The expression and clinical significance of secretory leukocyte proteinase inhibitor (SLPI) in mammary carcinoma using bioinformatics analysis

A gene expression-based classifier for HER2-low breast cancer

In clinical trials evaluating antibody-conjugated drugs (ADCs), HER2-low breast cancer is defined through protein immunohistochemistry scoring (IHC) 1+ or 2+ without gene amplification. However, in daily practice, the accuracy of IHC is compromised by inter-observer variability. Herein, we aimed to identify HER2-low breast cancer primary tumors by leveraging gene expression profiling. A discovery approach was applied to gene expression profile of institutional INT1 (n = 125) and INT2 (n = 84) datasets. We identified differentially expressed genes (DEGs) in each specific HER2 IHC category 0, 1+, 2+ and 3+. Principal Component Analysis was used to generate a HER2-low signature whose performance was evaluated in the independent INT3 (n = 95), and in the publicly available TCGA and GSE81538 datasets. The association between the HER2-low signature and HER2 IHC categories was evaluated by Kruskal-Wallis test with post hoc pair-wise comparisons. The HER2-low signature discriminatory capability was assessed by estimating the area under the receiver operating characteristic curve (AUC). Gene Ontology and KEGG analyses were performed to evaluate the HER2-low signature genes functional enrichment. A HER2-low signature was computed based on HER2 IHC category-specific DEGs. The twenty genes included in the signature were significantly enriched with lipid and steroid metabolism pathways, peptidase regulation, and humoral immune response. The HER2-low signature values showed a bell-shaped distribution across IHC categories (low values in 0 and 3+; high values in 1+ and 2+), effectively distinguishing HER2-low from 0 (p < 0.001) to 3+ (p < 0.001). Notably, the signature values were higher in tumors scored with 1+ as compared to 0. The HER2-low signature association with IHC categories and its bell-shaped distribution was confirmed in the independent INT3, TCGA and GSE81538 datasets. In the combined INT1 and INT3 datasets, the HER2-low signature achieved an AUC value of 0.74 (95% confidence interval, CI 0.67-0.81) in distinguishing HER2-low vs. the other categories, outperforming the individual ERBB2 mRNA AUC value of 0.52 (95% CI 0.43-0.60). These results represent a proof-of-concept for an observer-independent gene-expression-based classifier of HER2-low status. The herein identified 20-gene signature shows promise in distinguishing between HER2 0 and HER2-low expressing tumors, including those scored as 1+ at IHC, and in developing a selection approach for ADCs candidates.

The secretory leukocyte protease inhibitor (SLPI) in pathophysiology of non-communicable diseases: Evidence from experimental studies to clinical applications

Non-communicable diseases (NCDs) are a worldwide health issue because of their prevalence, negative impacts on human welfare, and economic costs. Protease enzymes play important roles in viral and NCD diseases. Slowing disease progression by inhibiting proteases using small-molecule inhibitors or endogenous inhibitory peptides appears to be crucial. Secretory leukocyte protease inhibitor (SLPI), an inflammatory serine protease inhibitor, maintains protease/antiprotease balance. SLPI is produced by host defense effector cells during inflammation to prevent proteolytic enzyme-induced tissue damage. The etiology of noncommunicable illnesses is linked to SLPI's immunomodulatory and tissue regeneration roles. Disease phases are associated with SLPI levels and activity changes in regional tissue and circulation. SLPI has been extensively evaluated in inflammation, but rarely in NCDs. Unfortunately, the thorough evaluation of SLPI's pathophysiological functions in NCDs in multiple research models has not been published elsewhere. In this review, data from PubMed from 2014 to 2023 was collected, analysed, and categorized into in vitro, in vivo, and clinical studies. According to the review, serine protease inhibitor (SLPI) activity control is linked to non-communicable diseases (NCDs) and other illnesses. Overexpression of the SLPI gene and protein may be a viable diagnostic and therapeutic target for non-communicable diseases (NCDs). SLPI is also cytoprotective, making it a unique treatment. These findings suggest that future research should focus on these pathways using advanced methods, reliable biomarkers, and therapy approaches to assess susceptibility and illness progression. Implications from this review will help pave the way for a new therapeutic target and diagnosis marker for non-communicable diseases.

Secretory leukocyte protease inhibitor (SLPI) in cancer pathophysiology: Mechanisms of action and clinical implications

Cancer is a multifaceted disorder frequently linked to the dysregulation of several biological processes. The SLPI is a multifunctional protein involved in the modulation of immunological response and the inhibition of protease activities. SLPI acts as an inhibitor of proteases, exerts antibacterial properties, and suppresses the transcription of proinflammatory genes through the nuclear factor-kappa B (NF-κB) pathway. The role of this protein as a regulatory agent has been implicated in various types of cancer. Recent research has revealed that SLPI upregulation in cancer cells enhances the metastatic capacity of epithelial malignancies, indicating the deleterious effects of this protein. Furthermore, SLPI interacts intricately with other cancer-promoting factors, including matrix metalloproteinase-2 (MMP-2), MMP-9, the NF-κB and Akt pathways, and the p53-upregulated modulator of apoptosis (PUMA). This review provides an overview of the role of SLPI in cancer pathophysiology, emphasizing its expression in cancer cells and tissues, its potential as a prognostic biomarker, and its therapeutic promise as a target in cancer treatment. The mechanisms of SLPI action in cancer, including its anti-inflammatory effects, regulation of cell proliferation and angiogenesis, and modulation of the tumor microenvironment, have been investigated. The clinical implications of SLPI in cancer have been discussed, including its potential as a diagnostic and prognostic biomarker, its role in chemoresistance, and its therapeutic potential in several types of cancer, such as hepatocellular carcinoma (HCC), colorectal cancer (CRC), pancreatic cancer, head and neck squamous cell carcinoma (HNSCC), ovarian cancer (OvCa), prostate cancer (PC), gastric cancer (GC), breast cancer, and other cancers. In addition, we emphasized the significance of SLPI in cancer, which offers fresh perspectives on potential targets for cancer therapy.

Overexpression of secretory leukocyte peptidase inhibitor (SLPI) does not modulate experimental osteoarthritis but may be a biomarker for the disease

OBJECTIVE

Osteoarthritic cartilage destruction can be regulated by the balance between proteases and anti-proteases. Here, we sought to identify novel cellular protease inhibitors associated with osteoarthritis (OA) pathogenesis.

METHODS

Candidate molecules were screened from microarray data of chondrocytes treated with OA-associated catabolic factors. The functions of candidate molecules in OA pathogenesis were examined in primary-culture mouse articular chondrocytes and mouse models of OA, such as those stimulated by destabilization of the medial meniscus (DMM) or intra-articular (IA) injection of adenovirus expressing the candidate gene. The value of the selected candidate molecule as a biomarker of OA was examined by measuring its circulating levels in human and mouse blood.

RESULTS

Bioinformatic analysis identified secretory leukocyte peptidase inhibitor (SLPI) as a highly upregulated cellular protease inhibitor in chondrocytes treated with pathogenic catabolic factors, including interleukin (IL)-1β, hypoxia-inducible factor (HIF)-2α, and zinc importer ZIP8. The adenovirus-mediated overexpression of SLPI in joint tissues did not cause any OA-like change or modulate DMM- or HIF-2α-induced experimental OA in mice. SLPI also did not markedly modulate the expression of OA-associated catabolic or anabolic factors in chondrocytes. However, SLPI was specifically upregulated in OA cartilage, and the serum SLPI levels were significantly elevated in human OA patients and experimental OA mice, suggesting that SLPI may be a biomarker of OA.

CONCLUSION

Although SLPI is upregulated in OA chondrocytes, it does not appear to per se modulate OA development in mice. However, it may be a potential biomarker of OA in humans and animal models.

Exploration of the Immune-Related Signatures and Immune Infiltration Analysis in Melanoma

In the present study, we aimed to investigate immune-related signatures and immune infiltration in melanoma. The transcriptome profiling and clinical data of melanoma were downloaded from The Cancer Genome Atlas database, and their matched normal samples were obtained from the Genotype-Tissue Expression database. After merging the genome expression data using Perl, the limma package was used for data normalization. We screened the differentially expressed genes (DEGs) and obtained immune signatures associated with melanoma by an immune-related signature list from the InnateDB database. Univariate Cox regression analysis was used to identify potential prognostic immune genes, and LASSO analysis was used to identify the hub genes. Next, based on the results of multivariate Cox regression analysis, we constructed a risk model for melanoma. We investigated the correlation between risk score and clinical characteristics and overall survival (OS) of patients. Based on the TIMER database, the association between selected immune signatures and immune cell distribution was evaluated. Next, the Wilcoxon rank-sum test was performed using CIBERSORT, which confirmed the differential distribution of immune-infiltrating cells between different risk groups. We obtained a list of 91 differentially expressed immune-related signatures. Functional enrichment analysis indicated that these immune-related DEGs participated in several areas of immune-related crosstalk, including cytokine-cytokine receptor interactions, JAK-STAT signaling pathway, chemokine signaling pathway, and Th17 cell differentiation pathway. A risk model was established based on multivariate Cox analysis results, and Kaplan-Meier analysis was performed. The Kruskal-Wallis test suggested that a high risk score indicated a poorer OS and correlated with higher American Joint Committee on Cancer-TNM (AJCC-TNM) stages and advanced pathological stages (P < 0.01). Furthermore, the association between hub immune signatures and immune cell distribution was evaluated in specific tumor samples. The Wilcoxon rank-sum test was used to estimate immune infiltration density in the two groups, and results showed that the high-risk group exhibited a lower infiltration density, and the dominant immune cells included M0 macrophages (P = 0.023) and activated mast cells (P = 0.005).

Effective inhibition of cancer cells by recombinant adenovirus expressing EGFR-targeting artificial microRNA and reversed-caspase-3

The EGFR-targeting cancer therapies are commonly facing drug resistance, mostly due to mutations. Gene therapy with artificial microRNA targeting EGFR conserved sequence may avoid such problem. In this study, we constructed a recombinant adenovirus expressing EGFR-targeting artificial microRNA and active revCASP3 (Ad-EC), under the control of tumor-specific SLPI promoter, and evaluated its inhibitory effect on HEP-2 cancer cells both in vitro and in vivo. MTT assay showed that cell growth inhibition rate at 72h was 44.0% in Ad-EC group at MOI 50, while the rate was 7.7% in the control virus Ad-GFP group and 3.6% in Cetuximab (500 μg/ml) group respectively. Flow cytometry analysis revealed the late apoptotic cells rate was 36.1% in Ad-EC group, significantly higher than 6.5% of Ad-GFP group (p < 0.001). When Ad-EC (MOI 50) was combined with CDDP (0.25 μg/ml), late apoptotic cells rate increased to 61.2%, significantly higher than each monotherapy group (P < 0.001). The real-time xCELLigence system recorded an effective cell growth inhibition in Ad-EC and CDDP groups, and more enhanced effect in Ad-EC plus CDDP group. Western blot revealed that Ad-EC could inhibit the activation of AKT pathway and ERK1/2 pathway, while Cetuximab had the AKT pathway over-activated. In vivo experiments with HEP-2 xenograft in nude mice confirmed the tumor inhibition in Ad-EC, CDDP and Ad-EC plus CDDP groups compared with PBS group (P < 0.01). Collectively, these data support the effective inhibition of cancer cells by this novel gene therapy strategy.