CTHRC1 expression is a novel shared diagnostic and prognostic biomarker of survival in six different human cancer subtypes

Aberrant promoter methylation of CTHRC1 gene and its clinicopathological characteristics in head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) is genetically complex and difficult to treat. Detection in the early stage is challenging, leading to diagnosis at advanced stages with limited treatment options. This study examined the collagen triple helix repeat containing 1 gene (CTHRC1) as a potential biomarker and therapeutic target in HNSCC. Despite documented CTHRC1 upregulation in various cancers, the underlying causes remain unclear. The objective was to investigate potential epigenetic regulation of CTHRC1 expression through the analysis of promoter methylation. CTHRC1 DNA methylation, mRNA, and its protein expression were analysed using The Cancer Genome Atlas (TCGA) HNSCC cohort and oral squamous cell carcinoma (OSCC) patient samples. Functional analysis included scrutinizing the protein-protein interaction network and associations with DisGeNET (disease gene network). Various statistical methods were employed for analysis. HNSCC tumours exhibited significant hypomethylation of CTHRC1 DNA, correlating with advanced disease features. Elevated mRNA and protein expression of CTHRC1 further support its role in disease progression. High CTHRC1 gene expression was associated with a poorer prognosis. The protein interaction network implicated crucial pathways in cancer development and links to oral submucous fibrosis. Despite the limitations of this study, including the use of retrospective data and need for functional experiments, CTHRC1 shows potential as a prognostic predictor and target for therapeutic applications in HNSCC, paving the way for further research and improved patient management.

Interpretable niche-based cell‒cell communication inference using multi-view graph neural networks

Cell‒cell communication (CCC) is a fundamental biological process for the harmonious functioning of biological systems. Increasing evidence indicates that cells of the same type or cluster may exhibit different interaction patterns under varying niches, yet most prevailing methods perform CCC inference at the cell type or cluster level while disregarding niche heterogeneity. Here we introduce the Spatial Transcriptomics-based cell‒cell Communication And Subtype Exploration (STCase) tool, which can describe CCC events at the single-cell/spot level based on spatial transcriptomics (ST). STCase includes an interpretable multi-view graph neural network via CCC-aware attention to identify niches for each cell type and uncover niche-specific CCC events. We show that STCase outperforms state-of-the-art approaches and accurately captures reported immune-related CCC events in human bronchial glands. We also identify three distinct niches of oral squamous cell carcinoma that may be obscured by agglomerative methods, and discover niche-specific CCC events that could influence tumor prognosis.

Identification and functional characterization of hub genes CLTA, EDIL3, HAPLN1, and HIP1 as diagnostic biomarkers and therapeutic targets in thyroid cancer and Hashimoto's thyroiditis

In this study, we sought to identify key molecular players in both thyroid cancer (TC) and Hashimoto's thyroiditis (HT) by analyzing differentially expressed genes (DEGs) and their potential as biomarkers. We utilized datasets from the Gene Expression Omnibus (GEO) database and identified CLTA, EDIL3, HAPLN1, and HIP1 as hub genes common to both TC and HT. These genes were significantly upregulated in TC cell lines compared to normal controls, with high diagnostic accuracy as indicated by Receiver Operating Characteristic (ROC) curve analysis. Further validation using the TCGA TC dataset revealed their significant upregulation in tumor tissues, particularly in advanced TC stages. Promoter methylation analysis indicated hypomethylation of these genes in TC, suggesting a role of methylation in their regulation. We also observed mutations and copy number variations (CNVs) in these hub genes, with CLTA and HIP1 showing significant amplifications, which may contribute to their overexpression in tumor samples. In addition, we conducted a meta-analysis to assess the impact of these genes on survival outcomes in TC patients, with results indicating that higher expression of HAPLN1 and HIP1 was associated with poor survival. Our study also highlighted the involvement of CLTA and EDIL3 in activating the Rap1 signaling pathway, crucial for cancer cell migration, proliferation, and invasion. These findings emphasize the potential of CLTA, EDIL3, HAPLN1, and HIP1 as diagnostic biomarkers and therapeutic targets for TC and HT.

RETRACTED: Refining molecular subtypes and risk stratification of ovarian cancer through multi-omics consensus portfolio and machine learning

Ovarian cancer (OC), known for its pronounced heterogeneity, has long evaded a unified classification system despite extensive research efforts. This study integrated five distinct multi-omics datasets from eight multicentric cohorts, applying a combination of ten clustering algorithms and ninety-nine machine learning models. This methodology has enabled us to refine the molecular subtyping of OC, leading to the development of a novel Consensus Machine Learning-driven Signature (CMLS). Our analysis delineated two prognostically significant cancer subtypes (CS), each marked by unique genetic and immunological signatures. Notably, CS1 is associated with an adverse prognosis. Leveraging a subtype classifier, we identified five key genes (CTHRC1, SPEF1, SCGB3A1, FOXJ1, and C1orf194) instrumental in constructing the CMLS. Patients classified within the high CMLS group exhibited a poorer prognosis and were characterized by a "cold tumor" phenotype, indicative of an immunosuppressive microenvironment rich in MDSCs, CAFs, and Tregs. Intriguingly, this group also presented higher levels of tumor mutation burden (TMB) and tumor neoantigen burden (TNB), factors that correlated with a more favorable response to immunotherapy compared to their low CMLS counterparts. In contrast, the low CMLS group, despite also displaying a "cold tumor" phenotype, showed a favorable prognosis and a heightened responsiveness to chemotherapy. This study's findings underscore the potential of targeting immune-suppressive cells, particularly in patients with high CMLS, as a strategic approach to enhance OC prognosis. Furthermore, the redefined molecular subtypes and risk stratification, achieved through sophisticated multi-omics analysis, provide a framework for the selection of therapeutic agents.

Comprehensive investigation of matrix metalloproteinases in skin cutaneous melanoma: diagnostic, prognostic, and therapeutic insights

The dysregulation of matrix metalloproteinases (MMPs) in skin cutaneous melanoma (SKCM) represents a critical aspect of tumorigenesis. In this study, we investigated the diagnostic, prognostic, and therapeutic aspects of the MMPs in SKCM. Thirteen SKCM cell lines and seven normal skin cell lines were cultured under standard conditions for experimental analyses. RNA and DNA were extracted, followed by RT-qPCR to assess MMP expression and promoter methylation analysis to determine methylation levels. Functional assays, including cell proliferation, colony formation, and wound healing, were conducted post-MMP7 knockdown using siRNA in A375 cells. Databases like GEPIA2, HPA, MEXPRESS, and miRNet were employed for expression, survival, methylation, and miRNA-mRNA network analyses. We investigated the expression and promoter methylation landscape of MMPs in SKCM cell lines, revealing significant (p-value < 0.05) up-regulation of MMP1, MMP7, MMP9, MMP10, MMP11, MMP12, MMP13, MMP14, and MMP25, alongside down-regulation of MMP2, MMP3, and MMP21. Furthermore, our analysis demonstrated a significant (p-value < 0.05) inverse correlation between MMP expression levels and promoter methylation status, suggesting a potential regulatory role of DNA methylation in MMP dysregulation. Notably, MMP7, MMP11, and MMP14 exhibited significant (p-value < 0.05) associations with the overall survival of SKCM patients, emphasizing their prognostic significance. Additionally, Receiver operating characteristic (ROC) curve analysis highlighted the significant (p-value < 0.05) diagnostic potential of MMP7, MMP11, and MMP14 in distinguishing SKCM from normal individuals. Subsequent validation across multiple cohorts confirmed significant (p-value < 0.05) elevated MMP expression levels in SKCM tissues, particularly in advanced disease stages, further emphasizing their role in tumor progression. Furthermore, we elucidated potential regulatory pathways involving miR-22-3p, which targets MMP7, MMP11, and MMP14 genes in SKCM. Our findings also revealed associations between MMP expression and immune modulation, drug sensitivity, and functional states of SKCM cells. Lastly, MMP7 knockdown in A375 cells significantly significant (p-value < 0.05) impacted several characteristics, including cell proliferation, colony formation, and wound healing. Our findings highlight the diagnostic, prognostic, and therapeutic potential of MMP7, MMP11, and MMP14 in SKCM. These MMPs could serve as biomarkers for early detection and targets for therapy. Future efforts should focus on preclinical and clinical validation to translate these insights into personalized diagnostic and therapeutic strategies.

Mechanisms and technologies in cancer epigenetics

Cancer's epigenetic landscape, a labyrinthine tapestry of molecular modifications, has long captivated researchers with its profound influence on gene expression and cellular fate. This review discusses the intricate mechanisms underlying cancer epigenetics, unraveling the complex interplay between DNA methylation, histone modifications, chromatin remodeling, and non-coding RNAs. We navigate through the tumultuous seas of epigenetic dysregulation, exploring how these processes conspire to silence tumor suppressors and unleash oncogenic potential. The narrative pivots to cutting-edge technologies, revolutionizing our ability to decode the epigenome. From the granular insights of single-cell epigenomics to the holistic view offered by multi-omics approaches, we examine how these tools are reshaping our understanding of tumor heterogeneity and evolution. The review also highlights emerging techniques, such as spatial epigenomics and long-read sequencing, which promise to unveil the hidden dimensions of epigenetic regulation. Finally, we probed the transformative potential of CRISPR-based epigenome editing and computational analysis to transmute raw data into biological insights. This study seeks to synthesize a comprehensive yet nuanced understanding of the contemporary landscape and future directions of cancer epigenetic research.

CTHRC1 is associated with BRAF(V600E) mutation and correlates with prognosis, immune cell infiltration, and drug resistance in colon cancer, thyroid cancer, and melanoma

Colon cancer, thyroid cancer, and melanoma are common malignant tumors that seriously threaten human health globally. The B-Raf proto-oncogene, serine/threonine kinase (BRAF)(V600E) mutation is an important driver gene mutation in these cancer types. In this study, we identified that collagen triple helix repeat containing 1 (CTHRC1) expression was associated with the BRAF(V600E) mutation in colon cancer, thyroid cancer, and melanoma. Based on database analysis and clinical tissue studies, CTHRC1 was verified to correlate with poor prognosis and worse clinicopathological features in colon cancer and thyroid cancer patients, but not in patients with melanoma. Several signaling pathways, immune cell infiltration, and immunotherapy markers were associated with CTHRC1 expression. Additionally, a high level of CTHRC1 was correlated with decreased sensitivity to antitumor drugs (vemurafenib, PLX-4720, dabrafenib, and SB-590885) targeting the BRAF(V600E) mutation. This study provides evidence of a significant correlation between CTHRC1 and the BRAF(V600E) mutation, suggesting its potential utility as a diagnostic and prognostic biomarker in human colon cancer, thyroid cancer, and melanoma.

Investigating the clinical significance of OAS family genes in breast cancer: an in vitro and in silico study

BACKGROUND

Breast cancer is the most common malignancy among women worldwide, characterized by complex molecular and cellular heterogeneity. Despite advances in diagnosis and treatment, there is an urgent need to identify reliable biomarkers and therapeutic targets to improve early detection and personalized therapy. The OAS (2'-5'-oligoadenylate synthetase) family genes, known for their roles in antiviral immunity, have emerged as potential regulators in cancer biology. This study aimed to explore the diagnostic and functional relevance of OAS family genes in breast cancer.

METHODOLOGY

Breast cancer cell lines and controls were cultured under specific conditions, and DNA and RNA were extracted for downstream analyses. RT-qPCR, bisulfite sequencing, and Western blotting were employed to assess gene expression, promoter methylation, and knockdown efficiency of OAS family genes. Functional assays, including CCK-8, colony formation, and wound healing, evaluated cellular behaviors, while bioinformatics tools (UALCAN, GEPIA, HPA, OncoDB, cBioPortal, and others) validated findings and explored correlations with clinical data.

RESULTS

The OAS family genes (OAS1, OAS2, OAS3, and OASL) were found to be significantly upregulated in breast cancer cell lines and tissues compared to normal controls. This overexpression was strongly associated with reduced promoter methylation. Receiver operating characteristic (ROC) analysis demonstrated high diagnostic accuracy, with area under the curve (AUC) values exceeding 0.93 for all four genes. Increased OAS expression correlated with advanced cancer stages and poor overall survival in breast cancer patients. Functional analysis revealed their involvement in critical biological processes, including immune modulation and oncogenic pathways. Silencing OAS genes in breast cancer cells significantly inhibited cell proliferation and colony formation, while unexpectedly enhancing migratory capacity. Additionally, correlations with immune cell infiltration, molecular subtypes, and drug sensitivity highlighted their potential roles in the tumor microenvironment and therapeutic response.

CONCLUSION

The findings of this study established OAS family genes as potential biomarkers and key players in breast cancer progression, offering promise as diagnostic biomarkers and therapeutic targets to address unmet clinical needs.

Machine learning approach to predict blood-secretory proteins and potential biomarkers for liver cancer using omics data

Identifying non-invasive blood-based biomarkers is crucial for early detection and monitoring of liver cancer (LC), thereby improving patient outcomes. This study leveraged computational approaches to predict potential blood-based biomarkers for LC. Machine learning (ML) models were developed using selected features from blood-secretory proteins collected from the curated databases. The logistic regression (LR) model demonstrated the optimal performance. Transcriptome analysis across 7 LC cohorts revealed 231 common differentially expressed genes (DEGs). The encoded proteins of these DEGs were compared with the ML dataset, revealing 29 proteins overlapping with the blood-secretory dataset. The LR model also predicted 29 additional proteins as blood-secretory with the remaining protein-coding genes. As a result, 58 potential blood-secretory proteins were obtained. Among the top 20 genes, 13 common hub genes were identified. Further, area under the receiver operating characteristic curve (ROC AUC) analysis was performed to assess the genes as potential diagnostic blood biomarkers. Six genes, ESM1, FCN2, MDK, GPC3, CTHRC1 and COL6A6, exhibited an AUC value higher than 0.85 and were predicted as blood-secretory. This study highlights the potential of an integrative computational approach for discovering non-invasive blood-based biomarkers in LC, facilitating for further validation and clinical translation. SIGNIFICANCE: Liver cancer is one of the leading causes of premature death worldwide, with its prevalence and mortality rates projected to increase. Although current diagnostic methods are highly sensitive, they are invasive and unsuitable for repeated testing. Blood biomarkers offer a promising non-invasive alternative, but their wide dynamic range of protein concentration poses experimental challenges. Therefore, utilizing available omics data to develop a diagnostic model could provide a potential solution for accurate diagnosis. This study developed a computational method integrating machine learning and bioinformatics analysis to identify potential blood biomarkers. As a result, ESM1, FCN2, MDK, GPC3, CTHRC1 and COL6A6 biomarkers were identified, holding significant promise for improving diagnosis and understanding of liver cancer. The integrated method can be applied to other cancers, offering a possible solution for early detection and improved patient outcomes.

CTHRC1 modulates cell proliferation and invasion in hepatocellular carcinoma by DNA methylation

BACKGROUND

Collagen triple helix repeat containing-1 (CTHRC1), an extracellular matrix protein, is highly expressed in hepatocellular carcinoma (HCC) and linked to poor prognosis. Nevertheless, the precise mechanism of CTHRC1 in HCC is unclear.

METHODS

Agena MassARRAY® Methylation Analysis assessed the methylation level of CTHRC1 in the promoter region. Functional assays were conducted to investigate the effects of CTHRC1 knockdown in Hep3B2.1 cells. RNA sequencing identified differentially expressed genes and lncRNAs associated with angiogenesis after CTHRC1 knockdown. Furthermore, differential alternative splicing (AS) and gene fusion events were analyzed using rMATS and Arriba.

RESULTS

In HCC cell lines, CTHRC1 was highly expressed and associated with hypomethylation. Downregulation of CTHRC1 inhibited Hep3B2.1 cell proliferation, migration, and invasion, blocked cells in the G1/S phase, and promoted apoptosis. We obtained 34 mRNAs and 7 lncRNAs differentially expressed between the NC and CTHRC1 inhibitor groups. Additionally, we found 4 angiogenesis-related mRNAs and lncRNAs significantly correlated with CTHRC1. RT-qPCR results showed that knockdown of CTHRC1 in Hep3B2.1 cells resulted in significantly aberrant expression of CXCL6, LINC02127, and AC020978.8. Moreover, the role of CTHRC1 in HCC development may be associated with events, like 12 AS events and 5 pairs of fusion genes.

CONCLUSIONS

High expressed CTHRC1 is associated with hypomethylation and may promote HCC development, involving events like angiogenesis, alternative splicing, and gene fusion.

CTHRC1+ fibroblasts and SPP1+ macrophages synergistically contribute to pro-tumorigenic tumor microenvironment in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an extremely lethal cancer that accounts for over 90% of all pancreatic cancer cases. With a 5-year survival rate of only 13%, PDAC has proven to be extremely desmoplastic and immunosuppressive to most current therapies, including chemotherapy and surgical resection. In recent years, focus has shifted to understanding the tumor microenvironment (TME) around PDAC, enabling a greater understanding of biological pathways and intercellular interactions that can ultimately lead to potential for future drug targets. In this study, we leverage a combination of single-cell and spatial transcriptomics to further identify cellular populations and interactions within the highly heterogeneous TME. We demonstrate that SPP1+APOE+ tumor-associated macrophages (TAM) and CTHRC1+GREM1+ cancer-associated myofibroblasts (myCAF) not only act synergistically to promote an immune-suppressive TME through active extracellular matrix (ECM) deposition and epithelial mesenchymal transition (EMT), but are spatially colocalized and correlated, leading to worse prognosis. Our results highlight the crosstalk between stromal and myeloid cells as a significant area of study for future therapeutic targets to treat cancer.

Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

BACKGROUND

Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.

METHODS

CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.

RESULTS

A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]).

CONCLUSION

We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.

The role of collagen triple helix repeat containing 1 (CTHRC1) in cancer development and progression

INTRODUCTION

Collagen triple helix repeat containing 1 (CTHRC1) is a protein that has been implicated in pro-migratory pathways, arterial tissue-repair processes, and inhibition of collagen deposition via the regulation of multiple signaling cascades. Studies have also demonstrated an upregulation of CTHRC1 in multiple cancers where it has been linked to enhanced proliferation, invasion, and metastasis. However, the understanding of the exact role and mechanisms of CTHRC1 in cancer is far from complete.

AREAS COVERED

This review focuses on analyzing the role of CTHRC1 in cancer as well as its associations with clinicopathologies and cancer-related processes and signaling. We have also summarized the available literature information regarding the role of CTHRC1 in tumor microenvironment and immune signaling. Finally, we have discussed the mechanisms associated with CTHRC1 regulations, and opportunities and challenges regarding the development of CTHRC1 as a potential target for cancer management.

EXPERT OPINION

CTHRC1 is a multifaceted protein with critical roles in cancer progression and other pathological conditions. Its association with lower overall survival in various cancers, and impact on the tumor immune microenvironment make it an intriguing target for further research and potential therapeutic interventions in cancer.

MIR4435-2HG as a possible novel predictive biomarker of chemotherapy response and death in pediatric B-cell ALL

Introduction: Although B-cell acute lymphoblastic leukemia (B-cell ALL) survival rates have improved in recent years, Hispanic children continue to have poorer survival rates. There are few tools available to identify at the time of diagnosis whether the patient will respond to induction therapy. Our goal was to identify predictive biomarkers of treatment response, which could also serve as prognostic biomarkers of death, by identifying methylated and differentially expressed genes between patients with positive minimal residual disease (MRD+) and negative minimal residual disease (MRD-). Methods: DNA and RNA were extracted from tumor blasts separated by immunomagnetic columns. Illumina MethlationEPIC and mRNA sequencing assays were performed on 13 bone marrows from Hispanic children with B-cell ALL. Partek Flow was used for transcript mapping and quantification, followed by differential expression analysis using DEseq2. DNA methylation analyses were performed with Partek Genomic Suite and Genome Studio. Gene expression and differential methylation were compared between patients with MRD-/- and MRD+/+ at the end of induction chemotherapy. Overexpressed and hypomethylated genes were selected and validated by RT-qPCR in samples of an independent validation cohort. The predictive ability of the genes was assessed by logistic regression. Survival and Cox regression analyses were performed to determine the association of genes with death. Results: DAPK1, BOC, CNKSR3, MIR4435-2HG, CTHRC1, NPDC1, SLC45A3, ITGA6, and ASCL2 were overexpressed and hypomethylated in MRD+/+ patients. Overexpression was also validated by RT-qPCR. DAPK1, BOC, ASCL2, and CNKSR3 can predict refractoriness, but MIR4435-2HG is the best predictor. Additionally, higher expression of MIR4435-2HG increases the probability of non-response, death, and the risk of death. Finally, MIR4435-2HG overexpression, together with MRD+, are associated with poorer survival, and together with overexpression of DAPK1 and ASCL2, it could improve the risk classification of patients with normal karyotype. Conclusion: MIR4435-2HG is a potential predictive biomarker of treatment response and death in children with B-cell ALL.

Identifying and validating MMP family members (MMP2, MMP9, MMP12, and MMP16) as therapeutic targets and biomarkers in kidney renal clear cell carcinoma (KIRC)

Kidney Renal Clear Cell Carcinoma (KIRC) is a malignant tumor that carries a substantial risk of morbidity and mortality. The MMP family assumes a crucial role in tumor invasion and metastasis. This study aimed to uncover the mechanistic relevance of the MMP gene family as a therapeutic target and diagnostic biomarker in Kidney Renal Clear Cell Carcinoma (KIRC) through a comprehensive approach encompassing both computational and molecular analyses. STRING, Cytoscape, UALCAN, GEPIA, OncoDB, HPA, cBioPortal, GSEA, TIMER, ENCORI, DrugBank, targeted bisulfite sequencing (bisulfite-seq), conventional PCR, Sanger sequencing, and RT-qPCR based analyses were used in the present study to analyze MMP gene family members to accurately determine a few hub genes that can be utilized as both therapeutic targets and diagnostic biomarkers for KIRC. By performing STRING and Cytohubba analyses of the 24 MMP gene family members, MMP2 (matrix metallopeptidase 2), MMP9 (matrix metallopeptidase 9), MMP12 (matrix metallopeptidase 12), and MMP16 (matrix metallopeptidase 16) genes were denoted as hub genes having highest degree scores. After analyzing MMP2, MMP9, MMP12, and MMP16 via various TCGA databases and RT-qPCR technique across clinical samples and KIRC cell lines, interestingly, all these hub genes were found significantly overexpressed at mRNA and protein levels in KIRC samples relative to controls. The notable effect of the up-regulated MMP2, MMP9, MMP12, and MMP16 was also documented on the overall survival (OS) of the KIRC patients. Moreover, targeted bisulfite-sequencing (bisulfite-seq) analysis revealed that promoter hypomethylation pattern was associated with up-regulation of hub genes (MMP2, MMP9, MMP12, and MMP16). In addition to this, hub genes were involved in various diverse oncogenic pathways. The MMP gene family members (MMP2, MMP9, MMP12, and MMP16) may serve as therapeutic targets and prognostic biomarkers in KIRC.

Bone morphogenetic protein 1: a prognostic indicator and potential biomarker in three cancer types

BACKGROUND

Bone morphogenetic protein 1 (BMP1) is a metalloprotease that plays a role in activating both transforming growth factor-β (TGF-β) and BMP signaling pathways. TGF-β has been identified as a factor initiating and facilitating cancer development. Consequently, we propose the hypothesis that dysregulation of BMP1 could potentially contribute to the onset and advancement of human cancers.

METHODS

In this research, we aimed to analyze BMP1 expression level and the associated clinical outcomes across various cancers using online cancer OMICS databases, advanced Bioinformatics tools, and molecular analyses.

RESULTS

The outcomes of our web server-based expression analysis indicated an up-regulation of BMP1 in a majority of the human cancers examined. External validation using clinical samples also showed higher expression of BMP1. Moreover, heightened BMP1 expression exhibited a noteworthy correlation with reduced overall survival (OS) duration in Bladder Cancer (BLCA), Kidney Renal Clear Cell Carcinoma (KIRC), and Lung Adenocarcinoma (LUAD) patients. This suggests a substantial involvement of the BMP1 gene in the development and progression of these three types of cancers. The major signaling pathways related with BMP1 enriched genes were "ECM-receptor interaction, Amoebiasis, Focal adhesion, Protein digestion and absorption, progesterone-mediated, PI3K-Akt signaling pathway, and platelet activation". Moreover, we also explored some interesting correlations among BMP1 expression and its DNA promoter methylation level, CD8+ T immune cells level, and genetic variations.

CONCLUSION

In conclusion, our study has provided some solid basis for BMP1 to be used as a reliable common biomarker for BLCA, KIRC, and LUAD patients.

Deciphering DNA repair gene mutational landscape in uterine corpus endometrial carcinoma patients using next generation sequencing

Uterine Corpus Endometrial Carcinoma (UCEC) is a significant health concern with a complex genetic landscape impacting disease susceptibility and progression. This study aimed to unravel the spectrum of DNA repair gene mutations in Pakistani UCEC patients through Next Generation Sequencing (NGS) and explore their potential functional consequences via downstream analyses. NGS analysis of genomic DNA from 30 UCEC patients was conducted to identify clinically significant pathogenic mutations in DNA repair genes. This analysis revealed mutations in 4 key DNA repair genes: BRCA1, BRCA2, APC, and CDH1. Kaplan-Meier (KM) analysis was employed to assess the prognostic value of these mutations on patient overall survival (OS) in UCEC. To delve into the functional impact of these mutations, we performed RT-qPCR, immunohistochemistry (IHC), and western blot analyses on the mutated UCEC samples compared to their non-mutated counterparts. These results unveiled the up-regulation in the expression of the mutated genes, suggesting a potential association between the identified mutations and enhanced gene activity. Additionally, targeted bisulfite sequencing analysis was utilized to evaluate DNA methylation patterns in the promoters of the mutated genes. Strikingly, hypomethylation in the promoters of BRCA1, BRCA2, APC, and CDH1 was observed in the mutated UCEC samples relative to the non-mutated, indicating the involvement of epigenetic mechanisms in the altered gene expression. In conclusion, this study offers insights into the genetic landscape of DNA repair gene mutations in Pakistani UCEC patients. The presence of pathogenic mutations in BRCA1, BRCA2, APC, and CDH1, coupled with their down-regulation and hypermethylation, suggests a convergence of genetic and epigenetic factors contributing to genomic instability in UCEC cells. These findings enhance our understanding of UCEC susceptibility and provide potential avenues for targeted therapeutic interventions in Pakistani UCEC patients.

Unlocking the diagnostic, prognostic roles, and immune implications of BAX gene expression in pan-cancer analysis

OBJECTIVES

Cancer, a formidable disease, continues to challenge our understanding and therapeutic approaches. This study delves into the pan-cancer analysis of BCL2 Associated X (BAX) gene expression, seeking to unravel its significance in cancer development, prognosis, and potential therapeutic strategies.

METHODS

A combination of bioinformatics and molecular experiments.

RESULTS

Our pan-cancer investigation into BAX expression encompassed 33 distinct cancer types, revealing a remarkable and uniform increase in BAX expression. This groundbreaking finding emphasizes the potential universality of BAX's role in cancer development and progression. Further, our study explored the prognostic implications of BAX expression, highlighting a consistent association between up-regulated BAX and poor overall survival (OS) in Liver Hepatocellular Carcinoma (LIHC) and Skin Cutaneous Melanoma (SKCM). These results suggest that BAX may serve as an adverse prognostic indicator in these malignancies, emphasizing the importance of personalized treatment strategies. Epigenetic and genetic analyses of BAX provided valuable insights. Hypomethylation of the BAX promoter region was evident in LIHC and SKCM, which likely contributes to the up-regulation of BAX, while genetic mutations in the BAX gene itself were infrequent in these cancers. Our exploration of BAX-associated signaling pathways and the correlation between BAX expression and CD8+ T cell infiltration shed light on the intricate molecular landscape of cancer. BAX's interaction with key apoptotic and immune-related pathways reinforces its role as a central player in tumor development and the immune microenvironment. Moreover, our drug prediction analysis identified potential therapeutic agents for modulating BAX expression in the context of LIHC and SKCM, bridging the gap between research and clinical application.

CONCLUSION

In sum, our comprehensive BAX study not only enhances our understanding of its significance as a biomarker gene but also offers novel avenues for therapeutic interventions, contributing to the ongoing quest for more effective cancer treatments and improved patient care.

CTHRC1 promotes colorectal cancer progression by recruiting tumor-associated macrophages via up-regulation of CCL15

Tumor-associated macrophages (TAMs) represent a key factor in the tumor immune microenvironment (TME), exerting significant influence over tumor migration, invasion, immunosuppressive features, and drug resistance. Collagen triple helix repeat containing 1 (CTHRC1), a 30 KDa protein which was secreted during the tissue-repair process, is highly expressed in several malignant tumors, including colorectal cancer (CRC). Previous studies demonstrated that CTHRC1 expression in TAMs was positively correlated to M2 macrophage polarization and liver metastasis, while our discovery suggesting a novel mechanism that CTHRC1 secreted from cancer cell could indirectly interplay with TAMs. In this study, the high expression level of CTHRC1 was evaluated in CRC based on GEO and TCGA databases. Further, CTHRC1 was detected high in all stages of CRC patients by ELISA and was correlated to poor prognosis. Multispectral imaging of IHC demonstrated that M2 macrophage infiltration was increased accompanied with CTHRC1 enrichment, suggesting that CTHRC1 may have chemotactic effect on macrophages. In vitro, CTHRC1 could have chemotactic ability of macrophage in the presence of HT-29 cell line. Cytokine microarray revealed that CTHRC1 could up-regulate the CCL15 level of HT-29, pathway analysis demonstrated that CTHRC1 could regulate CCL15 by controlling the TGFβ activation and Smad phosphorylation level. In vivo, knocking down of CTHRC1 from CT-26 also inhibits tumor formation. In conclusion, CTHRC1 could promote the chemotactic ability of macrophages by up-regulating CCL15 via TGFβ/Smad pathway; additionally, a high level of CTHRC1 could promote macrophage's M2 polarization. This discovery may be related to tumor immune tolerance and tumor immunotherapy resistance in CRC. KEY MESSAGES: CTHRC1 promotes CRC progression by up-regulating CCL15 via TGF-β/Smad pathways to further recruit tumor-associated macrophages. By the means of autocrine or paracrine, CTHRC1 can indeed promote macrophage chemotaxis and enhance the infiltration of macrophages in tumor tissues but in the presence of tumor cells. CAFs were another source of CTHRC1, indicating CTHRC1 can infiltrate tumor islet as well as the stomal and be secreted from both tumor cells and CAFs. This study validated CTHRC1 as a potential immune therapy target CRC.

Deciphering key genes involved in cisplatin resistance in kidney renal clear cell carcinoma through a combined in silico and in vitro approach

The low survival rate of Kidney renal clear cell carcinoma (KIRC) patients is largely attributed to cisplatin resistance. Rather than focusing solely on individual proteins, exploring protein-protein interactions could offer greater insight into drug resistance. To this end, a series of in silico and in vitro experiments were conducted to identify hub genes in the intricate network of cisplatin resistance-related genes in KIRC chemotherapy. The genes involved in cisplatin resistance across KIRC were retrieved from the National Center for Biotechnology Information (NCBI) database using search terms as "Kidney renal clear cell carcinoma" and "Cisplatin resistance". The genes retrieved were analyzed for hub gene identification using the STRING database and Cytoscape tool. Expression and promoter methylation profiling of the hub genes was done using UALCAN, GEPIA, OncoDB, and HPA databases. Mutational, survival, functional enrichment, immune cell infiltration, and drug prediction analyses of the hub genes were performed using the cBioPortal, GEPIA, GSEA, TIMER, and DrugBank databases. Lastly, expression and methylation levels of the hub genes were validated on two cisplatin-resistant RCC cell lines (786-O and A-498) and a normal renal tubular epithelial cell line (HK-2) using two high throughput techniques, including targeted bisulfite sequencing (bisulfite-seq) and RT-qPCR. A total of 124 genes were identified as being associated with cisplatin resistance in KIRC. Out of these genes, MCL1, IGF1R, CCND1, and PTEN were identified as hub genes and were found to have significant (p < 0.05) variations in their mRNA and protein expressions and effects on the overall survival (OS) of the KIRC patients. Moreover, an aberrant promoter methylation pattern was found to be associated with the dysregulation of the hub genes. In addition to this, hub genes were also linked with different cisplatin resistance-causing pathways. Thus, hub genes can be targeted with Alvocidib, Estradiol, Tretinoin, Capsaicin, Dronabinol, Metribolone, Calcitriol, Acetaminophen, Acitretin, Cyclosporine, Azacitidine, Genistein, and Resveratrol drugs. As the pathogenesis of KIRC is complex, targeting hub genes and associated pathways involved in cisplatin resistance could bring a milestone change in the drug discovery and management of drug resistance, which might uplift overall survival among KIRC patients.

Characterization and verification of MMP family members as potential biomarkers in kidney clear cell renal carcinoma

Renal cell carcinoma can arise from lesions in the renal epithelium. This particular type of cancer is prevalent in the realm of renal cancers and is associated with an unfavorable prognosis. Among these cases, over 70% are classified as kidney renal clear cell carcinoma (KIRC). Since the underlying causes of KIRC haven't been fully understood, there is an urgent need for deeper investigation into its pathogenesis. Various tools, software, and molecular analysis was used, including Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Cytoscape, University of ALabama at Birmingham CANcer data analysis Portal (UALCAN), muTarget, Gene Expression Profiling Interactive Analysis (GEPIA), OncoDB, Human Protein Atlas (HPA), cBioPortal, Kaplan-Meier (KM) plotter, Gene Set Enrichment Analysis (GSEA), Tumor IMmune Estimation Resource (TIMER), Encyclopedia of RNA Interactomes (ENCORI), DrugBank, Encyclopedia of RNA Interactomes (RT-qPCR), targeted bisulfide sequencing (bisulfide-seq), and receiver operating curve (ROC) to matrix metallopeptidase (MMP) gene family constituents, with the precise objective of identifying a small set of hub genes. These hub genes hold the potential to be harnessed as molecular biomarkers for KIRC. By performing STRING and CytoHubba analyses of the 24 MMP gene family members, MMP2 (matrix metallopeptidase 2), MMP9 (matrix metallopeptidase 9), MMP14 (matrix metallopeptidase 14), and MMP16 (matrix metallopeptidase 16) were recognized as hub genes having highest degree scores. After conducting an in-depth expression analysis of MMP2, MMP9, MMP14, and MMP16 using various The Cancer Genome Atlas (TCGA) databases and RT-qPCR techniques, these displayed a significant increase in expression at both the mRNA and protein levels within KIRC samples when compared to control samples. The impact of the over expression of MMP2, MMP9, MMP14, and MMP16 also left a distinct mark on the worst overall survival (OS) rates of KIRC patients. Furthermore, a targeted bisulfide-seq investigation unveiled a correlation between promoter hypomethylation patterns and the up-regulation of these key genes in KIRC patients. Additionally, hub genes were involved in various diverse oncogenic pathways. In conclusion, four MMP gene family members, including MMP2, MMP9, MMP14, and MMP16 may serve as therapeutic target and molecular biomarker in KIRC.

CTHRC1 Induces Pancreatic Stellate Cells (PSCs) into Myofibroblast-like Cancer-Associated Fibroblasts (myCAFs)

[BACKGROUND] Collagen triple helix repeat containing-1 (CTHRC1) is a secreted protein that contributes to the progression of various cancers, including pancreatic cancer. The higher expression of CTHRC1 in tumor tissues is associated with poorer survival outcomes. However, its specific roles in tumor extracellular matrix (ECM) remodeling remain unclear. Our study aims to investigate the influences of CTHRC1 on pancreatic stellate cells (PSCs), a main source of ECM production in pancreatic cancer. [METHODS AND RESULTS] The analyses of the publicly available pancreatic cancer patient data revealed that CTHRC1 is mainly expressed in cancer stroma and highly correlated with ECM-related genes. An in vitro study showed that more than 40% of these genes can be upregulated by CTHRC1. CTHRC1 specifically activated PSC into myofibroblast-like cancer-associated fibroblasts (myCAFs), which are characterized by a significantly upregulated POSTN gene expression. Periostin (coded by the POSTN gene) has a central role in the CTHRC1-PSCs-cancer metastasis axis. Furthermore, CTHRC1 promoted pancreatic cancer cell proliferation through PSC activation to a greater extent than via direct stimulation. Proof-of-concept experiments showed that the long-term (4-week) inhibition of CTHRC1 led to significant tumor suppression and ECM reduction, and also resulted in an unexpected shift in the CAF subtype from myCAFs to inflammatory CAFs (iCAFs). [CONCLUSION] PSC activation was demonstrated to be the key molecular mechanism responsible for the tumor-promoting effects of CTHRC1, and CTHRC1 has a critical role in CAF subtype differentiation and tumor microenvironment (TME) remodeling. The inhibition of CTHRC1 as a therapeutic strategy for the treatment of pancreatic cancer warrants further investigation.

CTHRC1, a novel gene with multiple functions in physiology, disease and solid tumors (Review)

Collagen triple helix repeat containing 1 (CTHRC1) is a gene discovered in 2005; it is highly conserved, and no homologous proteins have been disclosed thus far. A number of studies have shown that CTHRC1 is present in normal tissues and organs, and it has vital functions in physiological processes, including participating in the regulation of metabolism, arterial remodeling, bone formation and myelination of the peripheral nervous system. It has been reported that abnormal expression of CTHRC1 is involved in the carcinogenesis of various human organs, such as the breast, colon, pancreas, lung, stomach and liver. Therefore, the present review aims to collate all known findings and results on the regulation of CTHRC1 expression and related signaling pathways. To conclude, this review also provides a hypothesis of the functional mechanism of this gene.

CTHRC1 promotes anaplastic thyroid cancer progression by upregulating the proliferation, migration, and invasion of tumor cells

Anaplastic thyroid carcinoma (ATC) is an extremely aggressive tumor with a high mortality rate and poor prognosis. However, the pathogenesis of ATC is complex and poorly understood, and the effective treatment options are limited. Analysis of data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases showed that collagen triple helix repeat containing-1 (CTHRC1) was specifically upregulated in ATC tissues and was negatively correlated with overall survival (OS) in thyroid carcinoma patients. In vitro knockdown of CTHRC1 dramatically decreased the proliferation, migration, and invasion abilities of ATC cells, and in vivo studies in BALB/c nude mice confirmed that CTHRC1 knockdown significantly inhibited tumor growth. Mechanistically, CTHRC1 knockdown was found to suppress the Wnt/β-catenin pathway and epithelial-mesenchymal transition (EMT) at the protein level. These findings suggest that CTHRC1 promotes the progression of ATC via upregulating tumor cell proliferation, migration, and invasion, which may be achieved by activating the Wnt/β-catenin pathway and EMT.

CTHRC1 is associated with immune cell infiltration and functions as an adverse marker for prognosis in head and neck squamous cell carcinoma

Collagen triple helix repeat containing 1 (CTHRC1) is a secreted glycoprotein that decreases the deposition of collagen matrix and accelerates tumor metastasis. However, the relationship between CTHRC1 and the outcomes of head and neck squamous cell carcinoma (HNSCC) and tumor-infiltrating lymphocytes remains unclear. In the present study, the transcriptional level of CTHRC1 and its association with overall survival (OS) and relapse-free survival (RFS) time in diverse cancer types were evaluated using The Cancer Genome Atlas, Tumor Immune Estimation Resource (TIMER), ONCOMINE and Kaplan-Meier plotter databases. The association of CTHRC1 expression level with the clinicopathological parameters of patients with HNSCC from The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) database were also evaluated. Enrichment analysis of CTHRC1 was carried out using gene set enrichment analysis software. CIBERSORT and TIMER databases were used to evaluate the relationship between the expression level of CTHRC1 and the proportion of tumor-infiltrating immune cells (TICs) in multiple cancer types. Moreover, immunohistochemistry was used to verify the expression of CTHRC1 in clinical samples of HNSCC. CTHRC1 was upregulated in HNSCC and high expression of CTHRC1 was associated with worsening clinicopathologic parameters and shorter OS and RFS times. There were eight HALLMARK gene sets, 1,231 immune signature gene sets and 14 KEGG gene sets significantly enriched in the high CTHRC1 expression group, while no gene set was enriched in the low CTHRC1 expression group. The expression of CTHRC1 was closely correlated with the proportion of TICs, where the expression of CTHRC1 was significantly positively correlated with the amount of infiltrated M0 and M2 macrophages, and significantly negatively associated with the levels of M1 macrophages. These findings suggest that CTHRC1 is an adverse prognostic marker and is associated with immune cell infiltration in HNSCC.

Elevated Levels of Plasma Collagen Triple Helix Repeat Containing 1 (CTHRC1) Is Strongly Associated with eGFR and Albuminuria in Chronic Kidney Disease

Background: Chronic kidney disease (CKD) has various etiologies, making it impossible to fully understand its complex pathophysiology. Elevated levels of plasma creatinine, proteinuria, and albuminuria and declined eGFR are traits observed in CKD patients. The current study attempts to highlight the collagen triple helix repeat containing 1 (CTHRC1) protein as a putative blood biomarker for CKD in addition to existing recognized indicators of CKD progression. Methods: A total of 26 CKD patients and 18 healthy controls were enrolled in this study. Clinical characteristics and complete blood and biochemical analyses were collected, and human ELISA kits were used to detect possible CKD biomarkers. Results: The study’s findings showed that CTHRC1 correlates with key clinical markers of kidney function such as 24 h urine total protein, creatinine, urea, and uric acid. In addition, CTHRC1 demonstrated a strong significant difference (p ≤ 0.0001) between the CKD and control group. Conclusions: Our research demonstrates that the plasma level of CTHRC1 can distinguish between those with CKD and healthy patients. Plasma CTHRC1 levels may aid in the diagnosis of CKD given the current state of knowledge, and these results call for further investigation in a wider, more diverse patient group.

Gene function and cell surface protein association analysis based on single-cell multiomics data

Single-cell transcriptomics provides researchers with a powerful tool to resolve the transcriptome heterogeneity of individual cells. However, this method falls short in revealing cellular heterogeneity at the protein level. Previous single-cell multiomics studies have focused on data integration rather than exploiting the full potential of multiomics data. Here we introduce a new analysis framework, gene function and protein association (GFPA), that mines reliable associations between gene function and cell surface protein from single-cell multimodal data. Applying GFPA to human peripheral blood mononuclear cells (PBMCs), we observe an association of epithelial mesenchymal transition (EMT) with the CD99 protein in CD4 T cells, which is consistent with previous findings. Our results show that GFPA is reliable across multiple cell subtypes and PBMC samples. The GFPA python packages and detailed tutorials are freely available at https://github.com/studentiz/GFPA.

DNA Methylation as a Diagnostic, Prognostic, and Predictive Biomarker in Head and Neck Cancer

Head and neck squamous cell carcinoma (HNSCC) is a term collectively used to describe all cancers that develop in the oral and nasal cavities, the paranasal sinuses, the salivary glands, the pharynx, and the larynx. The majority (75%) of all newly diagnosed cases are observed in patients with locally advanced and aggressive disease, associated with significant relapse rates (30%) and poor prognostic outcomes, despite advances in multimodal treatment. Consequently, there is an unmet need for the identification and application of tools that would enable diagnosis at the earliest possible stage, accurately predict prognostic outcomes, contribute to the timely detection of relapses, and aid in the decision for therapy selection. Recent evidence suggests that DNA methylation can alter the expression of genes in a way that it favors tumorigenesis and tumor progression in HNSCC, and therefore represents a potential source for biomarker identification. This study summarizes the current knowledge on how abnormally methylated DNA profiles in HNSCC patients may contribute to the pathogenesis of HNSCC and designate the methylation patterns that have the potential to constitute clinically valuable biomarkers for achieving significant advances in the management of the disease and for improving survival outcomes in these patients.

Identification of key biomarkers for STAD using filter feature selection approaches

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer death worldwide. Discovery of diagnostic biomarkers prompts the early detection of GC. In this study, we used limma method combined with joint mutual information (JMI), a machine learning algorithm, to identify a signature of 11 genes that performed well in distinguishing tumor and normal samples in a stomach adenocarcinoma cohort. Other two GC datasets were used to validate the classifying performances. Several of the candidate genes were correlated with GC tumor progression and survival. Overall, we highlight the application of feature selection approaches in the analysis of high-dimensional biological data, which will improve study accuracies and reduce workloads for the researchers when identifying potential tumor biomarkers.