Gut microbiota reshapes cancer immunotherapy efficacy: Mechanisms and therapeutic strategies.

Gut microbiota is essential for maintaining local and systemic immune homeostasis in the presence of bacterial challenges. It has been demonstrated that microbiota play contrasting roles in cancer development as well as anticancer immunity. Cancer immunotherapy, a novel anticancer therapy that relies on the stimulation of host immunity, has suffered from a low responding rate and incidence of severe immune-related adverse events (irAEs). Previous studies have demonstrated that the diversity and composition of gut microbiota were associated with the heterogeneity of therapeutic effects. Therefore, alteration in microbiota taxa can lead to improved clinical outcomes in immunotherapy. In this review, we determine whether microbiota composition or microbiota-derived metabolites are linked to responses to immunotherapy and irAEs. Moreover, we discuss various approaches to improve immunotherapy efficacy or reduce toxicities by modulating microbiota composition.

Single-cell RNA sequencing elucidated the landscape of breast cancer brain metastases and identified ILF2 as a potential therapeutic target.

Distant metastasis remains the primary cause of morbidity in patients with breast cancer. Hence, the development of more efficacious strategies and the exploration of potential targets for patients with metastatic breast cancer are urgently needed. The data of six patients with breast cancer brain metastases (BCBrM) from two centres were collected, and a comprehensive landscape of the entire tumour ecosystem was generated through the utilisation of single-cell RNA sequencing. We utilised the Monocle2 and CellChat algorithms to investigate the interrelationships among each subcluster. In addition, multiple signatures were collected to evaluate key components of the subclusters through multi-omics methodologies. Finally, we elucidated common expression programs of malignant cells, and experiments were conducted in vitro and in vivo to determine the functions of interleukin enhancer-binding factor 2 (ILF2), which is a key gene in the metastasis module, in BCBrM progression. We found that subclusters in each major cell type exhibited diverse characteristics. Besides, our study indicated that ILF2 was specifically associated with BCBrM, and experimental validations further demonstrated that ILF2 deficiency hindered BCBrM progression. Our study offers novel perspectives on the heterogeneity of BCBrM and suggests that ILF2 could serve as a promising biomarker or therapeutic target for BCBrM.

Pan-Cancer Single-Cell and Spatial-Resolved Profiling Reveals the Immunosuppressive Role of APOE+ Macrophages in Immune Checkpoint Inhibitor Therapy.

The heterogeneity of macrophages influences the response to immune checkpoint inhibitor (ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI therapy using single-cell RNA sequencing (scRNA-seq) and machine learning methods. The scRNA-seq and bulk RNA-seq data are Integrated to construct an M.Sig model for predicting ICI response based on the distinct molecular signatures of macrophage and machine learning algorithms. Comprehensive single-cell analysis as well as in vivo and in vitro experiments are applied to explore the potential mechanisms of the APOE+ macrophage in affecting ICI response. The M.Sig model shows clear advantages in predicting the efficacy and prognosis of ICI therapy in pan-cancer patients. The proportion of APOE+ macrophages is higher in ICI non-responders of triple-negative breast cancer compared with responders, and the interaction and longer distance between APOE+ macrophages and CD8+ exhausted T (Tex) cells affecting ICI response is confirmed by multiplex immunohistochemistry. In a 4T1 tumor-bearing mice model, the APOE inhibitor combined with ICI treatment shows the best efficacy. The M.Sig model using real-world immunotherapy data accurately predicts the ICI response of pan-cancer, which may be associated with the interaction between APOE+ macrophages and CD8+ Tex cells.

PIWI-interacting RNA-YBX1 inhibits proliferation and metastasis by the MAPK signaling pathway via YBX1 in triple-negative breast cancer.

Breast cancer is the second leading cause of death in women worldwide, with triple-negative breast cancer (TNBC) having the worst prognosis. Although there are numerous studies on TNBC, there is no effective treatment for it, and it is still a major problem today. Studies on PIWI-interacting RNAs (piRNAs) are increasing and investigating the mechanism of piRNAs in the proliferation and metastasis of TNBC may lead to new potential treatment targets. Here, we identified a novel piRNA, piR-YBX1, which was downregulated in TNBC compared to matched normal breast tissue. Overexpression of piR-YBX1 significantly inhibited the proliferation, migration, invasion ability of TNBC cells both in vivo and in vitro. Mechanistically, piR-YBX1 could bind directly to mRNA of Y-box binding protein 1 (YBX1) and overexpression of piR-YBX1 downregulated YBX1 in both mRNA and protein levels, while the function of piR-YBX1 could be partly rescued by overexpression of YBX1. In addition, YBX1 could bind to RAF1 which is the key molecule in the MAPK signaling pathway, and overexpression of piR-YBX1 inhibited the p-MEK and p-ERK1/2, which can be reverted by YBX1. In conclusion, our findings discovered that the piR-YBX1/YBX1/MAPK axis suppresses the proliferation and metastasis of TNBC and therefore piR-YBX1 has the potential to be an effective therapeutic agent for breast cancer.

AURKAIP1 actuates tumor progression through stabilizing DDX5 in triple negative breast cancer.

Aurora-A kinase interacting protein 1 (AURKAIP1) has been proved to take an intermediary role in cancer by functioning as a negative regulator of Aurora-A kinase. However, it remains unclear whether and how AURKAIP1 itself would directly engage in regulating malignancies. The expression levels of AURKAIP1 were detected in triple negative breast cancer (TNBC) by immunohistochemistry and western blots. The CCK8, colony formation assays and nude mouse model were conducted to determine cell proliferation whereas transwell and wound healing assays were performed to observe cell migration. The interaction of AURKAIP1 and DEAD-box helicase 5 (DDX5) were verified through co-immunoprecipitation and successively western blots. From the results, we found that AURKAIP1 was explicitly upregulated in TNBC, which was positively associated with tumor size, lymph node metastases, pathological stage and unfavorable prognosis. AURKAIP1 silencing markedly inhibited TNBC cell proliferation and migration in vitro and in vivo. AURKAIP1 directly interacted with and stabilized DDX5 protein by preventing ubiquitination and degradation, and DDX5 overexpression successfully reversed proliferation inhibition induced by knockdown of AURKAIP1. Consequently, AURKAIP1 silencing suppressed the activity of Wnt/ß-catenin signaling in a DDX5-dependent manner. Our study may primarily disclose the molecular mechanism by which AURKAIP1/DDX5/ß-catenin axis modulated TNBC progression, indicating that AURKAIP1 might serve as a therapeutic target as well as a TNBC-specific biomarker for prognosis.

Dissection of FOXO1-Induced LYPLAL1-DT Impeding Triple-Negative Breast Cancer Progression via Mediating hnRNPK/ß-Catenin Complex.

Triple-negative breast cancer (TNBC) is considered as the most hazardous subtype of breast cancer owing to its accelerated progression, enormous metastatic potential, and refractoriness to standard treatments. Long noncoding RNAs (lncRNAs) are extremely intricate in tumorigenesis and cancerous metastasis. Nonetheless, their roles in the initiation and augmentation of TNBC remain elusive. Here, in silico analysis and validation experiments were utilized to analyze the expression pattern of clinically effective lncRNAs in TNBC, among which a protective lncRNA LYPLAL1-DT was essentially curbed in TNBC samples and indicated a favorable prognosis. Gain- and loss-of-function assays elucidated that LYPLAL1-DT considerably attenuated the proliferative and metastatic properties along with epithelial-mesenchymal transition of TNBC cells. Moreover, forkhead box O1 (FOXO1) was validated to modulate the transcription of LYPLAL1-DT. Mechanistically, LYPLAL1-DT impinged on the malignancy of TNBC mainly by restraining the aberrant reactivation of the Wnt/ß-catenin signaling pathway, explicitly destabilizing and diminishing ß-catenin protein by interacting with heterogeneous nuclear ribonucleoprotein K (hnRNPK) and constricting the formation of the hnRNPK/ß-catenin complex. Conclusively, our present research revealed the anti-oncogenic effects of LYPLAL1-DT in TNBC, unraveling the molecular mechanisms of the FOXO1/LYPLAL1-DT/hnRNPK/ß-catenin signaling axis, which shed innovative light on the potential curative medicine of TNBC.

Circular RNA: A promising new star of vaccine.

Circular RNAs (circRNAs) are a class of single-stranded RNAs with covalently closed structures. Owing to their not having 3' or 5' ends, circRNAs are highly durable and insusceptible to exonuclease-mediated degradation. Moreover, some circRNAs with certain structures are translatable, making them novel vaccines. Vaccines are efficient tools for immunotherapy, such as for the prevention of infectious diseases and cancer treatment. The immune system is activated during immunotherapy to fight against abnormal allies or invaders. CircRNA vaccines represent a potential new avenue in the vaccine era. Recently, several circRNA vaccines have been synthesized and tested in vitro and in vivo. Our review briefly introduces the current understanding of the biology and function of translatable circRNAs, molecular biology, synthetic methods, delivery of circRNA, and current circRNA vaccines. We also discussed the challenges and future directions in the field by summarizing the developments in circRNA vaccines in the past few years.

Comprehensive metabolome and transcriptome analyses demonstrate divergent anthocyanin and carotenoid accumulation in fruits of wild and cultivated loquats.

Eriobotrya is an evergreen fruit tree native to South-West China and adjacent countries. There are more than 26 loquat species known in this genus, while E. japonica is the only species yet domesticated to produce fresh fruits from late spring to early summer. Fruits of cultivated loquat are usually orange colored, in contrast to the red color of fruits of wild E. henryi (EH). However, the mechanisms of fruit pigment formation during loquat evolution are yet to be elucidated. To understand these, targeted carotenoid and anthocyanin metabolomics as well as transcriptomics analyses were carried out in this study. The results showed that ß-carotene, violaxanthin palmitate and rubixanthin laurate, totally accounted for over 60% of the colored carotenoids, were the major carotenoids in peel of the orange colored 'Jiefangzhong' (JFZ) fruits. Total carotenoids content in JFZ is about 10 times to that of EH, and the expression levels of PSY, ZDS and ZEP in JFZ were 10.69 to 23.26 folds to that in EH at ripen stage. Cyanidin-3-O-galactoside and pelargonidin-3-O-galactoside were the predominant anthocyanins enriched in EH peel. On the contrary, both of them were almost undetectable in JFZ, and the transcript levels of F3H, F3'H, ANS, CHS and CHI in EH were 4.39 to 73.12 folds higher than that in JFZ during fruit pigmentation. In summary, abundant carotenoid deposition in JFZ peel is well correlated with the strong expression of PSY, ZDS and ZEP, while the accumulation of anthocyanin metabolites in EH peel is tightly associated with the notably upregulated expressions of F3H, F3'H, ANS, CHS and CHI. This study was the first to demonstrate the metabolic background of how fruit pigmentations evolved from wild to cultivated loquat species, and provided gene targets for further breeding of more colorful loquat fruits via manipulation of carotenoids and anthocyanin biosynthesis.

Novel Implication of the Basement Membrane for Breast Cancer Outcome and Immune Infiltration.

Therapeutic failure in breast cancer patients is largely attributed to postoperative advancement and therapy resistance. Nevertheless, an efficacious prognostic signature for recognizing this population is lacking. The basement membrane (BM) has been proven to be strongly involved in cancer progression and metastasis, and has the potential to be a powerful predictor in breast cancer. In this study, substantial bulk RNA transcriptomics, single cell RNA transcriptomics and clinical information were collected from TCGA-BRCA, METABRIC and GSE96058, and Kaplan-Meier survival curves, single cell analysis and in vitro experiments were conducted to validate the signature. From the results, a prognostic index, namely, the BMscore, was established with six pivotal BM genes, specifically LOXL1, FBLN1, FBLN5, SDC1, ADAMTS8 and PXDNL. Verification by independent cohorts showed that breast cancer patients with high BMscore had a distinctly worse outcome. By integrating the BMscore and clinical factors, we constructed a prognostic nomogram that displayed good predictive capability. Furthermore, we evaluated the implication of the BMscore in breast cancer immune infiltration. More importantly, a strongly positive correlation between the BMscore and EMT activity was revealed with immunohistochemistry and in vitro experiments. Taken together, we provided a novel BMscore gene signature for breast cancer patients to predict clinical prognosis and metastasis accurately, which may help with individualized clinical decision-making.

Dissecting the role of cancer-associated fibroblast-derived biglycan as a potential therapeutic target in immunotherapy resistance: A tumor bulk and single-cell transcriptomic study.

INTRODUCTION: Cancer-associated fibroblasts (CAFs) are correlated with the immunotherapy response. However, the culprits that link CAFs to immunotherapy resistance are still rarely investigated in real-world studies. OBJECTIVES: This study aims to systematically assess the landscape of fibroblasts in cancer patients by combining single-cell and bulk profiling data from pan-cancer cohorts. We further sought to decipher the expression, survival predictive value and association with immunotherapy response of biglycan (BGN), a proteoglycan in the extracellular matrix, in multiple cohorts. METHODS: Pan-cancer tumor bulks and 27 single-cell RNA sequencing cohorts were enrolled to investigate the correlations and crosstalk between CAFs and tumor or immune cells. Specific secreting factors of CAFs were then identified by expression profiling at tissue microdissection, isolated primary fibroblasts and single-cell level. The role of BGN was further dissected in additional three bulk and five single-cell profiling datasets from immunotherapy cohorts and validated in real-world patients who have received PD-1 blockade using immunohistochemistry and immunofluorescence. RESULTS: CAFs were closely correlated with immune components. Frequent crosstalk between CAFs and other cells was revealed by the CellChat analysis. Single-cell regulatory network inference and clustering identified common and distinct regulators for CAFs across cancers. The BGN was determined to be a specific secreting factor of CAFs. The BGN served as an unfavourable indicator for overall survival and immunotherapy response. In the real-world immunotherapy cohort, patients with high BGN levels presented a higher proportion of poor response compared with those with low BGN (46.7% vs. 11.8%) and a lower level of infiltrating CD8+ T cells was also observed. CONCLUSIONS: We highlighted the importance of CAFs in the tumor microenvironment and revealed that the BGN, which is mainly derived from CAFs, may be applicable in clinical practice and serve as a therapeutic target in immunotherapy resistance.

The Pan-Cancer Multi-Omics Landscape of FOXO Family Relevant to Clinical Outcome and Drug Resistance.

The forkhead box O (FOXO) transcription factors (TFs) family are frequently mutated, deleted, or amplified in various human cancers, making them attractive candidates for therapy. However, their roles in pan-cancer remain unclear. Here, we evaluated the expression, prognostic value, mutation, methylation, and clinical features of four FOXO family genes (FOXO1, FOXO3, FOXO4, and FOXO6) in 33 types of cancers based on the Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases. We used a single sample gene set enrichment analysis (ssGSEA) algorithm to establish a novel index called "FOXOs score". Moreover, we investigated the association between the FOXOs score and tumor microenvironment (TME), the responses to multiple treatments, along with drug resistance. We found that the FOXO family genes participated in tumor progression and were related to the prognosis in various types of cancer. We calculated the FOXOs score and found that it was significantly correlated with multiple malignant pathways in pan-cancer, including Wnt/beta-catenin signaling, TGF-beta signaling, and hedgehog signaling. In addition, the FOXOs score was also associated with multiple immune-related characteristics. Furthermore, the FOXOs score was sensitive for predicting the efficacy of diverse treatments in multiple cancers, especially immunotherapy. In conclusion, FOXO family genes were vital in pan-cancer and were strongly correlated with the TME. A high FOXOs score indicated an excellent immune-activated TME and sensitivity to multiple treatments. Hence, the FOXOs score might potentially be used as a biomarker in patients with a tumor.

Leveraging diverse cell-death patterns to predict the prognosis and drug sensitivity of triple-negative breast cancer patients after surgery.

BACKGROUND: Postoperative progression and chemotherapy resistance is the major cause of treatment failure in patients with triple-negative breast cancer (TNBC). Currently, there is a lack of an ideal predictive model for the progression and drug sensitivity of postoperative TNBC patients. Diverse programmed cell death (PCD) patterns play an important role in tumor progression, which has the potential to be a prognostic and drug sensitivity indicator for TNBC after surgery. MATERIALS AND METHODS: Twelve PCD patterns (apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis) were analyzed for model construction. Bulk transcriptome, single-cell transcriptome, genomics, and clinical information were collected from TCGA-BRCA, METABRIC, GSE58812, GSE21653, GSE176078, GSE75688, and KM-plotter cohorts to validate the model. RESULTS: The machine learning algorithm established a cell death index (CDI) with a 12-gene signature. Validated in five independent datasets, TNBC patients with high CDI had a worse prognosis after surgery. Two molecular subtypes of TNBC with distinct vital biological processes were identified by an unsupervised clustering model. A nomogram with high predictive performance was constructed by incorporating CDI with clinical features. Furthermore, CDI was associated with immune checkpoint genes and key tumor microenvironment components by integrated analysis of bulk and single-cell transcriptome. TNBC patients with high CDI are resistant to standard adjuvant chemotherapy regimens (docetaxel, oxaliplatin, etc.); however, they might be sensitive to palbociclib (an FDA-approved drug for luminal breast cancer). CONCLUSION: Generally, we established a novel CDI model by comprehensively analyzing diverse cell death patterns, which can accurately predict clinical prognosis and drug sensitivity of TNBC after surgery. A user-friendly website was created to facilitate the application of this prediction model (https://tnbc.shinyapps.io/CDI_Model/).

Turning up a new pattern: Identification of cancer-associated fibroblast-related clusters in TNBC.

Growing evidence indicates a connection between cancer-associated fibroblasts (CAFs) and tumor microenvironment (TME) remodeling and tumor progression. Nevertheless, how patterns of CAFs impact TME and immunotherapy responsiveness in triple-negative breast cancer (TNBC) remains unclear. Here, we systematically investigate the relationship between TNBC progression and patterns of CAFs. By using unsupervised clustering methods in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, we identified two distinct CAF-associated clusters that were related to clinical features, characteristics of TME, and prognosis of patients. Then, we established a CAF-related prognosis index (CPI) by the least absolute shrinkage and selection operator (LASSO)-Cox regression method. CPI showed prognostic accuracy in both training and validation cohorts (METABRIC, GSE96058, and GSE21653). Consequently, we constructed a nomogram with great predictive performance. Moreover, the CPI was verified to be correlated with the responsiveness of immunotherapy in three independent cohorts (GSE91061, GSE165252, and GSE173839). Taken together, the CPI might help us improve our recognition of the TME of TNBC, predict the prognosis of TNBC patients, and offer more immunotherapy strategies in the future.

Integrative mRNA and Long Noncoding RNA Analysis Reveals the Regulatory Network of Floral Bud Induction in Longan (Dimocarpus longan Lour.).

Longan (Dimocarpus longan Lour.) is a tropical/subtropical fruit tree of significant economic importance. Floral induction is an essential process for longan flowering and plays decisive effects on the longan yield. Due to the instability of flowering, it is necessary to understand the molecular mechanisms of floral induction in longan. In this study, mRNA and long noncoding RNA (lncRNA) transcriptome sequencing were performed using the apical buds of fruiting branches as materials. A total of 7,221 differential expressions of mRNAs (DEmRNAs) and 3,238 differential expressions of lncRNAs (DElncRNAs) were identified, respectively. KEGG enrichment analysis of DEmRNAs highlighted the importance of starch and sucrose metabolic, circadian rhythms, and plant hormone signal transduction pathways during floral induction. Combining the analysis of weighted gene co-expression network (WGCNA) and expression pattern of DEmRNAs in the three pathways, specific transcriptional characteristics at each stage during floral induction and regulatory network involving co-expressed genes were investigated. The results showed that sucrose metabolism and auxin signal transduction may be crucial for the growth and maturity of autumn shoots in September and October (B1-B2 stage); starch and sucrose metabolic, circadian rhythms, and plant hormone signal transduction pathways participated in the regulation of floral bud physiological differentiation together in November and December (B3-B4 stage) and the crosstalk among three pathways was also found. Hub genes in the co-expression network and key DEmRNAs in three pathways were identified. The circadian rhythm genes FKF1 and GI were found to activate SOC1gene through the photoperiod core factor COL genes, and they were co-expressed with auxin, gibberellin, abscisic acid, ethylene signaling genes, and sucrose biosynthesis genes at B4 stage. A total of 12 hub-DElncRNAs had potential for positively affecting their distant target genes in three putative key pathways, predominantly in a co-transcriptional manner. A hypothetical model of regulatory pathways and key genes and lncRNAs during floral bud induction in longan was proposed finally. Our studies will provide valuable clues and information to help elucidate the potential molecular mechanisms of floral initiation in longan and woody fruit trees.

Establishment of a Cell Necroptosis Index to Predict Prognosis and Drug Sensitivity for Patients With Triple-Negative Breast Cancer.

Background: Necroptosis has been an alternatively identified mechanism of programmed cancer cell death, which plays a significant role in cancer. However, research about necroptosis-related long noncoding RNAs (lncRNAs) in cancer are still few. Moreover, the potentially prognostic value of necroptosis-related lncRNAs and their correlation with the immune microenvironment remains unclear. The present study aimed to explore the potential prognostic value of necroptosis-related lncRNAs and their relationship to immune microenvironment in triple-negative breast cancer (TNBC). Methods: The RNA expression matrix of patients with TNBC was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Finally, 107 patients of GSE58812, 159 patients of TCGA, and 143 patients of GSE96058 were included. Necroptosis-related lncRNAs were screened by Cox regression and Pearson correlation analysis with necroptosis-related genes. By LASSO regression analysis, nine necroptosis-related lncRNAs were employed, and a cell necroptosis index (CNI) was established; then, we evaluated its prognostic value, clinical significance, pathways, immune infiltration, and chemotherapeutics efficacy. Results: Based on the CNI value, the TNBC patients were divided into high- and low-CNI groups, and the patients with high CNI had worse prognosis, more lymph node metastasis, and larger tumor (p < 0.05). The receiver operating characteristic (ROC) analysis showed that the signature performed well. The result of the infiltration proportion of different immune cell infiltration further explained that TNBC patients with high CNI had low immunogenicity, leading to poor therapeutic outcomes. Moreover, we found significant differences of the IC50 values of various chemotherapeutic drugs in the two CNI groups, which might provide a reference to make a personalized chemotherapy for them. Conclusion: The novel prognostic marker CNI could not only precisely predict the survival probability of patients with TNBC but also demonstrate a potential role in antitumor immunity and drug sensitivity.

N6-methyladenosine regulated FGFR4 attenuates ferroptotic cell death in recalcitrant HER2-positive breast cancer.

Intrinsic and acquired anti-HER2 resistance remains a major hurdle for treating HER2-positive breast cancer. Using genome-wide CRISPR/Cas9 screening in vitro and in vivo, we identify FGFR4 as an essential gene following anti-HER2 treatment. FGFR4 inhibition enhances susceptibility to anti-HER2 therapy in resistant breast cancer. Mechanistically, m6A-hypomethylation regulated FGFR4 phosphorylates GSK-3ß and activates ß-catenin/TCF4 signaling to drive anti-HER2 resistance. Notably, suppression of FGFR4 dramatically diminishes glutathione synthesis and Fe2+ efflux efficiency via the ß-catenin/TCF4-SLC7A11/FPN1 axis, resulting in excessive ROS production and labile iron pool accumulation. Ferroptosis, a unique iron-dependent form of oxidative cell death, is triggered after FGFR4 inhibition. Experiments involving patient-derived xenografts and organoids reveals a synergistic effect of anti-FGFR4 with anti-HER2 therapy in breast cancer with either intrinsic or acquired resistance. Together, these results pinpoint a mechanism of anti-HER2 resistance and provide a strategy for overcoming resistance via FGFR4 inhibition in recalcitrant HER2-positive breast cancer.

Landscape of cancer-associated fibroblasts identifies the secreted biglycan as a protumor and immunosuppressive factor in triple-negative breast cancer.

Cancer-associated fibroblasts (CAFs) are essential for tumor microenvironment remodeling and correlate with tumor progression. However, interactions between CAFs and tumor cells and immune cells in triple-negative breast cancer (TNBC) are still poorly explored. Here, we investigate the role of CAFs in TNBC and potential novel mediators of their functions. The clustering of classic markers was applied to estimate the relative abundance of CAFs in TNBC cohorts. Primary fibroblasts were isolated from normal and tumor samples. The RNA and culture medium of fibroblasts were subjected to RNA sequencing and mass spectrometry to explore the upregulated signatures in CAFs. Microdissection and single-cell RNA sequencing datasets were used to examine the expression profiles. CAFs were associated with hallmark signalings and immune components in TNBC. Clustering based on CAF markers in the literature revealed different CAF infiltration groups in TNBC: low, medium and high. Most of the cancer hallmark signaling pathways were enriched in the high CAF infiltration group. Furthermore, RNA sequencing and mass spectrometry identified biglycan (BGN), a soluble secreted protein, as upregulated in CAFs compared to normal cancer-adjacent fibroblasts (NAFs). The expression of biglycan was negatively correlated with CD8 + T cells. Biglycan indicated poor prognostic outcomes and might be correlated with the immunosuppressive tumor microenvironment (TME). In conclusion, CAFs play an essential role in tumor progression and the TME. We identified an extracellular protein, biglycan, as a prognostic marker and potential therapeutic target in TNBC.