Pan-cancer analysis identifies ITIH1 as a novel prognostic indicator for hepatocellular carcinoma

Deciphering the shared genetic architecture between bipolar disorder and body mass index

BACKGROUND

The comorbidity between bipolar disorder (BD) and high body mass index (BMI) is well-documented, but their shared genetic architecture remains unclear. Our study aimed to explore this genetic correlation and potential causality.

METHODS

Utilizing large-scale genome-wide association study (GWAS) summary statistics, we quantified global and local genetic correlations between BD and BMI using linkage disequilibrium score regression (LDSC) and Heritability Estimation from Summary Statistics. Stratified LDSC characterized genetic overlap across functional categories. Cross-trait meta-analyses identified shared risk single nucleotide polymorphisms (SNPs), followed by colocalization analysis using Coloc. Bi-directional Mendelian randomization (MR) assessed causality, while tissue-level SNP heritability enrichment for BD and BMI was evaluated using LDSC-specific expressed genes and Multi-marker Analysis of Genomic Annotation.

RESULTS

We found a genetic correlation between BD and BMI, especially in localized genomic regions. Cross-trait meta-analysis identified 46 significant SNPs shared between BD and BMI, including three novel shared risk SNPs. Colocalization analysis verified two novel SNPs with shared causal variants linked to ITIH1 and TM6SF2 genes. MR analysis demonstrated a causal effect of BD on BMI, but not the reverse. Gene expression data revealed genetic correlation enrichment in five specific brain regions.

CONCLUSION

This study comprehensively analyzes the genetic correlation between BD and BMI, uncovering shared genetic architecture and identifying novel risk loci. These findings provide new insights into the interplay between BD and BMI, informing the development of diagnostic tools and therapeutic strategies.

m6A-Dependent ITIH1 Regulated by TGF-β Acts as a Target for Hepatocellular Carcinoma Progression

Both the transforming growth factor beta (TGF-β) signaling pathway and N6-methyladenosine (m6A) modification for mRNA play an important role in hepatocellular carcinoma (HCC) progression. However, the relationship between TGF-β and m6A in hepatocellular carcinoma (HCC) remains unclear. Here, it is found that TGF-β can promote the liquid phase separation of METTL3, which further leads to the reduction of mRNA stability of ITIH1. As a secreted protein, ITIH1 can act as a ligand of integrin α5β1 to antagonize fibronectin, induce the inhibition of focal adhesion kinase signaling pathway, and inhibit the progression of HCC. In the preclinical model (mouse model, patient-derived organoid, patient-derived xenografts), purified recombinant ITIH1 (r-ITIH1) protein can be targeted for HCC. More importantly, r-ITIH1 can play a synergistic role in targeting HCC with TGF-β inhibitor. The downstream ITIH1 regulatory mechanism of TGF-β and m6A modification is revealed, and ITIH1 can be translational as a potential target for HCC.

ITIH1 suppresses carcinogenesis in renal cell carcinoma through regulation of the NF‑κB signaling pathway

Renal cell carcinoma (RCC) is a common malignancy of the urinary system. Although traditional therapies, such as surgery assisted with chemotherapy have improved the quality of life and survival time of patients with RCC, patients with metastasis or recurrence benefit little from such therapies. At present, little is known about the underlying mechanisms of RCC, rendering treatment selection and implementation challenging. Therefore, investigating the cause and underlying mechanisms of RCC remain of importance to explore potential new avenues for its treatment. Inter-α-trypsin inhibitor heavy chain 1 (ITIH1) is an inflammation-associated gene reported to suppress the progression of liver cancer. However, its role in RCC remains poorly understood. Therefore, the present study aimed to investigate the role and mechanism of ITIH1 in RCC. Based on data obtained from The Cancer Genome Atlas database, ITIH1 expression was demonstrated to be significantly higher in tumor tissues compared with normal tissues, which was in turn negatively associated with the survival of patients with RCC. However, in RCC cells, ITIH1 was shown to be expressed at significantly lower levels compared with those in HK-2 cells. The discrepancy between tissues and cell lines might be due to the different environment of cell growth. ITIH1 knockdown in RCC cells significantly increased cell proliferation and invasion whilst significantly decreasing the apoptosis rate, compared with those in control cells (without ITIH1 knockdown). By contrast, overexpression of ITIH1 significantly inhibited cell proliferation and invasion in RCC cells. In terms of western blotting results, the phosphorylation levels of NF-κB were significantly increased following ITIH1 knockdown. The protein expression level of IκB significantly decreased whereas that of IKK, Cyclin D1, proliferating cell nuclear antigen and α-smooth muscle actin were significantly increased in ITIH1-knockdown cells, compared with those in the control cells (without ITIH1 knockdown). This suggests that the NF-κB pathway may be activated after ITIH1 knockdown. Following treatment with the NF-κB pathway inhibitor JSH-23 in combination with ITIH1 knockdown, RCC cell proliferation and invasion were significantly reduced compared with those after ITIH1 knockdown alone. In summary, results from the present study suggest that ITIH1 can serve an inhibitory role in the progression of RCC, which could potentially be inhibited through the NF-κB signaling pathway.

The function of the inter-alpha-trypsin inhibitors in the development of disease

Through the formation of covalent connections with hyaluronic acid (HA), the inter-α-trypsin inhibitor (IαI) family collaborates to preserve the stability of the extracellular matrix (ECM). The five distinct homologous heavy chains (ITIH) and one type of light chain make up the IαI family. ITIH alone or in combination with bikunin (BK) has been proven to have important impacts in a number of earlier investigations. This implies that BK and ITIH might be crucial to both physiological and pathological processes. The functions of BK and ITIH in various pathophysiological processes are discussed independently in this paper. In the meanwhile, this study offers suggestions for further research on the roles of BK and ITIH in the course of disease and summarizes the plausible mechanisms of the previous studies.

Selenoprotein GPX3 is a novel prognostic indicator for stomach adenocarcinoma and brain low-grade gliomas: Evidence from an integrative pan-cancer analysis

Background

The antioxidant enzyme GPX3 is a selenoprotein that transports selenium in blood and maintains its levels in peripheral tissues. Aberrant GPX3 expression is strongly linked to the development of some tumors. However, there is a scarcity of studies examining the pan-cancer expression patterns and prognostic relevance of GPX3.

Methods

GPX3 expression levels in normal tissues and multiple tumors were analyzed using TCGA, CCLE, GTEx, UALCAN and HPA databases. Forest plots and KM survival curves were utilized to evaluate the correlation between GPX3 expression and the outcome of tumor patients. The prognostic value of GPX3 in LGG was assessed utilizing the CGGA datasets, and that in STAD was tested by TCGA and GEO databases. A nomogram was then constructed to predict OS in STAD using R software. Additionally, the impact of GPX3 on post-chemoradiotherapy OS in patients with LGG and STAD was evaluated using the KM method. The multiplicative interaction of GPX3 expression, chemotherapy and radiotherapy on STAD and LGG was analyzed using logistic regression models. The correlation of GPX3 with the immune infiltration, immune neoantigens and MMR genes were investigated in TCGA cohort.

Results

GPX3 exhibited downregulation across 21 tumor types, including STAD, with its decreased expression significantly associated with improved OS, DFS, PFS and DSS. Conversely, in LGG, low levels of GPX3 expression were indicative of a poorer prognosis. Univariate and multivariate Cox models further identified GPX3 as an independent predictor of STAD, and a nomogram based on GPX3 expression and other independent factors showed high level of predictive accuracy. Moreover, low GPX3 expression and chemotherapy prolonged the survival of STAD. In LGG patients, chemoradiotherapy, GPX3 and chemotherapy, and GPX3 and chemoradiotherapy may improve prognosis. Our observations reveal a notable connection between GPX3 and immune infiltration, immune neoantigens, and MMR genes.

Conclusions

The variations in GPX3 expression are linked to the controlling tumor development and could act as a promising biomarker that impacts the prognosis of specific cancers like STAD and LGG.

Methylation signatures as biomarkers for non-invasive early detection of breast cancer: A systematic review of the literature

BACKGROUND

Early detection of breast cancer would help alleviate the burden of treatment for early-stage breast cancer and help patient prognosis. There is currently no established gene panel that utilizes the potential of DNA methylation as a molecular signature for the early detection of breast cancer. This systematic review aims to identify the optimal methylation biomarkers for a non-invasive liquid biopsy assay and the gaps in knowledge regarding biomarkers for early detection of breast cancer.

METHODS

Following the PRISMA-ScR method, Pubmed and Google Scholar was searched for publications related to methylation biomarkers in breast cancer over a five-year period. Eligible publications were mined for key data fields such as study aims, cohort demographics, types of breast cancer studied, technologies used, and outcomes. Data was analyzed to address the objectives of the review.

RESULTS

Literature search identified 112 studies of which based on eligibility criteria, 13 studies were included. 28 potential methylation gene targets were identified, of which 23 were methylated at the promoter region, 1 was methylated in the body of the gene and 4 were methylated at yet to be identified locations.

CONCLUSIONS

Our evaluation shows that at minimum APC, RASSFI, and FOXA1 genes would be a promising set of genes to start with for the early detection of breast cancer, based on the sensitivity and specificity outlined in the studies. Prospective studies are needed to optimize biomarkers for broader impact in early detection of breast cancer.

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum, and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1), and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.

CD99 Modulates the Proteomic Landscape of Ewing Sarcoma Cells and Related Extracellular Vesicles

Ewing sarcoma (EWS) is an aggressive pediatric bone tumor characterized by unmet clinical needs and an incompletely understood epigenetic heterogeneity. Here, we considered CD99, a major surface molecule hallmark of EWS malignancy. Fluctuations in CD99 expression strongly impair cell dissemination, differentiation, and death. CD99 is also loaded within extracellular vesicles (EVs), and the delivery of CD99-positive or CD99-negative EVs dynamically exerts oncogenic or oncosuppressive functions to recipient cells, respectively. We undertook mass spectrometry and functional annotation analysis to investigate the consequences of CD99 silencing on the proteomic landscape of EWS cells and related EVs. Our data demonstrate that (i) the decrease in CD99 leads to major changes in the proteomic profile of EWS cells and EVs; (ii) intracellular and extracellular compartments display two distinct signatures of differentially expressed proteins; (iii) proteomic changes converge to the modulation of cell migration and immune-modulation biological processes; and (iv) CD99-silenced cells and related EVs are characterized by a migration-suppressive, pro-immunostimulatory proteomic profile. Overall, our data provide a novel source of CD99-associated protein biomarkers to be considered for further validation as mediators of EWS malignancy and as EWS disease liquid biopsy markers.

Hepatocellular carcinoma cell differentiation trajectory predicts immunotherapy, potential therapeutic drugs, and prognosis of patients

The aim of this study is to explore a novel classification and investigate the clinical significance of hepatocellular carcinoma (HCC) cells. We analyzed integrated single-cell RNA sequencing and bulk RNA-seq data obtained from HCC samples. Cell trajectory analysis divided HCC cells into three subgroups with different differentiation states: state 1 was closely related to phosphoric ester hydrolase activity, state 2 was involved in eukaryotic initiation factor 4E binding, translation regulator activity and ribosome, and state 3 was associated with oxidoreductase activity and metabolism. Three molecular classes based on HCC differentiation-related genes (HDRGs) from HCC samples were identified, which revealed immune checkpoint gene expression and overall survival (OS) of HCC patients. Moreover, a prognostic risk scoring (RS) model was generated based on eight HDRGs, and the results showed that the OS of the high-risk group was worse than that of the low-risk group. Further, potential therapeutic drugs were screened out based on eight prognostic RS-HDRGs. This study highlights the importance of HCC cell differentiation in immunotherapy, clinical prognosis, and potential molecular-targeted drugs for HCC patients, and proposes a direction for the development of individualized treatments for HCC.

Patterns of Somatic Variants in Colorectal Adenoma and Carcinoma Tissue and Matched Plasma Samples from the Hungarian Oncogenome Program

Analysis of circulating cell-free DNA (cfDNA) of colorectal adenoma (AD) and cancer (CRC) patients provides a minimally invasive approach that is able to explore genetic alterations. It is unknown whether there are specific genetic variants that could explain the high prevalence of CRC in Hungary. Whole-exome sequencing (WES) was performed on colon tissues (27 AD, 51 CRC) and matched cfDNAs (17 AD, 33 CRC); furthermore, targeted panel sequencing was performed on a subset of cfDNA samples. The most frequently mutated genes were APC, KRAS, and FBN3 in AD, while APC, TP53, TTN, and KRAS were the most frequently mutated in CRC tissue. Variants in KRAS codons 12 (AD: 8/27, CRC: 11/51 (0.216)) and 13 (CRC: 3/51 (0.06)) were the most frequent in our sample set, with G12V (5/27) dominance in ADs and G12D (5/51 (0.098)) in CRCs. In terms of the cfDNA WES results, tumor somatic variants were found in 6/33 of CRC cases. Panel sequencing revealed somatic variants in 8 out of the 12 enrolled patients, identifying 12/20 tumor somatic variants falling on its targeted regions, while WES recovered only 20% in the respective regions in cfDNA of the same patients. In liquid biopsy analyses, WES is less efficient compared to the targeted panel sequencing with a higher coverage depth that can hold a relevant clinical potential to be applied in everyday practice in the future.

Quantitative proteomic analysis of exosomes from umbilical cord mesenchymal stem cells and rat bone marrow stem cells

Exosomes derived from mesenchymal stem cells (MSCs) have been used for cancer treatment, however, an in-depth analysis of the exosomal proteomes is lacking. In this manuscript, we use the diaPASEF (parallel accumulation serial fragmentation combined with the data-independent acquisition) method to quantify exosomes derived from human umbilical cord mesenchymal stem cells (UCMSCs) and rat bone marrow stem cells (BMSCs), resulting in identification of 4200 human proteins and 5362 rat proteins. Comparison of human exosomal proteins and total cellular proteins reveals that some proteins exist in the exosomes exclusively that can be served as potential markers for exosomes. Quantitative proteomic analysis of exosomes from different passages of BMSCs shows that the proteins involved in TGF-β signaling pathway are regulated in abundance, which could be markers for the therapeutic ability of BMSC exosomes. Collectively, the data presented by this study can be a resource for further study of exosome research.

Transcriptional pathways linked to fetal and maternal hepatic dysfunction caused by gestational exposure to perfluorooctanoic acid (PFOA) or hexafluoropropylene oxide-dimer acid (HFPO-DA or GenX) in CD-1 mice

Per- and polyfluoroalkyl substances (PFAS) comprise a diverse class of chemicals used in industrial processes, consumer products, and fire-fighting foams which have become environmental pollutants of concern due to their persistence, ubiquity, and associations with adverse human health outcomes, including in pregnant persons and their offspring. Multiple PFAS are associated with adverse liver outcomes in adult humans and toxicological models, but effects on the developing liver are not fully described. Here we performed transcriptomic analyses in the mouse to investigate the molecular mechanisms of hepatic toxicity in the dam and its fetus after exposure to two different PFAS, perfluorooctanoic acid (PFOA) and its replacement, hexafluoropropylene oxide-dimer acid (HFPO-DA, known as GenX). Pregnant CD-1 mice were exposed via oral gavage from embryonic day (E) 1.5-17.5 to PFOA (0, 1, or 5 mg/kg-d) or GenX (0, 2, or 10 mg/kg-d). Maternal and fetal liver RNA was isolated (N = 5 per dose/group) and the transcriptome analyzed by Affymetrix Array. Differentially expressed genes (DEG) and differentially enriched pathways (DEP) were obtained. DEG patterns were similar in maternal liver for 5 mg/kg PFOA, 2 mg/kg GenX, and 10 mg/kg GenX (R2: 0.46-0.66). DEG patterns were similar across all 4 dose groups in fetal liver (R2: 0.59-0.81). There were more DEGs in fetal liver compared to maternal liver at the low doses for both PFOA (fetal = 69, maternal = 8) and GenX (fetal = 154, maternal = 93). Upregulated DEPs identified across all groups included Fatty Acid Metabolism, Peroxisome, Oxidative Phosphorylation, Adipogenesis, and Bile Acid Metabolism. Transcriptome-phenotype correlation analyses demonstrated > 1000 maternal liver DEGs were significantly correlated with maternal relative liver weight (R2 >0.92). These findings show shared biological pathways of liver toxicity for PFOA and GenX in maternal and fetal livers in CD-1 mice. The limited overlap in specific DEGs between the dam and fetus suggests the developing liver responds differently than the adult liver to these chemical stressors. This work helps define mechanisms of hepatic toxicity of two structurally unique PFAS and may help predict latent consequences of developmental exposure.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

Gastric Cancer Pre-Stage Detection and Early Diagnosis of Gastritis Using Serum Protein Signatures

Background: A gastric cancer (GC) diagnosis relies on histopathology. Endoscopy rates are increasing. Helicobacter pylori infection is a major GC risk factor. In an effort to elucidate abundant blood biomarkers, and potentially reduce the number of diagnostic surgical interventions, we investigated sera and biopsies from a cohort of 219 H. pylori positive and negative patients diagnosed with GC, gastritis, and ulcers. This allowed the comparative investigation of the different gastroduodenal diseases, and the exclusion of protein changes resulting from bacterial infection or inflammation of the gastric mucosa when searching for GC-dependent proteins. Methods: High-definition mass spectrometry-based expression analysis of tryptically digested proteins was performed, followed by multivariate statistical and network analyses for the different disease groups, with respect to H. pylori infection status. Significantly regulated proteins differing more than two-fold between groups were shortlisted, and their role in gastritis and GC discussed. Results: We present data of comparative protein analyses of biopsies and sera from patients suffering from mild to advanced gastritis, ulcers, and early to advanced GC, in conjunction with a wealth of metadata, clinical information, histopathological evaluation, and H. pylori infection status. We used samples from pre-malignant stages to extract prospective serum markers for early-stage GC, and present a 29-protein marker panel containing, amongst others, integrin β-6 and glutathione peroxidase. Furthermore, ten serum markers specific for advanced GC, independent of H. pylori infection, are provided. They include CRP, protein S100A9, and kallistatin. The majority of these proteins were previously discussed in the context of cancer or GC. In addition, we detected hypoalbuminemia and increased fibrinogen serum levels in gastritis. Conclusion: Two protein panels were suggested for the development of multiplex tests for GC serum diagnostics. For most of the elements contained in these panels, individual commercial tests are available. Thus, we envision the design of multi-protein assays, incorporating several to all of the panel members, in order to gain a level of specificity that cannot be achieved by testing a single protein alone. As their development and validation will take time, gastritis diagnosis based on the fibrinogen to albumin serum ratio may be a quick way forward. Its determination at the primary/secondary care level for early diagnosis could significantly reduce the number of referrals to endoscopy. Preventive measures are in high demand. The protein marker panels presented in this work will contribute to improved GC diagnostics, once they have been transferred from a research result to a practical tool.

Lysine demethylase 5C epigenetically reduces transcription of ITIH1 that results in augmented progression of liver hepatocellular carcinoma

Lysine demethylase 5C (KDM5C) is a member of the KDM family of demethylases and has been reported as a cancer driver. This study aimed to probe the function of KDM5C in the development of liver hepatocellular carcinoma (LIHC) and the molecules of action. According to data from publicly accessible bioinformatic databases, KDM5C is highly expressed in LIHC and associated with poor patient prognosis. High expression of KDM5C was detected in acquired LIHC cell lines. Downregulation of KDM5C weakened proliferation, migration, invasiveness, and resistance to death of the LIHC cells in vitro, and it reduced growth of the xenograft tumors in nude mice. Inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) was predicted as a downstream gene negatively regulated by KDM5C. KDM5C-regulated H3K4me1 modification at the promoter region of ITIH1, inducing its transcriptional inactivation. Further downregulation of ITIH1 in cancer cells blocked the functions of KDM5C silencing and restored the malignant behaviors of LIHC cells. The activity of the PI3K/AKT signaling was decreased following KDM5C downregulation but recovered upon ITIH1 silencing. In conclusion, this study suggested that KDM5C epigenetically reduces ITIH1 and activates the PI3K/AKT signaling pathway to promote LIHC progression.