CRABP2 regulates infiltration of cancer-associated fibroblasts and immune response in melanoma

Abstract

Finding biomarkers for immunotherapy is an urgent issue in cancer treatment. Cellular retinoic acid-binding protein 2 (CRABP2) is a controversial factor in the occurrence and development of human tumors. However, there is limited research on the relationship between CRABP2 and immunotherapy response. This study found that negative correlations of CRABP2 and immune checkpoint markers (PD-1, PD-L1, and CTLA-4) were observed in breast invasive carcinoma (BRCA), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD) and testicular germ cell tumors (TGCT). In particular, in SKCM patients who were treated with PD-1 inhibitors, high levels of CRABP2 predicted poor prognosis. Additionally, CRABP2 expression was elevated in cancer-associated fibroblasts (CAFs) at the single-cell level. The expression of CRABP2 was positively correlated with markers of CAFs, such as MFAP5, PDPN, ITGA11, PDGFRα/β and THY1 in SKCM. To validate the tumor-promoting effect of CRABP2 in vivo , SKCM xenograft mice models with CRABP2 overexpression have been constructed. These models showed an increase in tumor weight and volume. Enrichment analysis indicated that CRABP2 may be involved in immune-related pathways of SKCM, such as extracellular matrix (ECM) receptor interaction and epithelial-mesenchymal transition (EMT). The study suggests that CRABP2 may regulate immunotherapy in SKCM patients by influencing infiltration of CAFs. In conclusion, this study provides new insights into the role of CRABP2 in immunotherapy response. The findings suggest that CRABP2 may be a promising biomarker for PD-1 inhibitors in SKCM patients. Further research is needed to confirm these findings and to explore the clinical implications of CRABP2 in immunotherapy.

Predictive Factors of Immunotherapy in Gastric Cancer: A 2024 Update

“…There is debate regarding the role of cellular retinoic acid-binding protein 2 (CRABP2) in the emergence and progression of human cancers. A negative correlation between CRABP2 and the immune checkpoint markers PD-1, PD-L1, and CTLA-4 was observed [ 22 ].…”

“…disulfidptosis-related gene prognostic risk model [4] -M2 macrophages were strongly correlated with a high PANscore [5] predictive signature AC129926.1, AC023511.1, AP002954.1, LINC01537, and TMEM7 based on CRLs [6] -ARLSig has strong predictive value for the survival of GC patients [7] -PRS was created using the TCGA, GSE15459, GSE26253, GSE62254, and GSE84437 datasets [8] -PI3K pathway linked to PD-L1 positivity is linked to increased immunotherapy efficacy [9] potentially valid serum predictive markers for identifying individuals who might profit from PD-1 inhibitors paired with chemotherapy include IL-6, IL-2, IL-17A, and NLR [10] -PD-L1+CD68+ macrophages may be a viable prognostic indicator in primary GC patients [11] -ITGB1 may be an effective prognostic biomarker and a useful predictor of outcome for GC patients receiving anti-PD-1 medication [12] a reduced tumor mass, absence or small number of lymph node metastases, and a large combined positive score; neoadjuvant chemotherapy plus PD-1 antibodies for the prediction of pCR in AGC patients undergoing neoadjuvant chemotherapy combined with PD-1 antibody immunotherapy [13] memory PD-1+CD8+ T cells and the ratio of PD-1+CD8+ T cells to PD-1+CD4+ T cells may be useful for identifying individuals who would benefit from immunotherapy among AGC patients [14] the CD4+/CD8+ ratio may be a potential predictive indicator for patients under PD-1 inhibitor-based combination therapy for advanced gastric and esophageal cancer, and it can independently predict dermatological damage [15] -MFSD2A may function as a prognostic biomarker for the response to anti-PD-1 immunotherapy in AGC patients [16] the peripheral CD4+ T-cell subset has shown significant predictive value for therapeutic response and longer survival in AGC patients [17] patients with GC receiving combination immunotherapy are predicted to respond better when HSPA4 is upregulated [18] the combination of Tregs, Ki-67, and age (65 years or older) can more accurately predict the likelihood of unfavorable responses [19] the incidence of irAEs could serve as a stand-in marker for ICIs [20] utilizing biomarkers based on the numbers of various lymphocyte subpopulations, it is possible to predict the clinical prognosis and efficacy of immunotherapy in patients with AGC [21] a negative correlation between CRABP2 and the immune checkpoint markers PD-1, PD-L1, and CTLA-4 was observed [22] Table 2. Major developments in genetic predictive factors research.…”