HCC 1 Human, His

What is HCC-1 and how was it initially discovered?

HCC-1 is a novel CC chemokine that was first isolated from the hemofiltrate of patients with chronic renal failure. Unlike other chemokines, it is constitutively expressed in several normal tissues and circulates at high concentrations (1-80 nM) in human plasma. The initial isolation and characterization of HCC-1 revealed it to be a protein with a relative molecular mass of 8,673 Da, consisting of 74 amino acids including four cysteines linked by disulfide bonds. The HCC-1 cDNA was subsequently cloned from human bone marrow and found to code for the mature protein plus a putative 19-residue leader sequence.

Where is HCC-1 expressed in normal human tissues?

Unlike most CC chemokines which are expressed primarily in response to inflammatory stimuli, HCC-1 is expressed constitutively in several normal tissues. These tissues include spleen, liver, skeletal muscle, heart muscle, gut, and bone marrow. This wide distribution suggests that HCC-1 may have physiological functions beyond the typical inflammatory roles associated with most chemokines. The constitutive expression contributes to its remarkably high concentration in plasma (1-80 nM), which is unusual for a chemokine.

What post-translational modifications of HCC-1 have been identified?

Research has identified several distinct post-translationally processed forms of HCC-1 circulating in human blood. Western blot analysis of human plasma extracts revealed an HCC-1 immunoreactive double band at 8-10 kDa, indicating the presence of at least two distinct HCC-1 peptides. These have been identified as predominantly HCC-1 (1-74) and glycosylated HCC-1 (1-74). The glycosylated form exhibits a molecular mass of 9621 Da due to O-glycosylation at position 7 (Ser-7) with two N-acetylneuraminic acids and the disaccharide N-acetylgalactosamine galactose. Additionally, N-terminally truncated forms including HCC-1 (3-74) and HCC-1 (4-74) have been identified in human blood filtrate.

How do different processed forms of HCC-1 affect its biological activity?

The post-translational processing of HCC-1 has been shown to modulate its biological properties, suggesting that these modifications play important roles in regulating HCC-1 function. In human hemofiltrate, approximately 3% of total HCC-1 represents HCC-1 (3-74) and approximately 1% represents HCC-1 (4-74), while the major products are non-glycosylated HCC-1 (1-74) and glycosylated HCC-1 (1-74). The N-terminal processing and modification of HCC-1 are likely important in displaying its full biological activity, though the specific functional differences between these forms require further research. This variability in processing may explain some of the nuanced biological effects observed with HCC-1 in different experimental contexts.

What receptor interactions mediate HCC-1 cellular effects?

HCC-1 has been shown to act via receptors that also recognize MIP-1 alpha, demonstrating overlap in receptor usage with other CC chemokines. On human monocytes, HCC-1 induces intracellular Ca²⁺ changes and enzyme release at concentrations of 100-1,000 nM, but notably does not induce chemotaxis. This contrasts with its effects on CD34+ myeloid progenitor cells, where HCC-1 enhances proliferation with efficacy similar to MIP-1 alpha, though approximately 100-fold less potent. The receptor interactions appear to be specific to certain cell types, as HCC-1 is inactive on T lymphocytes, neutrophils, and eosinophil leukocytes.

How are human-correlated genetic models advancing HCC research?

Recent advances in hepatocellular carcinoma research have involved the integration of transcriptomic data from mouse models with human HCC data to identify common human-mouse subtype clusters. This approach has allowed researchers to develop more accurate models that reflect the heterogeneity of human HCC. By mapping mouse end-stage HCC data onto human HCC data using techniques like nonlinear dimensionality reduction, researchers have identified four distinct clusters common across human and mouse models, referred to as HuMo clusters. These models recapitulate the full range of human HCC transcriptionally, including within individual clusters.

What are the main characteristics of the HuMo classification system for HCC?

The HuMo classification system for hepatocellular carcinoma identifies four distinct clusters (HuMo 1-4) with specific molecular and histopathological characteristics:

• HuMo cluster 1: Characterized by well-differentiated HCC, enriched for immune-evasive signatures, including the immune-excluded subclass, and de-enriched for immune checkpoint inhibitor (ICI) response signatures.

• HuMo cluster 2: Features higher inflammatory signaling signatures and is enriched for immune-active tumors without WNT–β-catenin activation. Patients in this cluster showed improved survival probability relative to other clusters.

• HuMo cluster 3: Displays deposition of extracellular matrix and moderately differentiated HCC with a strong progenitor signature.

• HuMo cluster 4: Exhibits poorly differentiated HCC, significantly enriched for the inflamed HCC class with an immune-exhaustion signature and characterized by TGFβ and EMT signatures.

How does the HuMo classification improve upon previous HCC classification systems?

The HuMo classification provides several advantages over previous systems like the Hoshida classification. Most notably, it distinguishes two patient populations within the Hoshida S3 molecular subclass (HuMo clusters 1 and 2), which Hoshida et al. had implied might exist based on CTNNB1 status but did not formally separate. This distinction revealed previously unappreciated differences in patient survival, with HuMo cluster 2 patients showing improved survival probability. The classification also separates immune-excluded (HuMo cluster 1) from immune-active (HuMo cluster 2) subclasses, providing greater precision in understanding the immune microenvironment of different HCC subtypes. The HuMo system surpasses previous attempts at comparing mouse and human HCC data in both scale and detail.

What are established methods for isolating and characterizing different forms of HCC-1?

The isolation of HCC-1 and its variants typically involves a multi-step process. In the original discovery, HCC-1 was isolated from the hemofiltrate of patients with chronic renal failure. For characterizing different forms, researchers employ peptide libraries from human blood filtrate followed by techniques like Western blot analysis to identify HCC-1 immunoreactive bands. The distinct forms can be separated based on their molecular weight differences (8-10 kDa range). Glycosylated forms exhibit higher molecular weights (around 9621 Da) compared to non-glycosylated forms. Molecular techniques including mass spectrometry are essential for precise characterization of modifications such as O-glycosylation at position 7 (Ser-7) with two N-acetylneuraminic acids and the disaccharide N-acetylgalactosamine galactose.

What experimental approaches are effective for studying HCC-1 biological activities?

For studying HCC-1 biological activities, researchers typically assess:

• Calcium mobilization: Measuring intracellular Ca²⁺ changes in responsive cells (particularly monocytes) upon HCC-1 exposure at concentrations of 100-1,000 nM.

• Enzyme release assays: Quantifying specific enzyme release from monocytes following HCC-1 stimulation.

• Chemotaxis assays: Evaluating cellular migration in response to HCC-1 (notably, HCC-1 does not induce chemotaxis in most cell types).

• Proliferation assays: Particularly with CD34+ myeloid progenitor cells, where HCC-1 enhances proliferation with efficacy similar to MIP-1 alpha but approximately 100-fold less potent.

• Receptor binding studies: Identifying which receptors mediate HCC-1 effects, particularly those that also recognize MIP-1 alpha.

How can transcriptomic approaches be optimized for cross-species HCC research?

Optimizing transcriptomic approaches for cross-species HCC research involves several key methodological considerations:

• Integration of diverse model systems: Including genetically engineered mouse models (GEMMs), carcinogen-induced (TOX), and orthotopic transplant (OT) HCC mouse models to comprehensively compare with human HCC.

• Dimensionality reduction techniques: Employing methods such as uniform manifold approximation and projection (UMAP) to map mouse end-stage HCC data onto human HCC data.

• Validation across multiple datasets: Testing classification systems on independent datasets of human HCC to confirm reproducibility of findings.

• Correlation with histopathological features: Ensuring that mouse and human tissue belonging to the same cluster have analogous morphological characteristics.

• Survival analysis across species: Comparing survival metrics between patients and respective GEMMs across multiple molecular subtype classifications to validate biological relevance.

This approach has proven valuable in identifying four distinct clusters common across human and mouse models that recapitulate the full range of human HCC transcriptionally, with alignment of histopathological features and relative survival within clusters.

What are the main challenges in translating HCC mouse model findings to human applications?

A significant challenge in translating HCC mouse model findings to human applications is the heterogeneity of HCC. As noted in the research, HCC is "highly heterogeneous making a one-size fits all option problematic." Additionally, "patients with similar disease phenotype can have different molecular etiology making treatment responses different." Another challenge is that mutational status is not always indicative of signaling status, and genomic profiling has shown that mutations are not exclusively prognostic of association with specific subtypes. This is particularly relevant for advanced disease stages with high mutational burden, where different genetic alterations can influence each other.

How might research on HCC-1 contribute to understanding liver cancer pathogenesis?

While direct evidence linking HCC-1 (the chemokine) to hepatocellular carcinoma pathogenesis is not explicitly stated in the search results, there are potential research directions worth exploring. As HCC-1 is constitutively expressed in normal liver tissue, alterations in its expression or post-translational modifications might play roles in liver pathology. Given that inflammatory processes and immune responses are critical in HCC development and progression, and HCC-1 has effects on immune cells like monocytes and myeloid progenitor cells, investigating its role in the tumor microenvironment could yield valuable insights. The discovery that HCC-1 enhances the proliferation of CD34+ myeloid progenitor cells suggests it might influence cellular proliferation pathways relevant to cancer development.

What novel therapeutic approaches are emerging from molecular classification of HCC?

The molecular classification of HCC is enabling more targeted therapeutic approaches. The preclinical platform and classification system developed through human-correlated genetic models can streamline preclinical research and increase comparability of different mouse models. By linking preclinical models with patient data, researchers can better stratify patients for treatment, identify new therapies, and improve the likelihood of translational success. One specific example mentioned is the identification of an FDA-approved anti-cancer drug, cladribine—not previously linked to HCC—that showed efficacy and improved survival in vivo when combined with standard-of-care treatment in a clinically relevant model. This approach of linking preclinical models to human data in a subtype-specific manner holds promise for translational research in HCC and potentially other solid cancers.