Actin-Associated Gene Expression is Associated with Early Regional Metastasis of Tongue Cancer

Patterns of metastatic progression and association with clinical outcomes in canine osteosarcoma: A necropsy study of 83 dogs

Osteosarcoma is a highly metastatic primary bone tumour that occurs spontaneously in both pet dogs and humans. Patterns of metastasis to organs beyond the most common site (lung) are poorly characterised and it is unknown whether specific associations between patterns of metastatic progression and patient features exist. This retrospective study characterised the necropsy findings of 83 dogs receiving standardised therapy and clinical monitoring in a prospective clinical trial setting to document patterns of metastasis and correlate outcomes with these patterns and other patient and tumour-specific factors. A total of 20 different sites of metastasis were documented, with lung as the most common site, followed by bone, kidney, liver, and heart. Two distinct clusters of dogs were identified based on patterns of metastasis. There was no significant association between site of enrollment, trial arm, sex, serum alkaline phosphatase (ALP) activity, or tumour location and clinical outcomes. A second cancer type was identified at necropsy in 10 dogs (10/83; 12%). These data showcase the extensive nature of osteosarcoma metastasis beyond the lung and provide a benchmark for clinical monitoring of the disease. Further, this study provides insight into transcriptional features of primary tumours that may relate to a propensity for osteosarcoma metastasis to specific organs and tissues.

Proteomics analysis of human breast milk by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) coupled with mass spectrometry to assess breast cancer risk

Breast cancer (BC) is one of the most common cancers and one of the most common causes for cancer-related mortality. Discovery of protein biomarkers associated with cancer is considered important for early diagnosis and prediction of the cancer risk. Protein biomarkers could be investigated by large-scale protein investigation or proteomics, using mass spectrometry (MS)-based techniques. Our group applies MS-based proteomics to study the protein pattern in human breast milk from women with BC and controls and investigates the alterations and dysregulations of breast milk proteins in comparison pairs of BC versus control. These dysregulated proteins might be considered potential future biomarkers of BC. Identification of potential biomarkers in breast milk may benefit young women without BC, but who could collect the milk for future assessment of BC risk. Previously we identified several dysregulated proteins in different sets of human breast milk samples from BC patients and controls using gel-based protein separation coupled with MS. Here, we performed 2D-PAGE coupled with nano-liquid chromatography-tandem MS (nanoLC-MS/MS) in a small-scale study on a set of six human breast milk pairs (three BC samples vs. three controls) and we identified several dysregulated proteins that have potential roles in cancer progression and might be considered potential BC biomarkers in the future.

Establishment of a Machine Learning Model for the Risk Assessment of Perineural Invasion in Head and Neck Squamous Cell Carcinoma

Perineural invasion is a prevalent pathological finding in head and neck squamous cell carcinoma and a risk factor for unfavorable survival. An adequate diagnosis of perineural invasion by pathologic examination is limited due to the availability of tumor samples from surgical resection, which can arise in cases of definitive nonsurgical treatment. To address this medical need, we established a random forest prediction model for the risk assessment of perineural invasion, including occult perineural invasion, and characterized distinct cellular and molecular features based on our new and extended classification. RNA sequencing data of head and neck squamous cell carcinoma from The Cancer Genome Atlas were used as a training cohort to identify differentially expressed genes that are associated with perineural invasion. A random forest classification model was established based on these differentially expressed genes and was validated by inspection of H&E-stained whole image slides. Differences in epigenetic regulation and the mutational landscape were detected by an integrative analysis of multiomics data and single-cell RNA-sequencing data were analyzed. We identified a 44-gene expression signature related to perineural invasion and enriched for genes mainly expressed in cancer cells according to single-cell RNA-sequencing data. A machine learning model was trained based on the expression pattern of the 44-gene set with the unique feature to predict occult perineural invasion. This extended classification model enabled a more accurate analysis of alterations in the mutational landscape and epigenetic regulation by DNA methylation as well as quantitative and qualitative differences in the cellular composition in the tumor microenvironment between head and neck squamous cell carcinoma with or without perineural invasion. In conclusion, the newly established model could not only complement histopathologic examination as an additional diagnostic tool but also guide the identification of new drug targets for therapeutic intervention in future clinical trials with head and neck squamous cell carcinoma patients at a higher risk for treatment failure due to perineural invasion.

Tissue proteome analysis for profiling proteins associated with lymph node metastasis in gallbladder cancer

Lymph node (LN) metastasis is the earliest sign of metastatic spread and an established predictor of poor outcome in gallbladder cancer (GBC). Patients with LN positive GBC have a significantly worse survival (median survival- 7 months) than patients with LN negative disease (median survival- ~ 23 months) in spite of standard treatment which includes extended surgery followed by chemotherapy, radiotherapy and targeted therapy. This study aims at understanding the underlying molecular processes associated with LN metastasis in GBC. Here, we used iTRAQ-based quantitative proteomic analysis using tissue cohort comprising of primary tumor of LN negative GBC (n = 3), LN positive GBC (n = 4) and non-tumor controls (Gallstone disease, n = 4), to identify proteins associated with LN metastasis. A total of 58 differentially expressed proteins (DEPs) were found to be specifically associated with LN positive GBC based on the criteria of p value ≤ 0.05, fold change ≥ 2 and unique peptides ≥ 2. These include the cytoskeleton and associated proteins such as keratin, type II cytoskeletal 7 (KRT7), keratin type I cytoskeletal 19 (KRT19), vimentin (VIM), sorcin (SRI) and nuclear proteins such as nucleophosmin Isoform 1 (NPM1), heterogeneous nuclear ribonucleoproteins A2/B1 isoform X1 (HNRNPA2B1). Some of them are reported to be involved in promoting cell invasion and metastasis. Bioinformatic analysis of the deregulated proteins in LN positive GBC using STRING database identified 'neutrophil degranulation' and 'HIF1 activation' to be among the top deregulated pathways. Western blot and IHC analysis showed a significant overexpression of KRT7 and SRI in LN positive GBC in comparison to LN negative GBC. KRT7, SRI and other proteins may be further explored for their diagnostics and therapeutic applications in LN positive GBC.

Exposure to dietary fatty acids oleic and palmitic acid alters structure and mechanotransduction of intestinal cells in vitro

Intestinal cells are continuously exposed to food constituents while adapting to peristaltic movement and fluid shear stress. Oleic acid (OA) and palmitic acid (PA) are among the most prevalent fatty acids with respect to dietary lipids. Despite the central importance of dietary lipids for a balanced diet, awareness about potential detrimental effects related to excessive consumption is increasing; this includes toxicity, metabolic deregulation, and, particularly for cancer cells, a benefit from the uptake of fatty acids related to promotion of metastasis. Expanding on this, we started elucidating the effects of OA and PA (25-500 µM) on non-transformed human intestinal epithelial cells (HCEC-1CT) in comparison to colon carcinoma cells (HCT116), with regard to the mechanosensory apparatus. Hence, intestinal cells' motility is on the one side essential to ensure adaption to peristaltic movement and barrier function, but also to enable metastatic progression. Incubation with both OA and PA (≥ 25 µM) significantly decreased membrane fluidity of HCT116 cells, whereas the effect on HCEC-1CT was more limited. Application of rhodamine-labelled PA demonstrated that the fatty acid is incorporated into the plasma membrane of HCT116, which could not be observed in the non-tumorigenic cell line. Down-streaming into the intracellular compartment, a pronounced rearrangement of actin cytoskeleton was evident in both cell lines (OA and PA; 25 and 100 µM). This was accompanied by a variation of translocation efficiency of the mechanosensitive co-transcription factor YAP1, albeit with a stronger effect seen for PA and the cancer cells. Untargeted proteomic analysis confirmed that exposure to OA and PA could alter the response capacity of HCT116 cells to fluid shear stress. Taken together, OA and PA were able to functionally modulate the mechanosensory apparatus of intestinal cells, implying a novel role for dietary fatty acids in the regulation of intestinal pathophysiology.

Signatures and prognostic values of related immune targets in tongue cancer

Background

Tongue cancer, as one of the most malignant oral cancers, is highly invasive and has a high risk of recurrence. At present, tongue cancer is not obvious and easy to miss the opportunity for early diagnosis when in the advanced stage. It is important to find markers that can predict the occurrence and progression of tongue cancer.

Methods

Bioinformatics analysis plays an important role in the acquisition of marker genes. GEO and TCGA data are very important public databases. In addition to expression data, the TCGA database also contains corresponding clinical data. In this study, we screened three GEO data sets that met the standard, which included GSE13601, GSE34105, and GSE34106. These data sets were combined using the SVA package to prepare the data for differential expression analysis, and then the limma package was used to set the standard to p < 0.05 and |log2 (FC)| ≥ 1.5.

Results

A total of 170 differentially expressed genes (DEGs) were identified. In addition, the DEseq package was used for differential expression analysis using the same criteria for samples in the TCGA database. It ended up with 1,589 DEGs (644 upregulated, 945 downregulated). By merging these two sets of DEGs, 5 common upregulated DEGs (CCL20, SCG5, SPP1, KRT75, and FOLR3) and 15 common downregulated DEGs were obtained.

Conclusions

Further functional analysis of the DEGs showed that CCL20, SCG5, and SPP1 are closely related to prognosis and may be a therapeutic target of TSCC.

Differential proteomic expression in indolent versus transforming oral lichen planus

Oral lichen planus (OLP) confers an approximately 1% risk of transformation to oral squamous cell carcinoma (OSCC). Early identification of high-risk OLP would be very helpful for optimal patient management. We aimed to discover specific tissue-based protein biomarkers in patients with OLP who developed OSCC compared to those who did not. We used laser capture microdissection- and nanoLC-tandem mass spectrometry to assess protein expression in fixed lesional mucosal specimens in patients with indolent OLP (no OSCC after at least 5-year follow-up, n = 6), transforming OLP (non-dysplastic epithelium with lichenoid inflammation marginal to OSCC, n = 6) or normal oral mucosa (NOM, n = 5). Transforming OLP protein profile was enriched for actin cytoskeleton, mitochondrial dysfunction and oxidative phosphorylation pathways. CA1, TNNT3, SYNM and MB were overexpressed, and FBLN1 was underexpressed in transforming OLP compared with indolent OLP. Integrin signalling and antigen presentation pathways were enriched in both indolent and transforming OLP compared with NOM. This proteomic study provides potential biomarkers, such as CA1 overexpression, for higher-risk OLP. While further validation studies are needed, we propose that epithelial-mesenchymal transition may be involved in OLP carcinogenesis.

Comprehensive Analysis of PDLIM3 Expression Profile, Prognostic Value, and Correlations with Immune Infiltrates in Gastric Cancer

Protein PDZ and LIM domain 3 (PDLIM3) is a cytoskeletal protein, colocalizing with α-actinin on the Z line of mature muscle fibers. It plays a key role in dilated cardiomyopathy (DCM), muscular dystrophy, and tumor progression. However, correlations between PDLIM3 expression, prognosis, and tumor-infiltrating immune cells in gastric cancer are unknown. Therefore, we leveraged the Oncomine, GEPIA, GEO, and HPA databases to evaluate PDLIM3 expression in tumors. We also quantified PDLIM3 expression in 15 matched pairs of gastric tumor and nontumor tissues by immunohistochemistry. The Kaplan-Meier method was employed to determine the relationship between PDLIM3 expression and clinical outcomes. GO and KEGG analyses were performed to illuminate the molecular mechanisms of action of PDLIM3. TIMER2.0 and GEPIA were applied to investigate correlations between PDLIM3 expression and gene marker subsets signifying immune infiltration, with TIMER2.0 exploring the correlations between PDLIM3 and related signaling pathways. Gastric cancer tissues were found to express more PDLIM3 than nontumor tissues. PDLIM3 overexpression was associated with shorter OS and PFS of gastric cancer patients (OS $\text{HR}=2.02$ , $P=9.8\text{e}-10$ ; PFS $\text{HR}=1.77$ , $P=7.5\text{e}-06$ ). PDLIM3 was also positively correlated with worse OS and PFS according to gastric cancer staging, Her-2 overexpression, differentiation grade, and Lauren classification. PDLIM3 was shown to be associated with immunological responses by GO, while it was related to PI3K/Akt signal pathways by KEGG analysis. Furthermore, increased PDLIM3 expression was significantly correlated with greater infiltration of CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells. PDLIM3 expression had significant positive correlations with a variety of immune marker subsets. Finally, correlations were found between PDLIM3 and crucial markers of signaling pathways involving PI3K/Akt and p38 MAPK. Thus, upregulation of PDLIM3 was significantly associated with poor prognosis, immune cell infiltration, and activation of two key signal pathways in gastric cancer. We propose that PDLIM3 could be used as a biomarker to predict prognosis and immune cell infiltration in gastric cancer.

Inferring Potential Cancer Driving Synonymous Variants

Synonymous single nucleotide variants (sSNVs) are often considered functionally silent, but a few cases of cancer-causing sSNVs have been reported. From available databases, we collected four categories of sSNVs: germline, somatic in normal tissues, somatic in cancerous tissues, and putative cancer drivers. We found that screening sSNVs for recurrence among patients, conservation of the affected genomic position, and synVep prediction (synVep is a machine learning-based sSNV effect predictor) recovers cancer driver variants (termed proposed drivers) and previously unknown putative cancer genes. Of the 2.9 million somatic sSNVs found in the COSMIC database, we identified 2111 proposed cancer driver sSNVs. Of these, 326 sSNVs could be further tagged for possible RNA splicing effects, RNA structural changes, and affected RBP motifs. This list of proposed cancer driver sSNVs provides computational guidance in prioritizing the experimental evaluation of synonymous mutations found in cancers. Furthermore, our list of novel potential cancer genes, galvanized by synonymous mutations, may highlight yet unexplored cancer mechanisms.

Bioinformatical analysis identifies PDLIM3 as a potential biomarker associated with immune infiltration in patients with endometriosis

Background

Endometriosis is a chronic systemic disease, whose classic symptoms are pelvic pain and infertility. This disease seriously reduces the life quality of patients. The pathogenesis, recognition and treatment of endometriosis is still unclear, and cannot be over emphasized. The aim of our study was to investigate the potential biomarker of endometriosis for the mechanism and treatment.

Methods

Using GSE11691, GSE23339 and GSE5108 datasets, differentially expressed genes (DEGs) were identified between endometriosis and normal samples. The functions of DEGs were reflected by the analysis of gene ontology (GO), pathway enrichment and gene set enrichment analysis (GSEA). The LASSO regression model was performed to identify candidate biomarkers. The receiver operating characteristic curve (ROC) was used to evaluate discriminatory ability of candidate biomarkers. The predictive value of the markers in endometriosis were further validated in the GSE120103 dataset. Then, the expression level of biomarkers was detected by qRT-PCR and Western blot. Finally, the relationship between candidate biomarker expression and immune infiltration was estimated using CIBERSORT.

Results

A total of 42 genes were identified, which were mainly involved in cytokine-cytokine receptor interaction, systemic lupus erythematosus and chemokine signaling pathway. We confirmed PDLIM3 was a specific biomarker in endometriosis (AUC = 0.955) and validated in the GSE120103 dataset (AUC = 0.836). The mRNA and protein expression level of PDLIM3 in endometriosis tissue was significantly higher than normal. Immune cell infiltration analysis revealed that PDLIM3 was correlated with M2 macrophages, neutrophils, CD4+ memory resting T cells, gamma delta T cells, M1 Macrophages, resting mast cells, follicular helper T cells, activated NK cells, CD8+ T cells, regulatory T cells (Tregs), naive B cells, plasma cells and resting NK cells.

Comprehensive gene cluster analysis of head and neck squamous cell carcinoma TCGA RNA-seq data defines B cell immunity-related genes as a robust survival predictor

BACKGROUND

The authors aimed to define novel gene expression signatures that are associated with patients' survival with head and neck squamous cell carcinoma (HNSCC).

METHODS

TCGA RNA-seq data were used for gene expression clusters extraction from 499 tumor samples by the "EPIG" method. Tumor samples were then partitioned into lower and higher than median level groups for survival relevant analysis by Kaplan-Meier estimator.

RESULTS

We found that two gene clusters (_1, _2) are favorably, while two (_3, _4) are unfavorably, associated with patients' survival with HNSCC. Notably, most genes on the top lists of cluster_2 are associated with B cells. A gene expression signature with combined genes from cluster_2 and _4 was further determined to be associated with HNSCC survival rate.

CONCLUSION

Our work strongly supported a favorable role of B cells in patients' survival with HNSCC and identified a novel coexpressed gene signature as prognostic biomarker for patients' survival with HNSCC estimation.

Characterization of Molecular Subtypes in Head and Neck Squamous Cell Carcinoma With Distinct Prognosis and Treatment Responsiveness

Head and neck squamous cell carcinoma (HNSCC) is one of the most aggressive malignancies with complex phenotypic, etiological, biological, and clinical heterogeneities. Previous studies have proposed different clinically relevant subtypes of HNSCC, but little is known about its corresponding prognosis or suitable treatment strategy. Here, we identified 101 core genes from three prognostic pathways, including mTORC1 signaling, unfold protein response, and UV response UP, in 124 pairs of tumor and matched normal tissues of HNSCC. Moreover, we identified three robust subtypes associated with distinct molecular characteristics and clinical outcomes using consensus clustering based on the gene expression profiles of 944 HNSCC patients from four independent datasets. We then integrated the genomic information of The Cancer Genome Atlas (TCGA) HNSCC cohort to comprehensively evaluate the molecular features of different subtypes and screen for potentially effective therapeutic agents. Cluster 1 had more arrested oncogenic signaling, the highest immune cell infiltration, the highest immunotherapy and chemotherapeutic responsiveness, and the best prognosis. By contrast, Cluster 3 showed more activated oncogenic signaling, the lowest immune cell infiltration, the lowest immunotherapy and chemotherapy responsiveness, and the worst prognosis. Our findings corroborate the molecular diversity of HNSCC tumors and provide a novel classification strategy that may guide for prognosis and treatment allocation.

Gene Expression Analysis Provides New Insights into the Mechanism of Intramuscular Fat Formation in Japanese Black Cattle

Japanese Black cattle (Japanese Wagyu) have a unique phenotype in which ectopic intramuscular fat accumulates in skeletal muscle, producing finely marbled beef. However, the mechanism of intramuscular fat formation in Japanese Black cattle remains unclear. To investigate the key genes involved in intramuscular fat accumulation, we comprehensively analyzed mRNA levels in subcutaneous and intramuscular fat tissues using RNA sequence (RNA-seq) analysis, which detected 27,606 genes. We identified eight key genes, namely carboxypeptidase E, tenascin C, transgelin, collagen type IV alpha 5 (COL4A5), cysteine and glycine-rich protein 2, PDZ, and LIM domain 3, phosphatase 1 regulatory inhibitor subunit 14A, and regulator of calcineurin 2. These genes were highly and specifically expressed in intramuscular fat tissue. Immunohistochemical analysis revealed a collagen network, including COL4A5, in the basement membrane around the intramuscular fat tissue. Moreover, pathway analysis revealed that, in intramuscular fat tissue, differentially expressed genes are related to cell adhesion, proliferation, and cancer pathways. Furthermore, pathway analysis showed that the transforming growth factor-β (TGF-β) and small GTPases regulators RASGRP3, ARHGEF26, ARHGAP10, ARHGAP24, and DLC were upregulated in intramuscular fat. Our study suggests that these genes are involved in intramuscular fat formation in Japanese Black cattle.