Transcript levels of keratin 1/5/6/14/15/16/17 as potential prognostic indicators in melanoma patients

Comprehensive analysis of aberrantly methylated differentially expressed genes and validation of CDC6 in melanoma

BACKGROUND

Skin Cutaneous Melanoma (SKCM) is a highly aggressive malignant tumor with a significant increase in mortality upon metastasis. The molecular mechanisms driving melanoma progression remain largely unclear. Recent studies have highlighted the importance of epigenetic alterations, especially DNA methylation, in melanoma development. This study aims to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) in genome-wide profiles between primary and metastatic melanoma.

METHODS

Gene expression profiling datasets GSE8401 and gene methylation profiling datasets GSE86355 were collected from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were systematically identified. Integration of DEGs and DMGs yielded a set of MeDEGs, which subsequently underwent functional enrichment analysis. The protein-protein interaction (PPI) network was constructed using STRING and visualized using Cytoscape software. Survival analysis was used to select prognostic hub genes. In addition, 37 SKCM and 37 normal skin tissues from the First Affiliated Hospital of Soochow University (FAHSU) were collected for immunohistochemical (IHC) staining and evaluation. Furthermore, DNA methylation patterns of CDC6 were analyzed. To validate these findings, SKCM cell cultures were utilized to elucidate the expression and behavioral characteristics of CDC6. Additionally, gene set enrichment analysis (GSEA) and immune infiltration analysis were conducted for CDC6.

RESULTS

In our study, we discovered 120 hypomethylated-upregulated genes and 212 hypermethylated-downregulated genes. The hypomethylated-upregulated genes were notably associated with biological processes such as spindle assembly checkpoint signaling, mitotic spindle assembly, and negative regulation of mitotic metaphase/anaphase transition. Our pathway analysis revealed significant enrichment in pathways related to dilated cardiomyopathy, amino sugar metabolism, progesterone-mediated oocyte maturation, and chemical carcinogenesis. Conversely, hypermethylated-downregulated genes were found to be enriched in processes like epidermis development, keratinocyte differentiation, and skin development. Additionally, pathway analysis highlighted associations with estrogen signaling, Staphylococcus aureus infection, axon guidance, and arachidonic acid metabolism. Following the establishment of PPI networks and survival analysis, we identified 11 prognostic hub genes: CCNA2, CDC6, CDCA3, CKS2, DTL, HJURP, KRT5, KRT14, KRT15, KRT16, and NEK2. Notably, among the 11 hub genes, our findings indicate that CDC6 plays a pivotal role in enhancing the proliferation, migration, and invasion capabilities of melanoma cells in vitro.

CONCLUSIONS

Our comprehensive genomic analyses reveal that genes with aberrant methylation exhibit differential expression during the transition from primary to metastatic melanoma. The identified genes, especially CDC6, which plays a crucial role in enhancing melanoma cell proliferation, migration, and invasion, provide valuable insights into potential methylation-based biomarkers. These findings could contribute significantly to advancing precision medicine in SKCM.

Assessment of Concentration KRT6 Proteins in Tumor and Matching Surgical Margin from Patients with Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinomas (HNSCCs) are one of the most frequently detected cancers in the world; not all mechanisms related to the expression of keratin in this type of cancer are known. The aim of this study was to evaluate type II cytokeratins (KRT): KRT6A, KRT6B, and KRT6C protein concentrations in 54 tumor and margin samples of head and neck squamous cell carcinoma (HNSCC). Moreover, we examined a possible association between protein concentration and the clinical and demographic variables. Protein concentrations were measured using enzyme-linked immunosorbent assay (ELISA). Significantly higher KRT6A protein concentration was found in HNSCC samples compared to surgical margins. An inverse relationship was observed for KRT6B and KRT6C proteins. We showed an association between the KRT6C protein level and clinical parameters T and N in tumor and margin samples. When analyzing the effect of smoking and drinking on KRT6A, KRT6B, and KRT6C levels, we demonstrated a statistically significant difference between regular or occasional tobacco and alcohol habits and patients who do not have any tobacco and alcohol habits in tumor and margin samples. Moreover, we found an association between KRT6B and KRT6C concentration and proliferative index Ki-67 and HPV status in tumor samples. Our results showed that concentrations of KRT6s were different in the tumor and the margin samples and varied in relation to clinical and demographic parameters. We add information to the current knowledge about the role of KRT6s isoforms in HNSCC. We speculate that variations in the studied isoforms of the KRT6 protein could be due to the presence and development of the tumor and its microenvironment. It is important to note that the analyses were performed in tumor and surgical margins and can provide more accurate information on the function in normal and cancer cells and regulation in response to various factors.

Bioinformatic analysis and experimental validation of six cuproptosis-associated genes as a prognostic signature of breast cancer

Background

Breast carcinoma (BRCA) is a life-threatening malignancy in women and shows a poor prognosis. Cuproptosis is a novel mode of cell death but its relationship with BRCA is unclear. This study attempted to develop a cuproptosis-relevant prognostic gene signature for BRCA.

Methods

Cuproptosis-relevant subtypes of BRCA were obtained by consensus clustering. Differential expression analysis was implemented using the 'limma' package. Univariate Cox and multivariate Cox analyses were performed to determine a cuproptosis-relevant prognostic gene signature. The signature was constructed and validated in distinct datasets. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were also conducted using the prognostic signature to uncover the underlying molecular mechanisms. ESTIMATE and CIBERSORT algorithms were applied to probe the linkage between the gene signature and tumor microenvironment (TME). Immunotherapy responsiveness was assessed using the Tumor Immune Dysfunction and Exclusion (TIDE) web tool. Real-time quantitative PCR (RT-qPCR) was performed to detect the expressions of cuproptosis-relevant prognostic genes in breast cancer cell lines.

Results

Thirty-eight cuproptosis-associated differentially expressed genes (DEGs) in BRCA were mined by consensus clustering and differential expression analysis. Based on univariate Cox and multivariate Cox analyses, six cuproptosis-relevant prognostic genes, namely SAA1, KRT17, VAV3, IGHG1, TFF1, and CLEC3A, were mined to establish a corresponding signature. The signature was validated using external validation sets. GSVA and GSEA showed that multiple cell cycle-linked and immune-related pathways along with biological processes were associated with the signature. The results ESTIMATE and CIBERSORT analyses revealed significantly different TMEs between the two Cusig score subgroups. Finally, RT-qPCR analysis of cell lines further confirmed the expressional trends of SAA1, KRT17, IGHG1, and CLEC3A.

Conclusion

Taken together, we constructed a signature for projecting the overall survival of BRCA patients and our findings authenticated the cuproptosis-relevant prognostic genes, which are expected to provide a basis for developing prognostic molecular biomarkers and an in-depth understanding of the relationship between cuproptosis and BRCA.

Azoxymethane-induced carcinogenesis-like model of mouse intestine and mouse embryonic stem cell-derived intestinal organoids

BACKGROUND

Tumor modeling using organoids holds potential in studies of cancer development, enlightening both the intracellular and extracellular molecular mechanisms behind different cancer types, biobanking, and drug screening. Intestinal organoids can be generated in vitro using a unique type of adult stem cells which are found at the base of crypts and are characterized by their high Lgr5 expression levels.

METHODS AND RESULTS

In this study, we successfully established intestinal cancer organoid models by using both the BALB/c derived and mouse embryonic stem cells (mESCs)-derived intestinal organoids. In both cases, carcinogenesis-like model was developed by using azoxymethane (AOM) treatment. Carcinogenesis-like model was verified by H&E staining, immunostaining, relative mRNA expression analysis, and LC/MS analysis. The morphologic analysis demonstrated that the number of generated organoids, the number of crypts, and the intensity of the organoids were significantly augmented in AOM-treated intestinal organoids compared to non-AOM-treated ones. Relative mRNA expression data revealed that there was a significant increase in both Wnt signaling pathway-related genes and pluripotency transcription factors in the AOM-induced intestinal organoids.

CONCLUSION

We successfully developed simple carcinogenesis-like models using mESC-based and Lgr5 + stem cell-based intestinal organoids. Intestinal organoid based carcinogenesi models might be used for personalized cancer therapy in the future.

The Expression of TP63 as a Biomarker of Early Recurrence in Resected Esophageal Squamous Cell Carcinoma after Neoadjuvant Chemoradiotherapy

Esophageal cancer ranks among the ten most common cancers worldwide. Despite the adoption of neoadjuvant concurrent chemoradiotherapy (nCCRT) followed by surgery as the standard treatment approach in recent years, the local recurrence rate remains high. In this study, we employed RNA-seq to investigate distinctive gene expression profiles in esophageal squamous cell carcinoma (ESCC) with or without recurrence following a standard treatment course. Our findings indicate that recurrent ESCC exhibits heightened keratinizing and epidermis development activity compared to non-recurrent ESCC. We identified TP63 as a potential candidate for distinguishing clinical outcomes. Furthermore, immunohistochemistry confirmed the trend of TP63 overexpression in ESCC recurrence. Patients with elevated TP63 expression had poorer overall survival and lower 3-year recurrence-free survival. This study underscores the potential of TP63 as a biomarker for detecting cancer recurrence and suggests its role in guiding future treatment options.

Emerging prognostic biomarkers in advanced cutaneous melanoma: a literature update

INTRODUCTION

Over the past two years, the scientific community has witnessed an exponential growth in research focused on identifying prognostic biomarkers for melanoma, both in pre-clinical and clinical settings. This surge in studies reflects the need of developing effective prognostic indicators in the field of melanoma.

AREAS COVERED

The aim of this work is to review the scientific literature on the most recent findings on the development or validation of prognostic biomarkers in melanoma, in the attempt of providing both clinicians and researchers with an updated broad synopsis of prognostic biomarkers in cutaneous melanoma.

EXPERT OPINION

While the field of prognostic biomarkers in melanoma appears promising, there are several complexities and limitations to address. The interdependence of clinical, histological, and molecular features requires accurate classification of different biomarker families. Correlation does not imply causation, and adjustments for confounding factors are often overlooked. In this scenario, large-scale studies based on high-quality clinical trial data can provide more reliable evidence. It is essential to avoid oversimplification by focusing on a single biomarker, as the interactions among multiple factors contribute to define the disease course and patient's outcome. Furthermore, implementing well-supported evidence in real-life settings can help advance prognostic biomarker research in melanoma.

Emerging Prognostic and Predictive Significance of Stress Keratin 17 in HPV-Associated and Non HPV-Associated Human Cancers: A Scoping Review

A growing body of literature suggests that the expression of cytokeratin 17 (K17) correlates with inferior clinical outcomes across various cancer types. In this scoping review, we aimed to review and map the available clinical evidence of the prognostic and predictive value of K17 in human cancers. PubMed, Web of Science, Embase (via Scopus), Cochrane Central Register of Controlled Trials, and Google Scholar were searched for studies of K17 expression in human cancers. Eligible studies were peer-reviewed, published in English, presented original data, and directly evaluated the association between K17 and clinical outcomes in human cancers. Of the 1705 studies identified in our search, 58 studies met criteria for inclusion. Studies assessed the prognostic significance (n = 54), predictive significance (n = 2), or both the prognostic and predictive significance (n = 2). Altogether, 11 studies (19.0%) investigated the clinical relevance of K17 in cancers with a known etiologic association to HPV; of those, 8 (13.8%) were focused on head and neck squamous cell carcinoma (HNSCC), and 3 (5.1%) were focused on cervical squamous cell carcinoma (SCC). To date, HNSCC, as well as triple-negative breast cancer (TNBC) and pancreatic cancer, were the most frequently studied cancer types. K17 had prognostic significance in 16/17 investigated cancer types and 43/56 studies. Our analysis suggests that K17 is a negative prognostic factor in the majority of studied cancer types, including HPV-associated types such as HNSCC and cervical cancer (13/17), and a positive prognostic factor in 2/17 studied cancer types (urothelial carcinoma of the upper urinary tract and breast cancer). In three out of four predictive studies, K17 was a negative predictive factor for chemotherapy and immune checkpoint blockade therapy response.

A novel lncRNA-mediated epigenetic regulatory mechanism in periodontitis

Periodontitis is a highly prevalent chronic inflammatory disease with an exaggerated host immune response, resulting in periodontal tissue destruction and potential tooth loss. The long non-coding RNA, LncR-ANRIL, located on human chromosome 9p21, is recognized as a genetic risk factor for various conditions, including atherosclerosis, periodontitis, diabetes, and cancer. LncR-APDC is an ortholog of ANRIL located on mouse genome chr4. This study aims to comprehend the regulatory role of lncR-APDC in periodontitis progression. Our experimental findings, obtained from lncR-APDC gene knockout (KO) mice with induced experimental periodontitis (EP), revealed exacerbated bone loss and disrupted pro-inflammatory cytokine regulation. Downregulation of osteogenic differentiation occurred in bone marrow stem cells harvested from lncR-APDC-KO mice. Furthermore, single-cell RNA sequencing of periodontitis gingival tissue revealed alterations in the proportion and function of immune cells, including T and B cells, macrophages, and neutrophils, due to lncR-APDC silencing. Our findings also unveiled a previously unidentified epithelial cell subset that is distinctively presenting in the lncR-APDC-KO group. This epithelial subset, characterized by the positive expression of Krt8 and Krt18, engages in interactions with immune cells through a variety of ligand-receptor pairs. The expression of Tff2, now recognized for its role in chronic inflammatory conditions, exhibited a notable increase across various tissue and cell types in lncR-APDC deficient mice. Additionally, our investigation revealed the potential for a direct binding interaction between lncR-APDC and Tff2. Intra-gingival administration of AAV9-lncR-APDC was shown to have therapeutic effects in the EP model. In conclusion, our results suggest that lncR-APDC plays a critical role in the progression of periodontal disease and holds therapeutic potential for periodontitis. Furthermore, the presence of the distinctive epithelial subpopulation and significantly elevated Tff2 levels in the lncR-APDC-silenced EP model offer new perspectives on the epigenetic regulation of periodontitis pathogenesis.

Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel

Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited in proteomic depth, throughput, and robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated and complete dimethyl labeling of bulk or single-cell samples, without losing proteomic depth. Lys-N digestion enables five-plex quantification at MS1 and MS2 level. Because the multiplexed channels are quantitatively isolated from each other, mDIA accommodates a reference channel that does not interfere with the target channels. Our algorithm RefQuant takes advantage of this and confidently quantifies twice as many proteins per single cell compared to our previous work (Brunner et al, PMID 35226415), while our workflow currently allows routine analysis of 80 single cells per day. Finally, we combined mDIA with spatial proteomics to increase the throughput of Deep Visual Proteomics seven-fold for microdissection and four-fold for MS analysis. Applying this to primary cutaneous melanoma, we discovered proteomic signatures of cells within distinct tumor microenvironments, showcasing its potential for precision oncology.

Tetraspanin CD63 reduces the progression and metastasis of head and neck squamous cell carcinoma via KRT1-mediated cell cycle arrest

Despite the fact that metastasis is the leading cause of death in patients with head and neck squamous cell carcinoma, fundamental questions about the mechanisms that enable or inhibit metastasis remain unanswered. Tetraspanin CD63 has been linked to tumor progression and metastasis. However, few studies have examined the role of CD63 in HNSCC. In this study, we discovered that CD63 levels were abnormally altered in HNSCC tissue compared to adjacent tissue (n = 69 pairs), and that this was linked to prognosis. Through functional in vitro and in vivo experiments, the roles of CD63 in HNSCC were confirmed. Overexpression of CD63 inhibited the progression and metastasis of HNSCC cells. Using mass spectrometry and co-immunoprecipitation assays, we discovered that KRT1 could be a direct interacting partner of CD63. Furthermore, both CD63 and KRT1 expression was significantly decreased in metastatic tissue compared with primary tumor tissue (n = 13 pairs), suggesting that CD63 and KRT1 play a role in reducing the metastasis of HNSCC. In summary, we reveal a previously unrecognized role of CD63 in regulating KRT1-mediated cell cycle arrest in HNSCC cells, and our findings contribute to defining an important mechanism of HNSCC progression and metastasis.

Candidate Genes and Pathways in Cervical Cancer: A Systematic Review and Integrated Bioinformatic Analysis

Cervical cancer is the leading cause of cancer-related death among women in developing countries. However, no comprehensive molecular mechanism for cervical cancer has been established, as many studies were small-cohort studies conducted with small sample sizes. A thorough literature search was performed using the PubMed, Scopus, EBSCOhost, and Science Direct databases. Medical Subject Heading (MeSH) terms such as "Uterine Cervical Neoplasms" and "gene expression" were used as the keywords in all fields. A total of 4027 studies were retrieved, and only clinical studies, which used the microarray method to identify differentially expressed genes (DEGs) in the cervical tissue of cervical cancer patients, were selected. Following the screening, 6 studies were selected and 1128 DEGs were extracted from the data. Sixty-two differentially expressed genes from at least two studies were selected for further analysis by DAVID, STRING, and Cytoscape software. In cervical cancer pathogenesis, three significant clusters with high intermolecular interactions from the Protein-Protein Interaction (PPI) network complex revealed three major molecular mechanisms, including cell signaling, cell cycle, and cell differentiation. Subsequently, eight genes were chosen as the candidate genes based on their involvement in the relevant gene ontology (GO) and their interaction with other genes in the PPI network through undirected first neighbor nodes. The present systematic review improves our understanding of the molecular mechanism of cervical cancer and the proposed genes that can be used to expand the biomarker panel in the screening for cervical cancer. The targeted genes may be beneficial for the development of better treatment strategies.

Short- and long-term polystyrene nano- and microplastic exposure promotes oxidative stress and divergently affects skin cell architecture and Wnt/beta-catenin signaling

Nano- and microplastic particles (NMP) are strong environmental contaminants affecting marine ecosystems and human health. The negligible use of biodegradable plastics and the lack of knowledge about plastic uptake, accumulation, and functional consequences led us to investigate the short- and long-term effects in freshly isolated skin cells from mice. Using fluorescent NMP of several sizes (200 nm to 6 µm), efficient cellular uptake was observed, causing, however, only minor acute toxicity as metabolic activity and apoptosis data suggested, albeit changes in intracellular reactive species and thiol levels were observed. The internalized NMP induced an altered expression of various targets of the nuclear factor-2-related transcription factor 2 pathway and were accompanied by changed antioxidant and oxidative stress signaling responses, as suggested by altered heme oxygenase 1 and glutathione peroxide 2 levels. A highly increased beta-catenin expression under acute but not chronic NMP exposure was concomitant with a strong translocation from membrane to the nucleus and subsequent transcription activation of Wnt signaling target genes after both single-dose and chronic long-term NMP exposure. Moreover, fibroblast-to-myofibroblast transdifferentiation accompanied by an increase of α smooth muscle actin and collagen expression was observed. Together with several NMP-induced changes in junctional and adherence protein expression, our study for the first time elucidates the acute and chronic effects of NMP of different sizes in primary skin cells' signaling and functional biology, contributing to a better understanding of nano- and microplastic to health risks in higher vertebrates.

Trojan-horse silk fibroin nanocarriers loaded with a re-call antigen to redirect immunity against cancer

BACKGROUND

The current challenge for immunotherapies is to generate effective antitumor immunity. Since tumor immune escape mechanisms do not impact pre-existing and consolidated immune responses, we tested the hypothesis of redirecting a pregenerated immunity to cancer: to recall a non-tumor antigen response against the tumor, silk fibroin nanoparticles (SFNs) have been selected as 'Trojan-horse' carriers, promoting the antigen uptake by the tumor cells.

METHODS

SFNs have been loaded with either ovalbumin (OVA) or CpG oligonucleotide (CpG) as antigen or adjuvant, respectively. In vitro uptake of SFNs by tumor (B16/F10 melanoma and MB49 bladder cancer) or dendritic cells, as well as the presence of OVA-specific T cells in splenic and tumor-infiltrating lymphocytes, were assessed by cytometric analyses. Proof-of-concept of in vivo efficacy was achieved in an OVA-hyperimmune B16/F10 murine melanoma model: SFNs-OVA or SFNs-CpG were injected, separately or in association, into the subcutaneous peritumoral area. Cancer dimensions/survival time were monitored, while, at the molecular level, system biology approaches based on graph theory and experimental proteomic data were performed.

RESULTS

SFNs were efficiently in vitro uptaken by cancer and dendritic cells. In vivo peritumor administration of SFNs-OVA redirected OVA-specific cytotoxic T cells intratumorally. Proteomics and systems biology showed that peritumoral treatment with either SFNs-OVA or SFNs-CpG dramatically modified tumor microenvironment with respect to the control (CTR), mainly involving functional modules and hubs related to angiogenesis, inflammatory mediators, immune function, T complex and serpins expression, redox homeostasis, and energetic metabolism. Both SFNs-OVA and SFNs-CpG significantly delayed melanoma growth/survival time, and their effect was additive.

CONCLUSIONS

Both SFNs-OVA and SFNs-CpG induce effective anticancer response through complementary mechanisms and show the efficacy of an innovative active immunotherapy approach based on the redirection of pre-existing immunity against cancer cells. This approach could be universally applied for solid cancer treatments if translated into the clinic using re-call antigens of childhood vaccination.

Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma

The complexity of lung adenocarcinoma (LUAD), the development of which involves many interacting biological processes, makes it difficult to find therapeutic biomarkers for treatment. FK506-binding proteins (FKBPs) are composed of 12 members classified as conservative intracellular immunophilin family proteins, which are often connected to cyclophilin structures by tetratricopeptide repeat domains and have peptidyl prolyl isomerase activity that catalyzes proline from residues and turns the trans form into the cis form. Since FKBPs belong to chaperone molecules and promote protein folding, previous studies demonstrated that FKBP family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcript expressions of this gene family in LUAD still need to be more fully investigated. In this research, we adopted high-throughput bioinformatics technology to analyze FKBP family genes in LUAD to provide credible information to clinicians and promote the development of novel cancer target drugs in the future. The current data revealed that the messenger (m)RNA levels of FKBP2, FKBP3, FKBP4, FKBP10, FKBP11, and FKBP14 were overexpressed in LUAD, and FKBP10 had connections to poor prognoses among LUAD patients in an overall survival (OS) analysis. Based on the above results, we selected FKBP10 to further conduct a comprehensive analysis of the downstream pathway and network. Through a DAVID analysis, we found that FKBP10 was involved in mitochondrial electron transport, NADH to ubiquinone transport, mitochondrial respiratory chain complex I assembly, etc. The MetaCore pathway analysis also indicated that FKBP10 was involved in "Ubiquinone metabolism", "Translation_(L)-selenoaminoacid incorporation in proteins during translation", and "Transcription_Negative regulation of HIF1A function". Collectively, this study revealed that FKBP family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, thus providing new targets for treating LUAD patients.

SpatialCorr identifies gene sets with spatially varying correlation structure

Recent advances in spatially resolved transcriptomics technologies enable both the measurement of genome-wide gene expression profiles and their mapping to spatial locations within a tissue. A first step in spatial transcriptomics data analysis is identifying genes with expression that varies spatially, and robust statistical methods exist to address this challenge. While useful, these methods do not detect spatial changes in the coordinated expression within a group of genes. To this end, we present SpatialCorr, a method for identifying sets of genes with spatially varying correlation structure. Given a collection of gene sets pre-defined by a user, SpatialCorr tests for spatially induced differences in the correlation of each gene set within tissue regions, as well as between and among regions. An application to cutaneous squamous cell carcinoma demonstrates the power of the approach for revealing biological insights not identified using existing methods.

Biomarker Discovery for Meta-Classification of Melanoma Metastatic Progression Using Transfer Learning

Melanoma is considered to be the most serious and aggressive type of skin cancer, and metastasis appears to be the most important factor in its prognosis. Herein, we developed a transfer learning-based biomarker discovery model that could aid in the diagnosis and prognosis of this disease. After applying it to the ensemble machine learning model, results revealed that the genes found were consistent with those found using other methodologies previously applied to the same TCGA (The Cancer Genome Atlas) data set. Further novel biomarkers were also found. Our ensemble model achieved an AUC of 0.9861, an accuracy of 91.05, and an F1 score of 90.60 using an independent validation data set. This study was able to identify potential genes for diagnostic classification (C7 and GRIK5) and diagnostic and prognostic biomarkers (S100A7, S100A7, KRT14, KRT17, KRT6B, KRTDAP, SERPINB4, TSHR, PVRL4, WFDC5, IL20RB) in melanoma. The results show the utility of a transfer learning approach for biomarker discovery in melanoma.

Development and validation of an epithelial–mesenchymal transition-related gene signature for predicting prognosis

BACKGROUND

Currently, there are many therapeutic methods for lung adenocarcinoma (LUAD), but the 5-year survival rate is still only 15% at later stages. Epithelial– mesenchymal transition (EMT) has been shown to be closely associated with local dissemination and subsequent metastasis of solid tumors. However, the role of EMT in the occurrence and development of LUAD remains unclear.

AIM

To further elucidate the value of EMT-related genes in LUAD prognosis.

METHODS

Univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were applied to establish and validate a new EMT-related gene signature for predicting LUAD prognosis. The risk model was evaluated by Kaplan–Meier survival analysis, principal component analysis, and functional enrichment analysis and was used for nomogram construction. The potential structures of drugs to which LUAD is sensitive were discussed with respect to EMT-related genes in this model.

RESULTS

Thirty-three differentially expressed genes related to EMT were found to be highly associated with overall survival (OS) by using univariate Cox regression analysis (log2FC ≥ 1, false discovery rate < 0.001). A prognostic signature of 7 EMT-associated genes was developed to divide patients into two risk groups by high or low risk scores. Kaplan–Meier survival analysis showed that the OS of patients in the high-risk group was significantly poorer than that of patients in the low-risk group (P < 0.05). Multivariate Cox regression analysis showed that the risk score was an independent risk factor for OS (HR > 1, P < 0.05). The results of receiver operator characteristic curve analysis suggested that the 7-gene signature had a perfect ability to predict prognosis (all area under the curves > 0.5).

CONCLUSION

The EMT-associated gene signature classifier could be used as a feasible indicator for predicting OS.

DEAD-Box RNA Helicases DDX3X and DDX5 as Oncogenes or Oncosuppressors: A Network Perspective

Simple Summary

The transformation of a normal cell into a cancerous one is caused by the deregulation of different metabolic pathways, involving a complex network of protein–protein interactions. The cellular enzymes DDX3X and DDX5 play important roles in the maintenance of normal cell metabolism, but their deregulation can accelerate tumor transformation. Both DDX3X and DDX5 interact with hundreds of different cellular proteins, and depending on the specific pathways in which they are involved, both proteins can either act as suppressors of cancer or as oncogenes. In this review, we summarize the current knowledge about the roles of DDX3X and DDX5 in different tumors. In addition, we present a list of interacting proteins and discuss the possible contribution of some of these protein–protein interactions in determining the roles of DDX3X and DDX5 in the process of cancer proliferation, also suggesting novel hypotheses for future studies.

Abstract

RNA helicases of the DEAD-box family are involved in several metabolic pathways, from transcription and translation to cell proliferation, innate immunity and stress response. Given their multiple roles, it is not surprising that their deregulation or mutation is linked to different pathological conditions, including cancer. However, while in some cases the loss of function of a given DEAD-box helicase promotes tumor transformation, indicating an oncosuppressive role, in other contexts the overexpression of the same enzyme favors cancer progression, thus acting as a typical oncogene. The roles of two well-characterized members of this family, DDX3X and DDX5, as both oncogenes and oncosuppressors have been documented in several cancer types. Understanding the interplay of the different cellular contexts, as defined by the molecular interaction networks of DDX3X and DDX5 in different tumors, with the cancer-specific roles played by these proteins could help to explain their apparently conflicting roles as cancer drivers or suppressors.

MetastaSite: Predicting metastasis to different sites using deep learning with gene expression data

Deep learning has massive potential in predicting phenotype from different omics profiles. However, deep neural networks are viewed as black boxes, providing predictions without explanation. Therefore, the requirements for these models to become interpretable are increasing, especially in the medical field. Here we propose a computational framework that takes the gene expression profile of any primary cancer sample and predicts whether patients’ samples are primary (localized) or metastasized to the brain, bone, lung, or liver based on deep learning architecture. Specifically, we first constructed an AutoEncoder framework to learn the non-linear relationship between genes, and then DeepLIFT was applied to calculate genes’ importance scores. Next, to mine the top essential genes that can distinguish the primary and metastasized tumors, we iteratively added ten top-ranked genes based upon their importance score to train a DNN model. Then we trained a final multi-class DNN that uses the output from the previous part as an input and predicts whether samples are primary or metastasized to the brain, bone, lung, or liver. The prediction performances ranged from AUC of 0.93–0.82. We further designed the model’s workflow to provide a second functionality beyond metastasis site prediction, i.e., to identify the biological functions that the DL model uses to perform the prediction. To our knowledge, this is the first multi-class DNN model developed for the generic prediction of metastasis to various sites.

Bioinformatic analysis identifies epidermal development genes that contribute to melanoma progression

Several diagnostic and prognostic markers for melanoma have been identified in last few years. However, their actual contribution to melanoma progression have not been investigated in detail. This study was aimed to identify genes, biological processes, and signaling pathways implicated in melanoma progression by applying bioinformatics analysis. We identified nine differentially expressed genes (DEGs) (IL36RN, KRT6A, KRT6B, KRT16, S100A7, SPRR1A, SPRR1B, SPRR2B, and KLK7) that were upregulated in primary melanoma compared with metastatic melanoma in all five datasets analyzed. All these genes except IL36RN, both form a protein-protein interaction network and have cellular functions associated with constitutive processes of keratinocytes. Thus, they were generically termed Epidermal Development and Cornification (EDC) genes. The differential expression of these genes in primary and metastatic melanoma was confirmed in the TCGA-SKCM cohort. High expression of the EDC genes correlated with reduced tumor thickness in primary melanoma and shorter survival in metastatic melanoma. Analysis of DEGs from primary melanoma patients displaying high or low expression of all eight EDC revealed that the upregulated genes are enriched in biological process related to cell migration, extracellular matrix organization, invasion, and Epithelial-Mesenchymal Transition. Further analysis of enriched curated oncogenic genesets together with RPPA data of phosphorylated proteins revealed the activation of MEK, ATF2, and EGFR pathways in tumors displaying high expression of EDC genes. Thus, EDC genes may contribute to melanoma progression by promoting the activation of MEK, ATF2, and EGFR pathways together with biological processes associated with tumor aggressiveness.

Gut Microbiota Dysbiosis Induced by Decreasing Endogenous Melatonin Mediates the Pathogenesis of Alzheimer's Disease and Obesity

Lifestyle choices, external environment, aging, and other factors influence the synthesis of melatonin. Although the physiological functions of melatonin have been widely studied in relation to specific organs, the systemic effects of endogenous melatonin reduction has not been reported. This study evaluates the systemic changes and possible pathogenic risks in an endogenous melatonin reduction (EMR) mouse model deficient in the rate limiting enzyme in melatonin production, arylalkylamine N-acetyltransferase (Aanat) gene. Using this model, we identified a new relationship between melatonin, Alzheimer’s disease (AD), and gut microbiota. Systematic changes were evaluated using multi-omics analysis. Fecal microbiota transplantation (FMT) was performed to examine the role of gut microbiota in the pathogenic risks of EMR. EMR mice exhibited a pan-metabolic disorder, with significant transcriptome changes in 11 organs, serum metabolome alterations as well as microbiota dysbiosis. Microbiota dysbiosis was accompanied by increased gut permeability along with gut and systemic inflammation. Correlation analysis revealed that systemic inflammation may be related to the increase of Ruminiclostridium_5 relative abundance. 8-month-old EMR mice had AD-like phenotypes, including Iba-1 activation, A β protein deposition and decreased spatial memory ability. Moreover, EMR mice showed decreased anti stress ability, under high-fat diet, EMR mice had greater body weight and more obvious hepatic steatosis compared with WT group. FMT improved gut permeability, systemic inflammation, and AD-related phenotypes, while reducing obesity in EMR mice. Our findings suggest EMR causes systemic changes mediated by gut microbiota dysbiosis, which may be a pathogenic factor for AD and obesity, we further proved the gut microbiota is a potential target for the prevention and treatment of AD and obesity.

The Dark Side of Melanin Secretion in Cutaneous Melanoma Aggressiveness

Skin cancers are among the most common cancers worldwide and are increasingly prevalent. Cutaneous melanoma (CM) is characterized by the malignant transformation of melanocytes in the epidermis. Although CM shows lower incidence than other skin cancers, it is the most aggressive and responsible for the vast majority of skin cancer-related deaths. Indeed, 75% of patients present with invasive or metastatic tumors, even after surgical excision. In CM, the photoprotective pigment melanin, which is produced by melanocytes, plays a central role in the pathology of the disease. Melanin absorbs ultraviolet radiation and scavenges reactive oxygen/nitrogen species (ROS/RNS) resulting from the radiation exposure. However, the scavenged ROS/RNS modify melanin and lead to the induction of signature DNA damage in CM cells, namely cyclobutane pyrimidine dimers, which are known to promote CM immortalization and carcinogenesis. Despite triggering the malignant transformation of melanocytes and promoting initial tumor growth, the presence of melanin inside CM cells is described to negatively regulate their invasiveness by increasing cell stiffness and reducing elasticity. Emerging evidence also indicates that melanin secreted from CM cells is required for the immunomodulation of tumor microenvironment. Indeed, melanin transforms dermal fibroblasts in cancer-associated fibroblasts, suppresses the immune system and promotes tumor angiogenesis, thus sustaining CM progression and metastasis. Here, we review the current knowledge on the role of melanin secretion in CM aggressiveness and the molecular machinery involved, as well as the impact in tumor microenvironment and immune responses. A better understanding of this role and the molecular players involved could enable the modulation of melanin secretion to become a therapeutic strategy to impair CM invasion and metastasis and, hence, reduce the burden of CM-associated deaths.

Development and validation of apoptosis-related signature and molecular subtype to improve prognosis prediction in osteosarcoma patients

BACKGROUND

Previous evidence has shown that apoptosis performs integral functions in the tumorigenesis and development of various tumors. Therefore, this study aimed to establish a molecular subtype and prognostic signature based on apoptosis-related genes (ARGs) to understand the molecular mechanisms and predict prognosis in patients with osteosarcoma.

METHODS

The GEO and TARGET databases were utilized to obtain the expression levels of ARGs and clinical information of osteosarcoma patients. Consensus clustering analysis was used to explore the different molecular subtypes based on ARGs. GO, KEGG, GSEA, ESTIMATE, and ssGSEA analyses were performed to examine the differences in biological functions and immune characteristics between the distinct molecular subtypes. Then, we constructed an ARG signature by LASSO analysis. The prognostic significance of the ARG signature in osteosarcoma was determined by Kaplan-Meier plotter, Cox regression, and nomogram analyses.

RESULTS

Two apoptosis-related subtypes were identified. Cluster 1 had a better prognosis, higher immunogenicity, and immune cell infiltration, as well as a better response to immunotherapy than Cluster 2. We discovered that patients in the high-risk cohort had a lower survival rate than those in the low-risk cohort according to the ARG signature. Furthermore, Cox regression analysis confirmed that a high risk score independently acted as an unfavorable prognostic marker. Additionally, the nomogram combining risk scores with clinical characteristics can improve prediction efficiency.

CONCLUSION

We demonstrated that patients suffering from osteosarcoma may be classified into two apoptosis-related subtypes. Moreover, we developed an ARG prognostic signature to predict the prognosis status of osteosarcoma patients.

Prognostic significance of AP-2α/γ targets as cancer therapeutics

Identifying genes with prognostic importance could improve cancer treatment. An increasing number of reports suggest the existence of successful strategies based on seemingly "untargetable" transcription factors. In addition to embryogenesis, AP-2 transcription factors are known to play crucial roles in cancer development. Members of this family can be used as prognostic factors in oncological patients, and AP-2α/γ transcription factors were previously investigated in our pan-cancer comparative study using their target genes. The present study investigates tumors that were previously found similar with an emphasis on the possible role of AP-2 factors in specific cancer types. The RData workspace was loaded back to R environment and 3D trajectories were built via Monocle3. The genes that met the requirement of specificity were listed using top_markers(), separately for mutual and unique targets. Furthermore, the candidate genes had to meet the following requirements: correlation with AP-2 factor (through Correlation AnalyzeR) and validated prognostic importance (using GEPIA2 and subsequently KM-plotter or LOGpc). Eventually, the ROC analysis was applied to confirm their predictive value; co-dependence of expression was visualized via BoxPlotR. Some similar tumors were differentiated by AP-2α/γ targets with prognostic value. Requirements were met by only fifteen genes (EMX2, COL7A1, GRIA1, KRT1, KRT14, SLC12A5, SEZ6L, PTPRN, SCG5, DPP6, NTSR1, ARX, COL4A3, PPEF1 and TMEM59L); of these, the last four were excluded based on ROC curves. All the above genes were confronted with the literature, with an emphasis on the possible role played by AP-2 factors in specific cancers. Following ROC analysis, the genes were verified using immunohistochemistry data and progression-related signatures. Staining differences were observed, as well as co-dependence on the expression of e.g. CTNNB1, ERBB2, KRAS, SMAD4, EGFR or MKI67. In conclusion, prognostic value of targets suggested AP-2α/γ as candidates for novel cancer treatment. It was also revealed that AP-2 targets are related to tumor progression and that some mutual target genes could be inversely regulated.

Quantitative Proteomic Analysis of Cervical Cancer Tissues Identifies Proteins Associated With Cancer Progression

BACKGROUND/AIM

To date, several proteomics studies in cervical cancer (CC) have focused mainly on squamous cervical cancer (SCC). Our study aimed to discover and clarify differences in SCC and CAD that may provide valuable information for the identification of proteins involved in tumor progression, in CC as a whole, or specific for SCC or CAD.

MATERIALS AND METHODS

Total protein extracts from 15 individual samples corresponding to 5 different CC tissue types were compared with a non-cancerous control group using bidimensional liquid chromatography-mass spectrometry (2D LC-MS/MS), isobaric tags for relative and absolute quantitation (ITRAQ), principal component analysis (PCA) and gene set enrichment analysis (GSEA).

RESULTS

A total of 622 statistically significant different proteins were detected. Exocytosis-related proteins were the most over-represented, accounting for 25% of the identified and quantified proteins. Based on the experimental results, reticulocalbin 3 (RCN3) and Ras-related protein Rab-14 (RAB14) were chosen for further downstream in vitro and vivo analyses. RCN3 was overexpressed in all CC tissues compared to the control and RAB14 was overexpressed in squamous cervical cancer (SCC) compared to invasive cervical adenocarcinoma (CAD). In the tumor xenograft experiment, RAB14 protein expression was positively correlated with increased tumor size. In addition, RCN3-expressing HeLa cells induced a discrete size increment compared to control, at day 47 after inoculation.

CONCLUSION

RAB14 and RCN3 are suggested as potential biomarkers and therapeutic targets in the treatment of CC.

Immune-related lncRNA pairs as novel signature to predict prognosis and immune landscape in melanoma patients

To investigate immune-related long non-coding RNA (irlncRNA) signatures for predicting survival and the immune landscape in melanoma patients.We retrieved gene expression files from The Cancer Genome Atlas and the Genotype-Tissue Expression database and extracted all the long non-coding RNAs from the original data. Then, we selected immune-related long non-coding RNAs (irlncRNAs) using co-expression networks and screened differentially expressed irlncRNAs (DEirlncRNAs) to form pairs. We also performed univariate analysis and Least absolute shrinkage and selection operator (LASSO) penalized regression analysis to identify prognostic DEirlncRNA pairs, constructed receiver operating characteristic curves, compared the areas under the curves, and calculated the optimal cut-off point to divide patients into high-risk and low-risk groups. Finally, we performed multivariate Cox regression analysis, Kaplan-Meier (K-M) survival analysis, clinical correlation analysis, and investigated correlations with tumor-infiltrating immune cells, chemotherapeutic effectiveness, and immunogene biomarkers.A total of 297 DEirlncRNAs were identified, of which 16 DEirlncRNA pairs were associated with prognosis in melanoma. After grouping patients by the optimal cut-off value, we could better distinguish melanoma patients with different survival outcomes, clinical characteristics, tumor immune status changes, chemotherapeutic drug sensitivity, and specific immunogene biomarkers.The DEirlncRNA pairs showed potential as novel biomarkers to predict the prognosis of melanoma patients. Furthermore, these DEirlncRNA pairs could be used to evaluate treatment efficacy in the future.

A Comprehensive Bioinformatic Analysis of NOTCH Pathway Involvement in Stomach Adenocarcinoma

Background

Activation of NOTCH signaling pathways, which are key regulators of multiple cellular functions, has been frequently implicated in cancer pathogenesis, and NOTCH inhibitors have received much recent focus in the context of cancer therapeutics. However, the role and possible involvement of NOTCH pathways in stomach adenocarcinoma (STAD) are unclear. Here, putative regulatory mechanisms and functions of NOTCH pathways in STAD were investigated.

Methods

Publicly available data from the TCGA-STAD database were utilized to explore the involvement of canonical NOTCH pathways in STAD by analyzing RNA expression levels of NOTCH receptors, ligands, and downstream genes. Statistical analysis of the data pertaining to cancer and noncancerous samples was performed using R software packages and public databases/webservers.

Results

Significant differential gene expression between control and STAD samples was noted for all NOTCH receptors (NOTCH1, 2, 3, and 4), the delta-like NOTCH ligands (DLL-3 and 4), and typical downstream genes (HES1 and HEY1). Four genes (NOTCH1, NOTCH2, NOTCH3, and HEY1) presented prognostic values for the STAD outcome in terms of overall survival. Functional enrichment analysis indicated that NOTCH family genes-strongly correlated genes were mainly enriched in several KEGG signaling pathways such as the PI3K-Akt signaling pathway, human papillomavirus infection, focal adhesion, Rap1 signaling pathway, and ECM-receptor interaction. Gene set enrichment analysis (GSEA) results showed that NOTCH family genes-significantly correlated genes were mainly enriched in four signaling pathways, ECM (extracellular matrix), tumor angiogenesis, inflammatory response, and immune regulation.

Conclusions

NOTCH family genes may play an essential role in the progression of STAD by modulating immune cells and mediating ECM synthesis, angiogenesis, focal adhesion, and PI3K-Akt signaling. Multiple NOTCH family genes are valuable candidate biomarkers or therapeutic targets for the management of STAD.

Aspects of the Epigenetic Regulation of EMT Related to Cancer Metastasis

Epithelial to mesenchymal transition (EMT) occurs during the pathological process associated with tumor progression and is considered to influence and promote the metastatic cascade. Characterized by loss of cell adhesion and apex base polarity, EMT enhances cell motility and metastasis. The key markers of the epithelial to mesenchymal transition are proteins characteristic of the epithelial phenotype, e.g., E-cadherin, cytokeratins, occludin, or desmoplakin, the concentration and activity of which are reduced during this process. On the other hand, as a result of acquiring the characteristics of mesenchymal cells, an increased amount of N-cadherin, vimentin, fibronectin, or vitronectin is observed. Importantly, epithelial cells undergo partial EMT where some of the cells show both epithelial and mesenchymal characteristics. The significant influence of epigenetic regulatory mechanisms is observed in the gene expression involved in EMT. Among the epigenetic modifications accompanying incorrect genetic reprogramming in cancer are changes in the level of DNA methylation within the CpG islands and posttranslational covalent changes of histone proteins. All observed modifications, which are stable but reversible changes, affect the level of gene expression leading to the development and progression of the disease, and consequently affect the uncontrolled growth of the population of cancer cells.

High S100A7 expression is associated with early muscle invasion and poor survival in bladder carcinoma

Muscle-invasive bladder carcinoma (MIBC) accounts for 25% of newly diagnosed bladder carcinomas (BCs) and presents a high risk of progression and metastasis. This study aimed to identify reliable biomarkers associated with muscle invasion and prognosis to identify potential therapeutic targets for MIBC. Four gene datasets were downloaded from the Gene Expression Omnibus, and the integrated differentially expressed genes (DEGs) were then subjected to gene ontology (GO) terms and pathway enrichment analyses. Correlation analysis between the expression of the top-ranking DEGs and pathological T stages was performed to identify the genes associated with early muscle invasion. The corresponding prognostic values were evaluated, and co-expressed genes mined in the cBioPortal database were loaded into ClueGo in Cytoscape for pathway enrichment analysis. Using data mining from the STRING and TCGA databases, protein-protein interaction and competitive endogenous RNA networks were constructed. In total, 645 integrated DEGs were identified and these were mainly enriched in 26 pathways, including cell cycle, bladder cancer, DNA replication, and PPAR signaling pathway. S100A7 expression was significantly increased from the T2 stage and showed significantly worse overall survival and disease-specific survival in patients with BC. In total, 144 genes co-expressed with S100A7 in BC were significantly enriched in the IL-17 pathway. S100A7 was predicted to directly interact with LYZ, which potentially shows competitive binding with hsa-mir-140 to affect the expression of six lncRNAs in MIBC. In conclusion, high S100A7 expression was predicted to be associated with early muscle invasion and poor survival in patients with BC.

Identification of a Pyroptosis-Related Gene Signature for Prediction of Overall Survival in Lung Adenocarcinoma

Pyroptosis is a kind of programmed cell death that is characterized by inflammation. However, the expression of pyroptosis-related genes and their connection with prognosis in lung adenocarcinoma (LUAD) remain unknown. The aim of this study is to create and validate a LUAD prediction signature based on genes associated with pyroptosis. The TCGA and GEO were used to collect gene sequencing data and clinical information for LUAD samples. To identify patients with LUAD from the TCGA cohort, consensus clustering by pyroptosis-related genes was employed. Our prognostic model was constructed using LASSO-Cox analysis after Cox regression using differentially expressed genes. To predict patient survival, we created a seven-mRNA signature. Additionally, reliability and validity were established in the GEO cohort. To assess its diagnostic and prognostic usefulness, an integrated bioinformatics method was used. Using a risk score with varying overall survival (OS) in two cohorts (all p < 0.001), a seven-gene signature was developed to categorize patients into two risk categories. The signature was shown to be an independent predictor of LUAD using multivariate regression analysis. The signature was linked to a variety of immune cell subtypes according to a study of immune cell infiltration. We constructed a signature consisting of seven genes as a robust biomarker with potential for clinical use in risk stratification and OS prediction in LUAD patients, as well as a potential indicator of immunotherapy in LUAD.

Imaging mass cytometry for high-dimensional tissue profiling in the eye

Background

Imaging mass cytometry (IMC) combines the principles of flow cytometry and mass spectrometry (MS) with laser scanning spatial resolution and offers unique advantages for the analysis of tissue samples in unprecedented detail. In contrast to conventional immunohistochemistry, which is limited in its application by the number of possible fluorochrome combinations, IMC uses isoptope-coupled antibodies that allow multiplex analysis of up to 40 markers in the same tissue section simultaneously.

Methods

In this report we use IMC to analyze formalin-fixed, paraffin-embedded conjunctival tissue. We performed a 18-biomarkers IMC analysis of conjunctival tissue to determine and summarize the possibilities, relevance and limitations of IMC for deciphering the biology and pathology of ocular diseases.

Results

Without modifying the manufacturer’s protocol, we observed positive and plausible staining for 12 of 18 biomarkers. Subsequent bioinformatical single-cell analysis and phenograph clustering identified 24 different cellular clusters with distinct expression profiles with respect to the markers used.

Conclusions

IMC enables highly multiplexed imaging of ocular samples at subcellular resolution. IMC is an innovative and feasible method, providing new insights into ocular disease pathogenesis that will be valuable for basic research, drug discovery and clinical diagnostics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12886-021-02099-8.

Whole-Genome Profiles of Malay Colorectal Cancer Patients with Intact MMR Proteins

Background: This study aimed to identify new genes associated with CRC in patients with normal mismatch repair (MMR) protein expression. Method: Whole-genome sequencing (WGS) was performed in seven early-age-onset Malay CRC patients. Potential germline genetic variants, including single-nucleotide variations and insertions and deletions (indels), were prioritized using functional and predictive algorithms. Results: An average of 3.2 million single-nucleotide variations (SNVs) and over 800 indels were identified. Three potential candidate variants in three genes—IFNE, PTCH2 and SEMA3D—which were predicted to affect protein function, were identified in three Malay CRC patients. In addition, 19 candidate genes—ANKDD1B, CENPM, CLDN5, MAGEB16, MAP3K14, MOB3C, MS4A12, MUC19, OR2L8, OR51Q1, OR51AR1, PDE4DIP, PKD1L3, PRIM2, PRM3, SEC22B, TPTE, USP29 and ZNF117—harbouring nonsense variants were prioritised. These genes are suggested to play a role in cancer predisposition and to be associated with cancer risk. Pathway enrichment analysis indicated significant enrichment in the olfactory signalling pathway. Conclusion: This study provides a new spectrum of insights into the potential genes, variants and pathways associated with CRC in Malay patients.

Bothrops Jararaca Snake Venom Modulates Key Cancer-Related Proteins in Breast Tumor Cell Lines

Cancer is characterized by the development of abnormal cells that divide in an uncontrolled way and may spread into other tissues where they may infiltrate and destroy normal body tissue. Several previous reports have described biochemical anti-tumorigenic properties of crude snake venom or its components, including their capability of inhibiting cell proliferation and promoting cell death. However, to the best of our knowledge, there is no work describing cancer cell proteomic changes following treatment with snake venoms. In this work we describe the quantitative changes in proteomics of MCF7 and MDA-MB-231 breast tumor cell lines following treatment with Bothrops jararaca snake venom, as well as the functional implications of the proteomic changes. Cell lines were treated with sub-toxic doses at either 0.63 μg/mL (low) or 2.5 μg/mL (high) of B. jararaca venom for 24 h, conditions that cause no cell death per se. Proteomics analysis was conducted on a nano-scale liquid chromatography coupled on-line with mass spectrometry (nLC-MS/MS). More than 1000 proteins were identified and evaluated from each cell line treated with either the low or high dose of the snake venom. Protein profiling upon venom treatment showed differential expression of several proteins related to cancer cell metabolism, immune response, and inflammation. Among the identified proteins we highlight histone H3, SNX3, HEL-S-156an, MTCH2, RPS, MCC2, IGF2BP1, and GSTM3. These data suggest that sub-toxic doses of B. jararaca venom have potential to modulate cancer-development related protein targets in cancer cells. This work illustrates a novel biochemical strategy to identify therapeutic targets against cancer cell growth and survival.

Developmental and sexual dimorphic atlas of the prenatal mouse external genitalia at the single-cell level

Birth defects of the external genitalia are among the most common in the world. Proper formation of the external genitalia requires a highly orchestrated process that involves special cell populations and sexually dimorphic hormone signaling. It is clear what the end result of the sexually dimorphic development is (a penis in the male versus clitoris in the female); however, the cell populations involved in the process remain poorly defined. Here, we used single-cell messenger RNA sequencing in mouse embryos to uncover the dynamic changes in cell populations in the external genitalia during the critical morphogenetic window. We found that overall, male and female external genitalia are largely composed of the same core cellular components. At the bipotential stage of development (embryonic day or E14.5), few differences in cell populational composition exist between male and female. Although similar in cell population composition, genetic differences in key sexual differentiation developmental pathways arise between males and females by the early (E16.5) and late (E18.5) differentiation stages. These differences include discrete cell populations with distinct responsiveness to androgen and estrogen. By late sexual differentiation (E18.5), unique cell populations in both male and female genitalia become apparent and are enriched with androgen- and estrogen-responsive genes, respectively. These data provide insights into the morphogenesis of the external genitalia that could be used to understand diseases associated with defects in the external genitalia.