Prognostic significance of CHCHD2P9 and ZNF204P in breast cancer: exploring their expression patterns and associations with malignancy-related genes.

BACKGROUND: Non-coding RNAs (ncRNAs) have a crucial impact on diverse cellular processes, influencing the progression of breast cancer (BC). The objective of this study was to identify novel ncRNAs in BC with potential effects on patient survival and disease progression. METHODS: We utilized the cancer genome atlas data to identify ncRNAs associated with BC pathogenesis. We explored the association between these ncRNA expressions and survival rates. A risk model was developed using candidate ncRNA expression and beta coefficients obtained from a multivariate Cox regression analysis. Co-expression networks were constructed to determine potential relationships between these ncRNAs and molecular pathways. For validation, we employed BC samples and the RT-qPCR method. RESULTS: Our findings revealed a noteworthy increase in the expression of AC093850.2 and CHCHD2P9 in BC, which was correlated with a poor prognosis. In contrast, ADAMTS9-AS1 and ZNF204P displayed significant downregulation and were associated with a favorable prognosis. The risk model, incorporating these four ncRNAs, robustly predicted patient survival. The co-expression network showed an effective association between levels of AC093850.2, CHCHD2P9, ADAMTS9-AS1, and ZNF204P and genes involved in pathways like metastasis, angiogenesis, metabolism, and DNA repair. The RT-qPCR results verified notable alterations in the expression of CHCHD2P9 and ZNF204P in BC samples. Pan-cancer analyses revealed alterations in the expression of these two ncRNAs across various cancer types. CONCLUSION: This study presents a groundbreaking discovery, highlighting the substantial dysregulation of CHCHD2P9 and ZNF204P in BC and other cancers, with implications for patient survival.

ANXA5: A Key Regulator of Immune Cell Infiltration in Hepatocellular Carcinoma.

BACKGROUND Hepatocellular carcinoma (HCC) poses a significant threat to human life and is the most prevalent form of liver cancer. The intricate interplay between apoptosis, a common form of programmed cell death, and its role in immune regulation stands as a crucial mechanism influencing tumor metastasis. MATERIAL AND METHODS Utilizing HCC samples from the TCGA database and 61 anoikis-related genes (ARGs) sourced from GeneCards, we analyzed the relationship between ARGs and immune cell infiltration in HCC. Subsequently, we identified long non-coding RNAs (lncRNAs) associated with ARGs, using the least absolute shrinkage and selection operator (LASSO) regression analysis to construct a robust prognostic model. The predictive capabilities of the model were then validated through examination in a single-cell dataset. RESULTS Our constructed prognostic model, derived from lncRNAs linked to ARGs, comprised 11 significant lncRNAs: NRAV, MCM3AP-AS1, OTUD6B-AS1, AC026356.1, AC009133.1, DDX11-AS1, AC108463.2, MIR4435-2HG, WARS2-AS1, LINC01094, and HCG18. The risk score assigned to HCC samples demonstrated associations with immune indicators and the infiltration of immune cells. Further, we identified Annexin A5 (ANXA5) as the pivotal gene among ARGs, with it exerting a prominent role in regulating the lncRNA gene signature. Our validation in a single-cell database elucidated the involvement of ANXA5 in immune cell infiltration, specifically in the regulation of mononuclear cells. CONCLUSIONS This study delves into the intricate correlation between ARGs and immune cell infiltration in HCC, culminating in the development of a novel prognostic model reliant on 11 ARGs-associated lncRNAs. Furthermore, our findings highlight ANXA5 as a promising target for immune regulation in HCC, offering new perspectives for immune therapy in the context of HCC.

Systematic Characterization of DNA Methyltransferases Family in Tumor Progression and Antitumor Immunity.

Objective: DNA methylation is an essential epigenetic marker governed by DNA methyltransferases (DNMTs), which can influence cancer onset and progression. However, few studies have provided an integrated analysis of the relevance of DNMT family genes to cell stemness, the tumor microenvironment (TME), and immunotherapy biomarkers across diverse cancers. Methods: This study investigated the impact of five DNMTs on transcriptional profiles, prognosis, and their association with Ki67 expression, epithelial-mesenchymal transition signatures, stemness scores, the TME, and immunological markers across 31 cancer types from recognized public databases. Results: The results indicated that DNMT1/DNMT3B/DNMT3A expression increased, whereas TRDMT1/DNMT3L expression decreased in most cancer types. DNMT family genes were identified as prognostic risk factors for numerous cancers, as well as being prominently associated with immune, stromal, and ESTIMATE scores, as well as with immune-infiltrating cell levels. Expression of the well-known immune checkpoints, PDCD1 and CILA4, was noticeably related to DNMT1/DNMT3A/DNMT3B expression. Finally, we validated the role of DNMT1 in MCF-7 and HepG2-C3A cell lines through its knockdown, whereafter a decrease in cell proliferation and migration ability in vitro was observed. Conclusion: Our study comprehensively expounded that DNMT family genes not only behave as promising prognostic factors but also have the potential to serve as therapeutic targets in cancer immunotherapy for various types of cancer.

DHCR24 in Tumor Diagnosis and Treatment: A Comprehensive Review.

As an important nutrient in the human body, cholesterol can not only provide structural components for the body's cells, but also can be transformed into a variety of active substances to regulate cell signaling pathways. As an important cholesterol synthase, DHCR24 participates in important regulatory processes in the body. The application of DHCR24 in tumor clinical diagnosis and treatment also attracts much attention. This article reviews the structure and regulatory characteristics of DHCR24, and the research of DHCR24 on tumor progression. We summarize the possible mechanisms of DHCR24 promoting tumor progression through reactive oxygen species (ROS), p53, Ras and PI3K-AKT pathways. Through our review, we hope to provide more research ideas and reference value for the application of DHCR24 in tumor prevention and treatment.

LINC01503 in cancer: from molecular mechanisms to therapeutic implications.

Long non-coding RNAs (lncRNAs) are fundamental agents that govern tumor growth and metastasis across a spectrum of cancer types. Linc01503 is a novel lncRNA situated on human chromosome 19, and it is intricately linked with the pathogenesis of multiple human cancers, underscoring its substantial role and significance in cancer development. It has been recognized as a pivotal contributor to inducing malignant behaviors in lung cancer, gastric cancer, colorectal cancer, cholangiocarcinoma, liver cancer and pancreatic cancer, among others. The dysregulation of linc01503 has been shown to strongly associate with advanced clinicopathological factors and foretell an unfavorable prognosis, indicating its prospective clinical significance as a valuable biomarker and therapeutic target for individuals with cancer. The primary objective of the current work is to present the intricate molecular pathways governed by linc01503 and its profound clinical relevance in the context of carcinogenesis. We also focus on the future prospects of linc01503-based clinical application. This will help us to better understand the regulatory mechanism of carcinogenesis and provide new ideas for precision molecular medicine.

Exploration of the shared pathways and common biomarker in adamantinomatous craniopharyngioma and type 2 diabetes using integrated bioinformatics analysis.

Craniopharyngiomas are rare tumors of the central nervous system that typically present with symptoms such as headache and visual impairment, and those reflecting endocrine abnormalities, which seriously affect the quality of life of patients. Patients with craniopharyngiomas are at higher cardiometabolic risk, defined as conditions favoring the development of type 2 diabetes and cardiovascular disease. However, the underlying common pathogenic mechanisms of craniopharyngiomas and type 2 diabetes are not clear. Especially due to the difficulty of conducting in vitro or in vivo experiments on craniopharyngioma, we thought the common pathway analysis between craniopharyngioma and type 2 diabetes based on bioinformatics is a powerful and feasible method. In the present study, using public datasets (GSE94349, GSE68015, GSE38642 and GSE41762) obtained from the GEO database, the gene expression associated with adamantinomatous craniopharyngioma, a subtype of craniopharyngioma, and type 2 diabetes were analyzed using a bioinformatic approach. We found 11 hub genes using a protein-protein interaction network analysis. Of these, seven (DKK1, MMP12, KRT14, PLAU, WNT5B, IKBKB, and FGF19) were also identified by least absolute shrinkage and selection operator analysis. Finally, single-gene validation and receptor operating characteristic analysis revealed that four of these genes (MMP12, PLAU, KRT14, and DKK1) may be involved in the common pathogenetic mechanism of adamantinomatous craniopharyngioma and type 2 diabetes. In addition, we have characterized the differences in immune cell infiltration that characterize these two diseases, providing a reference for further research.

A new label free spiral sensor using impedance spectroscopy to characterize hepatocellular carcinoma in tissue and serum samples.

Hepatocellular carcinoma (HCC) stands as the most prevalent form of primary liver cancer, predominantly affecting patients with chronic liver diseases such as hepatitis B or C-induced cirrhosis. Diagnosis typically involves blood tests (assessing liver functions and HCC biomarkers), imaging procedures such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), and liver biopsies requiring the removal of liver tissue for laboratory analysis. However, these diagnostic methods either entail lengthy lab processes, require expensive imaging equipment, or involve invasive techniques like liver biopsies. Hence, there exists a crucial need for rapid, cost-effective, and noninvasive techniques to characterize HCC, whether in serum or tissue samples. In this study, we developed a spiral sensor implemented on a printed circuit board (PCB) technology that utilizes impedance spectroscopy and applied it to 24 tissues and sera samples as proof of concept. This newly devised circuit has successfully characterized HCC and normal tissue and serum samples. Utilizing the distinct dielectric properties between HCC cells and serum samples versus the normal samples across a specific frequency range, the differentiation between normal and HCC samples is achieved. Moreover, the sensor effectively characterizes two HCC grades and distinguishes cirrhotic/non-cirrhotic samples from tissue specimens. In addition, the sensor distinguishes cirrhotic/non-cirrhotic samples from serum specimens. This pioneering study introduces Electrical Impedance Spectroscopy (EIS) spiral sensor for diagnosing HCC and liver cirrhosis in clinical serum-an innovative, low-cost, rapid (< 2 min), and precise PCB-based technology without elaborate sample preparation, offering a novel non-labeled screening approach for disease staging and liver conditions.

An immunogenic cell death-related lncRNA signature correlates with prognosis and tumor immune microenvironment in bladder cancer.

Immunogenic cell death (ICD) is a newly discovered form of cellular demise that triggers adaptive immune responses mediated by T cells. However, the immunogenic cell death-related lncRNAs (ICDRLs) involved in bladder cancer (BC) development and progression remain to be further elucidated. Molecular profiling data and clinicopathological information for BC patients were obtained from TCGA, and the ICDRGs list was obtained from published literature. For the identification of ICDRLs, Pearson co-expression analysis was performed, and a prognostic signature based on 13 ICDRLs was constructed by univariate assays and LASSO assays. Herein, an ICDRLSig consisting of 13 ICDRLs was constructed. KM curves and ROC curves demonstrated that the constructed signature in the TCGA training, testing, entire and external sets have good predictive performance. Multivariate assays illuminated that the signature is an independent predictor for BC patients' OS, exhibiting greater predictive power for the survival than traditional clinicopathological features. Additionally, patients in the high-ICDRLSig risk subgroup had more abundant immune infiltration, higher immune checkpoint gene expression, lower TMB and poorer response to immunotherapy. We have developed a novel ICDRLSig that can be exploited for survival prediction and provide a reference for further individualized treatment.

Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma.

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential implications for advancements in cancer treatments. Although emerging evidence highlights the critical regulatory roles of long non-coding RNAs (lncRNAs) in the pathobiology of lung adenocarcinoma (LUAD), research into lncRNAs specifically associated with disulfidptosis in LUAD, termed disulfidptosis-related lncRNAs (DRLs), remains insufficiently explored. Using The Cancer Genome Atlas (TCGA)-LUAD dataset, we implemented ten machine learning techniques, resulting in 101 distinct model configurations. To assess the predictive accuracy of our model, we employed both the concordance index (C-index) and receiver operating characteristic (ROC) curve analyses. For a deeper understanding of the underlying biological pathways, we referred to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) for functional enrichment analysis. Moreover, we explored differences in the tumor microenvironment between high-risk and low-risk patient cohorts. Additionally, we thoroughly assessed the prognostic value of the DRLs signatures in predicting treatment outcomes. The Kaplan-Meier (KM) survival analysis demonstrated a significant difference in overall survival (OS) between the high-risk and low-risk cohorts (p < 0.001). The prognostic model showed robust performance, with an area under the ROC curve exceeding 0.75 at one year and maintaining a value above 0.72 in the two and three-year follow-ups. Further research identified variations in tumor mutational burden (TMB) and differential responses to immunotherapies and chemotherapies. Our validation, using three GEO datasets (GSE31210, GSE30219, and GSE50081), revealed that the C-index exceeded 0.67 for GSE31210 and GSE30219. Significant differences in disease-free survival (DFS) and OS were observed across all validation cohorts among different risk groups. The prognostic model offers potential as a molecular biomarker for LUAD prognosis.

The OVAREX study: Establishment of ex vivo ovarian cancer models to validate innovative therapies and to identify predictive biomarkers.

BACKGROUND: Ovarian cancer is the first cause of death from gynecological malignancies mainly due to development of chemoresistance. Despite the emergence of PARP inhibitors, which have revolutionized the therapeutic management of some of these ovarian cancers, the 5-year overall survival rate remains around 45%. Therefore, it is crucial to develop new therapeutic strategies, to identify predictive biomarkers and to predict the response to treatments. In this context, functional assays based on patient-derived tumor models could constitute helpful and relevant tools for identifying efficient therapies or to guide clinical decision making. METHOD: The OVAREX study is a single-center non-interventional study which aims at investigating the feasibility of establishing in vivo and ex vivo models and testing ex vivo models to predict clinical response of ovarian cancer patients. Patient-Derived Xenografts (PDX) will be established from tumor fragments engrafted subcutaneously into immunocompromised mice. Explants will be generated by slicing tumor tissues and Ascites-Derived Spheroids (ADS) will be isolated following filtration of ascites. Patient-derived tumor organoids (PDTO) will be established after dissociation of tumor tissues or ADS, cell embedding into extracellular matrix and culture in specific medium. Molecular and histological characterizations will be performed to compare tumor of origin and paired models. Response of ex vivo tumor-derived models to conventional chemotherapy and PARP inhibitors will be assessed and compared to results of companion diagnostic test and/or to the patient's response to evaluate their predictive value. DISCUSSION: This clinical study aims at generating PDX and ex vivo models (PDTO, ADS, and explants) from tumors or ascites of ovarian cancer patients who will undergo surgical procedure or paracentesis. We aim at demonstrating the predictive value of ex vivo models for their potential use in routine clinical practice as part of precision medicine, as well as establishing a collection of relevant ovarian cancer models that will be useful for the evaluation of future innovative therapies. TRIAL REGISTRATION: The clinical trial has been validated by local research ethic committee on January 25th 2019 and registered at ClinicalTrials.gov with the identifier NCT03831230 on January 28th 2019, last amendment v4 accepted on July 18, 2023.

Prognostic and clinicopathological value of Ki-67 in patients with oesophageal squamous cell carcinoma: a systematic review and meta-analysis.

OBJECTIVES: The relationship between Ki-67 expression and the prognosis of patients with oesophageal squamous cell carcinoma (ESCC) has been extensively studied. However, their findings were inconsistent. Consequently, the present meta-analysis was performed to identify the precise value of Ki-67 in predicting the prognosis of ESCC. DESIGN: The current meta-analysis was carried out in accordance with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. DATA SOURCES: Electronic databases of PubMed, Embase, Web of Science and Cochrane Library were systematically searched until 26 September 2023. STATISTICAL METHODS: Pooled HRs and corresponding 95% CIs were calculated to estimate the role of Ki-67 in predicting overall survival (OS) and disease-free survival (DFS) in ESCC. Between-study heterogeneity was evaluated using Cochrane's Q test and I2 statistics. Specifically, significant heterogeneities were identified based on p<0.10 on the Q statistic test or I2>50% so the random-effects model should be used; otherwise, the fixed-effects model should be used. The relationship between Ki-67 and clinicopathological characteristics of ESCC was evaluated by combining ORs with their corresponding 95% CIs. RESULTS: 11 articles with 1124 patients were included in the present meta-analysis. Based on our analysis, increased Ki-67 expression was markedly associated with poor OS (HR 1.62, 95% CI 1.15 to 2.28, p=0.006) and DFS (HR 1.72, 95% CI 1.22 to 2.43, p=0.002) in ESCC. Moreover, subgroup analysis revealed that Ki-67 upregulation significantly predicted OS and DFS when a Ki-67 threshold of >30% was used. Nonetheless, Ki-67 was not significantly associated with sex, T stage, N stage, TNM stage, tumour differentiation or tumour location. CONCLUSIONS: In the present meta-analysis, high Ki-67 expression significantly predicted OS and DFS in patients with ESCC, especially when Ki-67>30% was used as the threshold. These results suggest that Ki-67 could serve as an effective and reliable prognostic indicator for ESCC.

[Application of PRAME immunohistochemistry in the differential diagnosis of primary endometrial and endocervical adenocarcinomas].

Objective: To investigate the diagnostic value of preferentially expressed antigen in melanoma (PRAME) immunohistochemical staining in differential diagnosis of primary endometrial and endocervical adenocarcinomas. Methods: Eighty-seven cases of endometrial adenocarcinoma and sixty-three cases of cervical adenocarcinoma were collected from May 2018 to November 2023 in the Department of Pathology, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School and all the cases were subject to PRAME immunohistochemical staining. The difference of PRAME expression between endometrial and endocervical adenocarcinomas was analyzed. Results: In 87 cases of endometrial adenocarcinoma, patients' age ranged from 35 to 71 years (average 59 years, median 59 years); in 63 cases of cervical adenocarcinoma patients' age ranged from 28 to 80 years (average 49 years, median 47 years). Seventy-eight cases (78/87, 89.7%) of endometrial adenocarcinoma; 2 cases (2/63, 3.2%) of cervical adenocarcinoma showed positive PRAME staining, and both cases of cervical adenocarcinoma were clear cell carcinoma. The sensitivity and specificity of PRAME in distinguishing between endometrial and cervical adenocarcinoma in the cohort were 89.7% and 96.8%, while those in differentiating non-clear cell carcinoma of the uterus from that of the cervix reached up to 91% and 100%, respectively. Conclusions: Immunohistochemical staining for PRAME demonstrates statistically significant differences between endometrial and cervical carcinomas, making it a useful auxiliary diagnostic marker for differentiating cervical and endometrial adenocarcinoma, especially non-clear cell carcinoma.

Prospective of Mitochondrial DNA Variations in Cancer on Genomic Medicine.

Mitochondrial DNA (mtDNA) has emerged as a pivotal component in understanding the etiology and susceptibility of cancer. A recent study by Chen and colleagues delineated the germline genetic effect of mtDNA single-nucleotide polymorphisms (SNP) and haplogroups across pan-cancer risk. They identified a subset of mtSNPs and the corresponding risk score, as well as haplogroups A and M7 alongside their genetic interactions, conferring a protective effect against various cancers. These findings underscored the value of mtDNA variations as biomarkers for cancer etiology and as tools for cancer risk stratification. Future investigations are encouraged to integrate comprehensive omics data of genomics, transcriptomics, proteomics, and metabolomics, etc., from nuclear DNA with mtDNA variations, alongside single-cell and spatial technologies, to unravel the tumor mechanism and identify the drug targets. Moreover, the incorporation of polygenic risk score, that included mtDNA variations with both rare and common frequencies, and liquid biopsy-based biomarkers would enhance the predictive performance of cancer risk assessment and refine the risk stratification of population-based cancer screening. This commentary advocates for the validation across diverse populations to harness the full potential of mitochondrial genomics, and ultimately paves the prospective way for advancements in personalized cancer therapeutics and prevention strategies. See related article by Chen and colleagues, Cancer Epidemiol Biomarkers Prev 2024;33:381-8.

Soluble immune checkpoints: implications for cancer prognosis and response to immune checkpoint therapy and conventional therapies.

Longitudinal sampling of tumor tissue from patients with solid cancers, aside from melanoma and a few other cases, is often unfeasible, and thus may not capture the plasticity of interactions between the tumor and immune system under selective pressure of a given therapy. Peripheral blood analyses provide salient information about the human peripheral immunome while offering technical and practical advantages over traditional tumor biopsies, and should be utilized where possible alongside interrogation of the tumor. Some common blood-based biomarkers used to study the immune response include immune cell subsets, circulating tumor DNA, and protein analytes such as cytokines. With the recent explosion of immune checkpoint inhibitors (ICI) as a modality of treatment in multiple cancer types, soluble immune checkpoints have become a relevant area of investigation for peripheral immune-based biomarkers. However, the exact functions of soluble immune checkpoints and their roles in cancer for the most part remain unclear. This review discusses current literature on the production, function, and expression of nine soluble immune checkpoints - sPD-L1, sPD-1, sCTLA4, sCD80, sTIM3, sLAG3, sB7-H3, sBTLA, and sHVEM - in patients with solid tumors, and explores their role as biomarkers of response to ICI as well as to conventional therapies (chemotherapy, radiotherapy, targeted therapy, and surgery) in cancer patients.

Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial.

Accurate identification of genetic alterations in tumors, such as Fibroblast Growth Factor Receptor, is crucial for treating with targeted therapies; however, molecular testing can delay patient care due to the time and tissue required. Successful development, validation, and deployment of an AI-based, biomarker-detection algorithm could reduce screening cost and accelerate patient recruitment. Here, we develop a deep-learning algorithm using >3000 H&E-stained whole slide images from patients with advanced urothelial cancers, optimized for high sensitivity to avoid ruling out trial-eligible patients. The algorithm is validated on a dataset of 350 patients, achieving an area under the curve of 0.75, specificity of 31.8% at 88.7% sensitivity, and projected 28.7% reduction in molecular testing. We successfully deploy the system in a non-interventional study comprising 89 global study clinical sites and demonstrate its potential to prioritize/deprioritize molecular testing resources and provide substantial cost savings in the drug development and clinical settings.

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study.

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell-cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

The TEOGIC study project: a comprehensive characterization of early onset gastrointestinal cancer in the Northern area of Spain.

BACKGROUND: Gastrointestinal cancers represent one of the most prevalent diseases worldwide. Strikingly, the incidence of Early Onset Gastrointestinal Cancer (EOGIC) has been rising during the last decades and changes in lifestyle and environmental exposure seem to play a role. EOGIC has been defined as a different entity compared to on-average gastrointestinal cancer, with distinct clinical and molecular characteristics. Inherent to the particularities of younger age, there is an unmet need for a tailored approach for the management of these patients. The TEOGIC proposes a comprehensive study to characterize EOGIC patients in the northern of Spain. METHODS: Patients with histologically confirmed new diagnosis of colorectal, gastroesophageal and pancreatic adenocarcinoma will be considered for two cohorts: EOGIC (≤ 50 years old) and non-EOGIC (60-75 years old), with a ratio of 1:2. Two hundred and forty patients will be recruited in 4 Public Hospitals from northern Spain. After receiving unified informed consent, demographic and clinical data of the patients will be collected in a REDCap database. Lifestyle related data will be obtained in questionnaires assessing diet, physical activity and the general quality of life of the patients before diagnosis. Biological samples prior to any onco-specific treatment will be obtained for the analyses of circulating inflammatory proteins, gut microbiota, and the proteome of the tumor microenvironment. Histologic characteristics and routine biomarkers will be also collected. Thereafter, data will be integrated and analyzed to assess tumor specific, pan-tumor and sex-associated differential characteristics of EOGIC. DISCUSSION: The underlying risk factors and differential characteristics of EOGIC remain poorly studied, particularly in our geographical area. Although limited by the exploratory nature and the small sample size estimated to be recruited, TEOGIC represents the first attempt to comprehensively characterize these young patients, and thus attend to their special needs. Findings derived from this study could contribute to raise awareness and preventive behaviors in the population. In parallel, molecular studies could lead to the identification of potential novel non-invasive biomarkers and therapeutic targets that would help in the development of the tailored clinical management of these patients, focusing on screening programs for early diagnosis and precision medicine.

Identification and diagnostic potential of hsa_circ_101303 in colorectal cancer: unraveling a regulatory network.

BACKGROUND: The role of novel circular RNAs (circRNAs) in colorectal cancer (CRC) remains to be determined. This study aimed to identify a novel circRNA involved in CRC pathogenesis, assess its diagnostic value, and construct a regulatory network. METHODS: Differential expression analysis was conducted using circRNA datasets to screen for differentially expressed circRNAs. The expression of selected circRNAs was validated in external datasets and clinical samples. Diagnostic value of plasma circRNA levels in CRC was assessed. A competing endogenous RNA (ceRNA) network was constructed for the circRNA using TCGA dataset. RESULTS: Analysis of datasets revealed that hsa_circ_101303 was significantly overexpressed in CRC tissues compared to normal tissues. The upregulation of hsa_circ_101303 in CRC tissues was further confirmed through the GSE138589 dataset and clinical samples. High expression of hsa_circ_101303 was associated with advanced N stage, M stage, and tumor stage in CRC. Plasma levels of hsa_circ_101303 were markedly elevated in CRC patients and exhibited moderate diagnostic ability for CRC (AUC = 0.738). The host gene of hsa_circ_101303 was also found to be related to the TNM stage of CRC. Nine miRNAs were identified as target miRNAs for hsa_circ_101303, and 27 genes were identified as targets of these miRNAs. Subsequently, a ceRNA network for hsa_circ_101303 was constructed to illustrate the interactions between the nine miRNAs and 27 genes. CONCLUSIONS: The study identifies hsa_circ_101303 as a highly expressed circRNA in CRC, which is associated with the progression of the disease. Plasma levels of hsa_circ_101303 show promising diagnostic potential for CRC. The ceRNA network for hsa_circ_101303 provides valuable insights into the regulatory mechanisms underlying CRC.

FAP Serves as a Prognostic Biomarker in Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) poses significant challenges with poor survival rates and limited therapeutic strategies. Our study, using The Cancer Genome Atlas (TCGA) data, assesses cancer-associated fibroblast (CAF) gene signatures' clinical relevance. In our analysis across TCGA tumor types, differential gene expression analysis revealed that fibroblast activation protein (FAP) is upregulated in tumor tissues and associated with poorer survival rates in HNSCC. Furthermore, mechanistic studies employing gene-silencing techniques substantiated that FAP knockout led to a significant decrease in cellular proliferation, invasion, and migration in HNSCC cell lines. Through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we established that high FAP expression correlates with vital biological processes such as extracellular matrix organization, angiogenesis, and cellular motility. Importantly, FAP was found to regulate these processes by promoting the expression of key proteins involved in epithelial-mesenchymal transition-related pathways. Additionally, our analysis revealed a significant correlation between FAP expression and the expression profiles of immune checkpoint molecules, underscoring its potential role in immune modulation. Collectively, our findings illuminate FAP's pivotal role in HNSCC pathogenesis and its potential as a prognostic biomarker and therapeutic target. This research lays the groundwork for understanding the multifaceted roles and regulatory mechanisms of CAFs in HNSCC, thereby offering valuable perspectives for the development of targeted therapeutic strategies aimed at improving patient outcomes.