001, respectively) in univariate and multivariate analyses. In the second cohort (CONKO-005), the IHC-based subtype was additionally found to have a potential predictive value for the erlotinib-based treatment effect. The revised IHC-based subtyping using KRT81 and HNF1A has prognostic significance for PDAC patients and may be of value in predicting treatment response to specific therapeutic agents.

Integrative single-cell analysis of LUAD: elucidating immune cell dynamics and prognostic modeling based on exhausted CD8+ T cells

Background

The tumor microenvironment (TME) plays a pivotal role in the progression and metastasis of lung adenocarcinoma (LUAD). However, the detailed characteristics of LUAD and its associated microenvironment are yet to be extensively explored. This study aims to delineate a comprehensive profile of the immune cells within the LUAD microenvironment, including CD8+ T cells, CD4+ T cells, and myeloid cells. Subsequently, based on marker genes of exhausted CD8+ T cells, we aim to establish a prognostic model for LUAD.

Method

Utilizing the Seurat and Scanpy packages, we successfully constructed an immune microenvironment atlas for LUAD. The Monocle3 and PAGA algorithms were employed for pseudotime analysis, pySCENIC for transcription factor analysis, and CellChat for analyzing intercellular communication. Following this, a prognostic model for LUAD was developed, based on the marker genes of exhausted CD8+ T cells, enabling effective risk stratification in LUAD patients. Our study included a thorough analysis to identify differences in TME, mutation landscape, and enrichment across varying risk groups. Moreover, by integrating risk scores with clinical features, we developed a new nomogram. The expression of model genes was validated via RT-PCR, and a series of cellular experiments were conducted, elucidating the potential oncogenic mechanisms of GALNT2.

Results

Our study developed a single-cell atlas for LUAD from scRNA-seq data of 19 patients, examining crucial immune cells in LUAD's microenvironment. We underscored pDCs' role in antigen processing and established a Cox regression model based on CD8_Tex-LAYN genes for risk assessment. Additionally, we contrasted prognosis and tumor environments across risk groups, constructed a new nomogram integrating clinical features, validated the expression of model genes via RT-PCR, and confirmed GALNT2's function in LUAD through cellular experiments, thereby enhancing our understanding and approach to LUAD treatment.

Conclusion

The creation of a LUAD single-cell atlas in our study offered new insights into its tumor microenvironment and immune cell interactions, highlighting the importance of key genes associated with exhausted CD8+ T cells. These discoveries have enabled the development of an effective prognostic model for LUAD and identified GALNT2 as a potential therapeutic target, significantly contributing to the improvement of LUAD diagnosis and treatment strategies.

Ectopic Expression of a Truncated Isoform of Hair Keratin 81 in Breast Cancer Alters Biophysical Characteristics to Promote Metastatic Propensity

Keratins are an integral part of cell structure and function. Here, it is shown that ectopic expression of a truncated isoform of keratin 81 (tKRT81) in breast cancer is upregulated in metastatic lesions compared to primary tumors and patient-derived circulating tumor cells, and is associated with more aggressive subtypes. tKRT81 physically interacts with keratin 18 (KRT18) and leads to changes in the cytosolic keratin intermediate filament network and desmosomal plaque formation. These structural changes are associated with a softer, more elastically deformable cancer cell with enhanced adhesion and clustering ability leading to greater in vivo lung metastatic burden. This work describes a novel biomechanical mechanism by which tKRT81 promotes metastasis, highlighting the importance of the biophysical characteristics of tumor cells.

MAPK1 promotes the metastasis and invasion of gastric cancer as a bidirectional transcription factor

BACKGROUND

The Mitogen-activated protein kinase 1 (MAPK1) has both independent functions of phosphorylating histones as a kinase and directly binding the promoter regions of genes to regulate gene expression as a transcription factor. Previous studies have identified elevated expression of MAPK1 in human gastric cancer, which is associated with its role as a kinase, facilitating the migration and invasion of gastric cancer cells. However, how MAPK1 binds to its target genes as a transcription factor and whether it modulates related gene expressions in gastric cancer remains unclear.

RESULTS

Here, we integrated biochemical assays (protein interactions and chromatin immunoprecipitation (ChIP)), cellular analysis assays (cell proliferation and migration), RNA sequencing, ChIP sequencing, and clinical analysis to investigate the potential genomic recognition patterns of MAPK1 in a human gastric adenocarcinoma cell-line (AGS) and to uncover its regulatory effect on gastric cancer progression. We confirmed that MAPK1 promotes AGS cells invasion and migration by regulating the target genes in different directions, up-regulating seven target genes (KRT13, KRT6A, KRT81, MYH15, STARD4, SYTL4, and TMEM267) and down-regulating one gene (FGG). Among them, five genes (FGG, MYH15, STARD4, SYTL4, and TMEM267) were first associated with cancer procession, while the other three (KRT81, KRT6A, and KRT13) have previously been confirmed to be related to cancer metastasis and migration.

CONCLUSION

Our data showed that MAPK1 can bind to the promoter regions of these target genes to control their transcription as a bidirectional transcription factor, promoting AGS cell motility and invasion. Our research has expanded the understanding of the regulatory roles of MAPK1, enriched our knowledge of transcription factors, and provided novel candidates for cancer therapeutics.

Single-cell data analysis of malignant epithelial cell heterogeneity in lung adenocarcinoma for patient classification and prognosis prediction

Lung cancer is one of the leading causes of cancer-related death. Most advanced lung adenocarcinoma (LUAD) patients have poor survival because of drug resistance and relapse. Neglecting intratumoral heterogeneity might be one of the reasons for treatment insensitivity, while single-cell RNA sequencing (scRNA-seq) technologies can provide transcriptome information at the single-cell level. Herein, we combined scRNA-seq and bulk RNA-seq data of LUAD and identified a novel cluster of malignant epithelial cells - KRT81+ malignant epithelial cells - associated with worse prognoses. Further analysis revealed that the hypoxia and EMT pathways of these cells were activated to predispose them to differentiate into metastatic lung adenocarcinoma cells. Finally, we also studied the role of these tumor cells in the immune microenvironment and their role in the classification and prognosis prediction of lung adenocarcinoma patients.

In Silico Bioinformatics Analysis on the Role of Long Non-Coding RNAs as Drivers and Gatekeepers of Androgen-Independent Prostate Cancer Using LNCaP and PC-3 Cells

Prostate cancer (PCa) is the leading cancer in men globally. The association between PCa and long non-coding RNAs (lncRNAs) has been reported. Aberrantly expressed lncRNAs have been documented in each of the cancer "hallmarks". Androgen signaling plays an important role in PCa progression. This study aimed to profile the aberrantly expressed lncRNAs in androgen-dependent (LNCaP) PCa compared to androgen-independent (PC-3) PCa cells. This was achieved by using a 384-well plate of PCa lncRNA gene panel. Differential expression of ±2 up or downregulation was determined using the CFX Maestro software v2.1. LncSEA and DIANA-miRPath were used to identify the enriched pathways. Telomerase RNA component (TERC) lncRNA was illustrated to participate in various tumourigenic classes by in silico bioinformatics analysis and was thus selected for validation using RT-qPCR. Further bioinformatics analysis revealed the involvement of differentially expressed lncRNAs in oncogenic pathways. Some lncRNAs undergo hypermethylation, others are encapsulated by exosomes, while others interact with several microRNAs (miRNAs), favouring tumourigenic pathways. Notably, TERC lncRNA was shown to interact with tumour-suppressor miRNAs hsa-miR-4429 and hsa-miR-320b. This interaction in turn activates TGF-β-signaling and ECM-receptor interaction pathways, favouring the progression of PCa. Understanding lncRNAs as competitive endogenous RNA molecules and their interactions with miRNAs may aid in the identification of novel prognostic PCa biomarkers and therapeutic targets.

HOXA1, a breast cancer oncogene

More than 25 years ago, the first literature records mentioned HOXA1 expression in human breast cancer. A few years later, HOXA1 was confirmed as a proper oncogene in mammary tissue. In the following two decades, molecular data about the mode of action of the HOXA1 protein, the factors contributing to activate and maintain HOXA1 gene expression and the identity of its target genes have accumulated and provide a wider view on the association of this transcription factor to breast oncogenesis. Large-scale transcriptomic data gathered from wide cohorts of patients further allowed refining the relationship between breast cancer type and HOXA1 expression. Several recent reports have reviewed the connection between cancer hallmarks and the biology of HOX genes in general. Here we take HOXA1 as a paradigm and propose an extensive overview of the molecular data centered on this oncoprotein, from what its expression modulators, to the interactors contributing to its oncogenic activities, and to the pathways and genes it controls. The data converge to an intricate picture that answers questions on the multi-modality of its oncogene activities, point towards better understanding of breast cancer aetiology and thereby provides an appraisal for treatment opportunities.

Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes

Background

Integrin β (ITGB) superfamily plays an essential role in the intercellular connection and signal transmission. It was exhibited that overexpressing of ITGB family members promotes the malignant progression of lung adenocarcinoma (LUAD), but the relationship between ITGB superfamily and the LUAD prognosis remains unclear.

Methods

In this study, the samples were assigned to different subgroups utilizing non‐negative matrix factorization clustering according to the expression of ITGB family members in LUAD. Kaplan–Meier (K‐M) survival analysis revealed the significant differences in the prognosis between different ITGB subgroups. Subsequently, we screened differentially expressed genes among different subgroups and conducted univariate Cox analysis, random forest feature selection, and multivariate Cox analysis. 9‐feature genes (FAM83A, AKAP12, PKP2, CYP17A1, GJB3, TMPRSS11F, KRT81, MARCH4, and STC1) in the ITGB superfamily were selected to establish a prognostic assessment model for LAUD.

Results

In accordance with the median risk score, LUAD samples were divided into high‐ and low‐risk groups. The receiver operating characteristic (ROC) curve of LUAD patients’ survival was predicted via K‐M survival curve and principal component analysis dimensionality reduction. This model was found to have a favorable performance in LUAD prognostic assessment. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed genes between groups and Gene Set Enrichment Analysis (GSEA) of intergroup samples confirmed that the high‐ and low‐risk groups had evident differences mainly in the function of extracellular matrix (ECM) interaction. Risk score and univariate and multivariate Cox regression analyses of clinical factors showed that the prognostic model could be applied as an independent prognostic factor for LUAD. Then, we draw the nomogram of 1‐, 3‐, and 5‐year survival of LUAD patients predicted with the risk score and clinical factors. Calibration curve and clinical decision curve proved the favorable predictive ability of nomogram.

Conclusion

We constructed a LUAD prognostic risk model based on the ITGB superfamily, which can provide guidance for clinicians on their prognostic judgment.

MoGCN: A Multi-Omics Integration Method Based on Graph Convolutional Network for Cancer Subtype Analysis

In light of the rapid accumulation of large-scale omics datasets, numerous studies have attempted to characterize the molecular and clinical features of cancers from a multi-omics perspective. However, there are great challenges in integrating multi-omics using machine learning methods for cancer subtype classification. In this study, MoGCN, a multi-omics integration model based on graph convolutional network (GCN) was developed for cancer subtype classification and analysis. Genomics, transcriptomics and proteomics datasets for 511 breast invasive carcinoma (BRCA) samples were downloaded from the Cancer Genome Atlas (TCGA). The autoencoder (AE) and the similarity network fusion (SNF) methods were used to reduce dimensionality and construct the patient similarity network (PSN), respectively. Then the vector features and the PSN were input into the GCN for training and testing. Feature extraction and network visualization were used for further biological knowledge discovery and subtype classification. In the analysis of multi-dimensional omics data of the BRCA samples in TCGA, MoGCN achieved the highest accuracy in cancer subtype classification compared with several popular algorithms. Moreover, MoGCN can extract the most significant features of each omics layer and provide candidate functional molecules for further analysis of their biological effects. And network visualization showed that MoGCN could make clinically intuitive diagnosis. The generality of MoGCN was proven on the TCGA pan-kidney cancer datasets. MoGCN and datasets are public available at https://github.com/Lifoof/MoGCN. Our study shows that MoGCN performs well for heterogeneous data integration and the interpretability of classification results, which confers great potential for applications in biomarker identification and clinical diagnosis.

Dicer Enhances Bevacizumab-Related Inhibition of Hepatocellular Carcinoma via Blocking the Vascular Endothelial Growth Factor Pathway

Purpose

Vascular endothelial growth factor (VEGF) family members contribute greatly to the development and angiogenesis of hypervascular hepatocellular carcinoma (HCC). We have previously shown that Dicer inhibited HCC growth. In this study, we aimed to determine the relationship between Dicer and VEGF in HCC.

Methods

Gain-of-function studies were performed to determine the effect of different treatments on the proliferation, migration, and invasion of HCC cells. Expression of VEGF-A in xenograft tumor tissues was analysed using Western blotting, and that of CD31 using immunohistochemical analysis.

Results

We found that Dicer inhibited proliferation, migration and invasion of HCC cells by suppressing VEGF-A expression. Interestingly, VEGF-A165, which is the most prominent VEGF-A isoform, counteracted Dicer-induced inhibition of HCC cells. In addition, a monoclonal anti-VEGF antibody (bevacizumab) enhanced Dicer-induced inhibition of HCC in vitro and in vivo. Further, immunohistochemical analysis of CD31 indicated bevacizumab and Dicer synergized to reduce tumor microvessel density.

Conclusion

Our data demonstrated that Dicer enhanced bevacizumab-related inhibition of HCC cell via the VEGF pathway; therefore, Dicer in coordination with bevacizumab may provide another potential approach for HCC therapy.

Comprehensive Transcriptome and Pathway Analyses Revealed Central Role for Fascin in Promoting Triple-Negative Breast Cancer Progression

Recent years have witnessed major progress in development of novel therapeutic agents such as chemotherapy, targeted therapy and immune checkpoint inhibitors for breast cancer. However, cancer-related death remains high especially in triple-negative breast cancer (TNBC) due limited therapeutic options. Development of targeted therapies for TNBC requires better understanding of biology and signaling networks that promote disease progression. Fascin, an actin bundling protein, was identified as a key regulator of many signaling pathways that contribute to breast cancer progression. Herein, fascin ShRNA was used to generate stable fascin knockdown (FSCN1^KD) in the MDA-MB-231 TNBC cell line and then were subjected to comprehensive mRNA and miRNA transcriptome analysis. We identified 129 upregulated and 114 downregulated mRNA transcripts, while 14 miRNAs were differentially expressed in FSCN1^KD. Ingenuity pathway analysis (IPA) was used to predict the impact of differentially expressed transcripts on signaling pathways and functional categories and to construct miRNA-mRNA regulatory networks in the context of FSCN1 knockdown. Compared to FSCN1^KD, fascin-positive (FSCN1^CON) breast cancer cells showed enrichment in genes promoting cellular proliferation, migration, survival, DNA replication and repair. Expression of FSCN1^high (identified in BRCA dataset from TCGA) in conjunction with elevated expression of the top 10 upregulated or decreased expression of the top 10 downregulated genes (identified in our FSCN1^CON vs. FSCN1^KD) correlates with worst survival outcome. Taken together, these data confirmed fascin's role in promoting TNBC progression, and identified a novel opportunity for therapeutic interventions via targeting those FSCN1-related transcripts.

Pharmacology, Toxicology, and Metabolism of Sennoside A, A Medicinal Plant-Derived Natural Compound

Sennoside A (SA) is a natural dianthrone glycoside mainly from medicinal plants of Senna and Rhubarb, and used as a folk traditional irritant laxative and slimming health food. Accumulating evidences suggest that SA possesses numerous pharmacological properties, such as laxative, anti-obesity, hypoglycemic, hepatoprotective, anti-fibrotic, anti-inflammatory, anti-tumor, anti-bacterial, anti-fungal, anti-viral, and anti-neurodegenerative activities. These pharmacological effects lay the foundation for its potential application in treating a variety of diseases. However, numerous published studies suggest that a long-term use of SA in large doses may have some adverse effects, including the occurrence of melanosis coli and carcinogenesis of colon cancer, thereby limiting its clinical use. It remains to be established whether SA or its metabolites are responsible for the pharmacological and toxicity effects. In this review, the latest advances in the pharmacology, toxicology, and metabolism of SA were summarizedbased on its biological characteristics and mechanism.

KRT81 Knockdown Inhibits Malignant Progression of Melanoma Through Regulating Interleukin-8

KRT81 is involved in carcinogenesis and progression of many types of human cancers. However, little is known about the role of KRT81 in melanoma. In this study, we identified that KRT81 expression is upregulated in melanoma tissues compared with corresponding adjacent nontumor tissues. Overexpression of KRT81 was also found in human melanoma cell lines. Cell functional studies have shown that KRT81 knockdown could inhibit proliferation, colony formation, migration, invasion, and promote apoptosis of A375 cells. Consistently, in vivo tumorigenesis experiments showed that KRT81 knockdown significantly suppressed the growth of xenograft tumors. Moreover, KRT81 knockdown increased the chemosensitivity of A375 cells to DDP. Mechanical exploration revealed that KRT81 knockdown mediated the downregulation of inflammatory cytokine interleukin-8 (IL-8). In conclusion, these findings indicate that downregulation of KRT81 could inhibit progression of melanoma by regulating IL-8. Therefore, KRT81 represents a potential therapeutic target for melanoma therapy.

In-Silico Analysis of Differentially Expressed Genes and Their Regulating microRNA Involved in Lymph Node Metastasis in Invasive Breast Carcinoma

Axillary nodal metastasis is related to poor prognosis in breast cancer (BC). Key candidate genes in BC lymph node metastasis have been identified from Gene Expression Omnibus datasets and explored through functional enrichment database for annotation, visualization and integrated discovery (DAVID) , protein-protein interaction by Search Tool for the Retrieval of Interacting Genes and proteins (STRING), network visualization (Cytoscape), survival analysis (GEPIA, KM Plotter), and target prediction (miRNet). A total of 102 overlapping differentially expressed genes were found. In-silico survival and expression analyses revealed six candidate hub genes, Desmocollin 3 (DSC3), KRT5, KRT6B, KRT17, KRT81, and SERPINB5, to be significantly associated with nodal metastasis and overall survival, and 83 MicroRNA (miRNAs), which may be potential diagnostic markers and therapeutic targets in BC patients.

Combined tumor epithelial and stromal histopathology with keratin 81 expression predicts prognosis for pancreatic ductal adenocarcinoma

BACKGROUND

Development of a pragmatic pathologic classifier of pancreatic ductal adenocarcinoma (PDAC) that reflects biological behavior is needed.

METHODS

The tumor epithelial and stromal features of PDAC and molecular subtype-related markers were evaluated in three independent cohorts.

RESULTS

In the non-neoadjuvant therapy cohort (n = 108), regarding tumor-epithelial feature, non-gland-forming type showed worse prognosis compared to gland-forming type (P < .001). For tumor-stromal feature, in gland-forming type, the prognosis was good in order of inactivated stroma-rich, stroma-poor, and activated stroma-rich (P = .027). Whereas, non-gland-forming type revealed no difference of prognosis according to tumor stroma. Of molecular subtype-related markers, keratin 81 expression was correlated with non-gland-forming type and poor prognosis (P = .005 and P = .021, respectively). Other markers (HNF1A, c-MET, and p53) showed no significant differences in prognosis. In the neoadjuvant therapy cohort (n = 68), non-gland-forming type was correlated with high residual tumor volume (≥20%) (P < .001) and gland-forming/stroma-poor type was not present. In the next-generation sequencing cohort (n = 55), non-gland-forming type was correlated with a higher number of the KRAS, TP53, CDKN2A, and SMAD4 mutations (P = .038).

CONCLUSION

Combined tumor epithelial and stromal histopathology with keratin 81 expression is suggested to be useful for predicting prognosis of PDAC.

Transcriptome Analysis of the Inhibitory Effect of Sennoside A on the Metastasis of Hepatocellular Carcinoma Cells

Sennoside A (SA) is a bioactive component of Rheum officinale Baill. with an activity of irritant laxative, which has been reported to possess therapeutic potential in various diseases or conditions including obesity, insulin resistance, liver steatosis, prostate cancer and pancreatic cancer progression. However, whether SA has therapeutic potential in hepatocellular carcinoma (HCC) treatment remains elusive. In this study, we treated two HCC cell lines, HepG2 and SMMC-7721 with SA and found that SA selectively inhibited the growth of HCC cells by proliferation assay. SA has a good inhibitory effect on proliferation of HepG2 cells in a concentration dependent manner, but there was no effect on SMMC-7721 cells. Then we conducted transwell assays and transcriptome analysis in HCC cells and examined the effects of SA on HCC in vivo. The results showed that SA significantly inhibited the migration and invasion of HCC. Comparison of RNA-seq transcriptome profiles from control groups and SA-treated groups identified 171 and 264 differentially expressed genes (DEGs) in HepG2 and SMMC-7721 cells respectively, in which includes 2 overlapping up-regulated DEGs and 12 overlapping down-regulated DEGs between HepG2 and SMMC-7721 cells. The qPCR were applied to investigate the transcriptional level of 9 overlapping down-regulated DEGs related to cancer metastasis, and the results were consistent with RNA-seq data. The dominate pathways including Wnt signaling pathway, TNF signaling pathway, VEGF signaling pathway, and NF-κB signaling pathway were strongly inhibited by SA, which are involved in regulating cancer metastasis. Finally, we confirmed that the downregulation of KRT7 and KRT81 could inhibit HCC metastasis. This study has provided new insight into the understanding of the inhibitory effects and potential targets of SA on the metastasis of HCC.

A Polymorphism at the microRNA Binding Site in the 3' Untranslated Region of KRT81 Is Associated with Breast Cancer

Single nucleotide polymorphisms in miRNA binding sites (miR-SNPs) are associated with cancer risk. We assessed the relationship between five miR-SNPs in the 3' untranslated region (3'-UTR) of RYR3 (rs1044129), KIAA0423 (rs1053667), C14orf101 (rs4901706), GOLGA7 (rs11337), and KRT81 (rs3660) and the risk of breast cancer (BC). The CC genotype of rs3660 located in the 3'-UTR of KRT81 was identified for its association with lower BC risk (odds ratio, 0.093; 95% confidence interval, 0.045-0.193; p = 0.000). Immunnochemical analysis and Renilla luciferase reporter assays indicated that the CC genotype of KRT81 was associated with lower expression of KRT81 (p < 0.05). The subsequently functional analysis showed that knockdown the KRT81 could inhibit proliferation and promote apoptosis of the MDA-MB-231 BC cells (p < 0.05) with monocyte chemotactic protein-1 (MCP-1) deregulation. Meanwhile, KRT81 overexpression could promote the proliferation and inhibit the apoptosis of MCF-7 BC cells (p < 0.05). Our data demonstrated that the KRT81 expressional change modulated by rs3660 miR-SNP could modify the carcinogenesis of BC, thereby KRT81 would be a new target for BC treatment.

Metalloproteomics analysis in human mammary cell lines treated with inorganic mercury

The interest in inorganic Hg toxicity and carcinogenicity has been pointed to target organs such as kidney, brain or placenta, but only a few studies have focused on the mammary gland. In this work, analytical combination techniques (SDS-PAGE followed by CV-AFS, and nanoUPLC-ESI-MS/MS) were used to determine proteins that could bind Hg in three human mammary cell lines. Two of them were tumorigenic (MCF-7 and MDA-MB-231) and the other one was the non-tumorigenic cell line (MCF-10A). There are no studies that provide this kind of information in breast cell lines with IHg treatment. Previously, we described the viability, uptake and the subcellular distribution of Hg in human breast cells and analysis of RNA-seq about the genes that encode proteins which are related to cytotoxicity of Hg. This work provides important protein candidates for further studies of Hg toxicity in the mammary gland, thus expanding our understanding of how environmental contaminants might affect tumor progression and contribute with future therapeutic methods.

High expression of keratin 6C is associated with poor prognosis and accelerates cancer proliferation and migration by modulating epithelial-mesenchymal transition in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a more frequent subtype of lung cancer and most cases are discovered in the late stages. The proliferation and metastasis of LUAD are pivotal for disease progression. Despite unremitting deeper understanding of LUAD biology, the mechanisms involved in the proliferation and metastasis of LUAD remain unclear. The objective of our article was to inquiry the expression and the function of keratin 6C (KRT6C) in LUAD cells.

METHODS

First, the expression level and prognostic value of KRT6C in LUAD tissues were analyzed on the basis of the data acquired from TCGA database. Through qRT-PCR, the expression level of KRT6C on LUAD cell lines (A549, H1299, PC-9) and human normal lung cell line MRC-5 was tested. After that, CCK8 and colony formation assays was utilized to detect cell proliferation. In addition, to explore the influence of KRT6C on LUAD migration and invasion ability, scratch wound healing and transwell assays were utilized. Through western blotting, the protein expression levels of KRT6C, PCNA, E-cadherin, N-cadherin, Snail and Vimentin were detected.

RESULTS

The outcomes revealed that KRT6C was highly expressed in LUAD tissues and cell lines. Besides, elevated level of KRT6C was related to worse prognosis in LUAD patients. Ablation of KRT6C restrained proliferation, migration and invasion of A549 cells. KRT6C deficiency augmented the expression of E-cadherin as well as reduced the expression of N-cadherin, Snail and Vimentin.

CONCLUSION

Above all, these consequences indicated that depletion of KRT6C suppressed A549 cell proliferation, migration and invasion, which might be achieved by regulating EMT. In general, KRT6C is identified as a potential therapeutic target for LUAD.