Clin Mol Hepatol > Volume 31(1); 2025 > Article
Ye and Zhou: Correspondence to editorial on “Development and validation of a stromal-immune signature to predict prognosis in intrahepatic cholangiocarcinoma”
Dear Editor,
We sincerely appreciated Dr. Sergi Marco and Dr. Chiara Braconi for their valuable and insightful comments [1] regarding our recently published paper titled “Development and validation of a stromal-immune signature to predict prognosis in intrahepatic cholangiocarcinoma” [2]. Their comments not only highlighted our contribution in predicting prognosis in intrahepatic cholangiocarcinoma after surgical resection, but also provided profound insights for the shortcoming of our research as well as possible future research directions in this field.
Intrahepatic cholangiocarcinoma (ICC) is the second most common primary hepatic malignancy with limited treatment [3]. Therefore, new biomarkers for predicting prognosis and the need for new therapies for ICC are of urgent significance. As noted in the editorial, the tumor microenvironment (TME) of ICC, consisting of a variety of cells (cancer cells, stroma cells, immune cells, etc.), has become a focus of study in ICC. In this work [2], based on the tumor stromal composition and immune context, we integrated the stromal-immune signature to predict recurrence-free survival (RFS) and overall survival (OS) in patient of ICC, which is a cost-effective and convenient classifier comparing with complex gene signatures.
In the aspect of tumor stromal composition, we investigated the prognostic value of α-smooth muscle actin (α-SMA)-positive cancer-associated fibroblasts (CAFs) and collagen type 1 fiber deposition. We classified the patients into four groups, dormant (low α-SMA/high collagen), inert (low α-SMA/low collagen), fibrogenic (high α-SMA/high collagen), or fibrolytic (high α-SMA/low collagen), in terms of α-SMA/collagen expression. Four groups of patients showed distinct RFS and OS, reflecting the importance of “stroma-tology” mentioned in the editorial. However, CAFs showed high heterogeneity in their origin, transcriptome, and function. Identified by scRNA-sequencing, human pan-CAF subtypes have been characterized and expanded. Specifically in ICC, CAFs are characterized by expression markers including: α-SMA, collagen type I alpha-1 (COL1A1), vimentin, fibroblast activation protein (FAP), plateletderived growth factor receptor-alpha (PDGFR-α), and platelet-derived growth factor receptor-beta (PDGFR-β) [4]. Yet, more comprehensive research are needed to unveil the next chapter of CAFs regarding their biomarkers and functions. Interestingly, besides our perspective of stromalimmune integration, a publication revealed the clinically relevant cancer cell-stroma interaction dynamics in head and neck cancer throughout single-cell resolution quantitative image analysis combined with spatial transcriptomics [5]. Deciphering the mechanisms by which tumor, immune cells and stromal cells drive cancer aggression is crucial for the advancement of targeted therapies. As Dr. Sergi Marco and Dr. Chiara Braconi emphasized the importance of further research regarding profiling different CAFs, we agreed that we could enhance our analysis more precisely by exploring the diversity of CAFs as they might function and interact uniquely in TME, deepening our understanding of stromal components and offering new insights into therapeutic strategies.
Equally, not only the number, but the diversity of immune cells such as macrophages, neutrophils, T-lymphocytes, did influence the TME and had an impact on patients’ survival. In our work, we stained CD3, CD4, CD8, Foxp3, CD68, CD66b to investigate the infiltration of T helper cells (CD4+ T cells), cytotoxic T cells (CD8+ T cells), regulatory T cells (Tregs) and their associations with stroma and patients’ clinical outcomes. Finally, we sorted out six classes, characterizing a unique stromal-immune signature with decreased median RFS and OS. We found that Group VI, defined by low CD8+ T cell infiltration and high neutrophil infiltration, displayed the worst survival prediction, suggesting the protumoral effect of tumor-associated neutrophils (TANs), which aligned with our previous finding of TANs in hepatocellular carcinoma (HCC) [6]. Interestingly, a recent work indicated the neutrophil divergence across cancers and suggested therapeutic opportunities such as antigenpresenting neutrophil delivery [7]. Thus, the heterogeneous functionality of immune cells may affect TME as well as tumor biology. Concordantly, Dr. Sergi Marco and Dr. Chiara Braconi noted that the heterogeneous functionality of Tlymphocytes and TAMs might contribute to immunosuppressive TME and are worthy of further research. We acknowledged deeper profiling of immune landscape can help accurately sort out valuable subtypes of immune cells and expand our understanding of tumor immunology.
Given that ICC represented high heterogeneity spatiotemporally at macroscopic level and molecular level (including genomics, transcriptomics, proteomics) [8-10]. Previously, our team have explored the ICC microbiome and its association with prognosis [11], KRAS and BRAF variant subtypes with prognosis in patients with ICC [12,13]. With the advancement of ICC therapeutic strategies, the number of ICC patients receiving adjuvant treatment after surgical resection is increasing. Thus, the development of predictive biomarkers of response to adjuvant treatment are of necessity and significance. We are committed to exploring the complicated TME to improve precision and personalized medicine in the future.

ACKNOWLEDGMENTS

This study was jointly supported by the National Natural Science Foundation of China (No. 82372985, No. 82373418, No. 82273247, No. 82173260, No. 82072681, No. 82003082), Shanghai Technical Standard Program (21DZ2201100) and Shanghai Medical Innovation Research Project (22Y11907300).

FOOTNOTES

Authors’ contribution
YHY drafted the manuscript. SLZ contributed to the conception, critical revision, and final approval of the manuscript.
Conflicts of Interest
The authors have no conflicts to disclose.

Abbreviations

CAFs
cancer-associated fibroblasts
COL1A1
collagen type I alpha-1
FAP
fibroblast activation protein
HCC
hepatocellular carcinoma
ICC
intrahepatic cholangiocarcinoma
OS
overall survival
PDGFR-α
platelet-derived growth factor receptor-alpha
PDGFR-β
platelet-derived growth factor receptor-beta
RFS
recurrencefree survival
TANs
tumor-associated neutrophils
TME
tumor microenvironment
Tregs
regulatory T cells
α-SMA
α-smooth muscle actin

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