Diagnostic value of clusterin immunostaining in hepatocellular carcinoma

Decoding CLU (Clusterin): Conquering cancer treatment resistance and immunological barriers

One major obstacle in the treatment of cancer is the presence of proteins resistant to cancer therapy, which can impede the effectiveness of traditional approaches such as radiation and chemotherapy. This resistance can lead to disease progression and cause treatment failure. Extensive research is currently focused on studying these proteins to create tailored treatments that can circumvent resistance mechanisms. CLU (Clusterin), a chaperone protein, has gained notoriety for its role in promoting resistance to a wide range of cancer treatments, including chemotherapy, radiation therapy, and targeted therapy. The protein has also been discovered to have a role in regulating the immunosuppressive environment within tumors. Its ability to influence oncogenic signaling and inhibit cell death bolster cancer cells resistant against treatments, which poses a significant challenge in the field of oncology. Researchers are actively investigating to the mechanisms by which CLU exerts its resistance-promoting effects, with the ultimate goal of developing strategies to circumvent its impact and enhance the effectiveness of cancer therapies. By exploring CLU's impact on cancer, resistance mechanisms, tumor microenvironment (TME), and therapeutic strategies, this review aims to contribute to the ongoing efforts to improve cancer treatment outcomes.

Ancillary tests for hepatobiliary neoplasms: what we know and what we need to know

Ancillary tests are commonly used in the surgical pathology setting for diagnosing challenging neoplastic diseases of the liver and biliary tract, while histology and clinical correlation remain to be critically important. With continuous discoveries, more and more useful ancillary tests have become available, which can help distinguish between malignant and benign hepatocellular neoplasms, malignant and benign biliary tract entities, and intrahepatic and metastatic carcinomas. This review will focus on existing and emerging biomarkers (such as glutamine synthetase, organic anion transporting polypeptide 1B3, insulin-like growth factor-II mRNA binding protein-3, S100P, SMAD4, enhancer of zeste homolog 2, albumin, hepatocyte nuclear factor-1β, etc.) that can be used for the diagnosis, classification and prognostication of hepatobiliary neoplasms.

Identification of a novel bile marker clusterin and a public online prediction platform based on deep learning for cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma (CCA) is a highly aggressive malignant tumor, and its diagnosis is still a challenge. This study aimed to identify a novel bile marker for CCA diagnosis based on proteomics and establish a diagnostic model with deep learning.

METHODS

A total of 644 subjects (236 CCA and 408 non-CCA) from two independent centers were divided into discovery, cross-validation, and external validation sets for the study. Candidate bile markers were identified by three proteomics data and validated on 635 clinical humoral specimens and 121 tissue specimens. A diagnostic multi-analyte model containing bile and serum biomarkers was established in cross-validation set by deep learning and validated in an independent external cohort.

RESULTS

The results of proteomics analysis and clinical specimen verification showed that bile clusterin (CLU) was significantly higher in CCA body fluids. Based on 376 subjects in the cross-validation set, ROC analysis indicated that bile CLU had a satisfactory diagnostic power (AUC: 0.852, sensitivity: 73.6%, specificity: 90.1%). Building on bile CLU and 63 serum markers, deep learning established a diagnostic model incorporating seven factors (CLU, CA19-9, IBIL, GGT, LDL-C, TG, and TBA), which showed a high diagnostic utility (AUC: 0.947, sensitivity: 90.3%, specificity: 84.9%). External validation in an independent cohort (n = 259) resulted in a similar accuracy for the detection of CCA. Finally, for the convenience of operation, a user-friendly prediction platform was built online for CCA.

CONCLUSIONS

This is the largest and most comprehensive study combining bile and serum biomarkers to differentiate CCA. This diagnostic model may potentially be used to detect CCA.

Molecular delineation, expression profiling, immune response, and anti-apoptotic function of a novel clusterin homolog from big-belly seahorse (Hippocampus abdominalis)

Clusterin (CLU) is a glycoprotein that contains α- and β-chains. CLU exerts multifunctional activities and plays a role in different cell signaling pathways that are associated with various diseases such as proteotoxic and oxidative stress, as well as cell death and survival. However, its role in marine teleost fish remains unclear. Therefore, the present study was carried out to characterize and investigate the immune responses and anti-apoptotic effects of CLU of the big-belly seahorse (Hippocampus abdominalis) (HaCLU) on oxidative stress-induced cell death. The HaCLU open reading frame was 1389 bp long and encoded a protein with 462 amino acids, a molecular weight of 51.28 kDa and an isoelectric point of 5.41. In-silico results demonstrated that HaCLU has a signal peptide in the 1-29 amino acid region, while the α- and β-chains were in the 34-227 and 228-455 amino acid regions, respectively. Multiple sequence alignment clarified the low homology of the α-chain with other orthologs. The highest HaCLU mRNA expression level was observed in the liver, followed by the heart, spleen, and brain tissues of healthy big-belly seahorses. Further, HaCLU mRNA expression level was elevated in the liver in response to different stimuli, including lipopolysaccharides, polyinosinic:polycytidylic acid, Edwardsiella tarda, and Streptococcus iniae. HaCLU potentiates cell viability and weakens chromatin condensation in the nucleus of FHM cells following H₂O₂-induced oxidative stress and subsequent cell death. HaCLU overexpression resulted in a reduced Bax/Bcl-2 mRNA expression ratio. This study revealed the role of HaCLU in immune regulation against pathogenic infections and its anti-apoptotic effects on oxidative stress-induced cell death.

Encouraging specific biomarkers-based therapeutic strategies for hepatocellular carcinoma

The prevention, early discovery and effective treatment of patients with hepatocellular carcinoma (HCC) remain a global medical challenge. At present, HCC is still mainly treated by surgery, supplemented by vascular embolization, radio frequency, radiotherapy, chemotherapy and biotherapy. The application of multikinase inhibitor sorafenib, chimeric antigen receptor T cells, or PD-1/PD-L1 inhibitors can prolong the median survival of HCC patients. However, the treatment efficacy is still unsatisfactory due to HCC metastasis and postoperative recurrence. During the process of hepatocyte malignant transformation, HCC tissues can express and secrete many types of specific biomarkers, or oncogenic antigen molecules into blood, for example, alpha-fetoprotein, glypican-3, Wnt3a (one of the key signaling molecules in the Wnt/β-catenin pathway), insulin-like growth factor (IGF)-II or IGF-I receptor, vascular endothelial growth factor, secretory clusterin and so on. In addition, combining immunotherapy with non-coding RNAs might improve anti-cancer efficacy. These biomarkers not only contribute to HCC diagnosis or prognosis, but may also become molecular targets for HCC therapy under developing or clinical trials. This article reviews the progress in emerging biomarkers in basic research or clinical trials for HCC immunotherapy.