Circulating PD-1 mRNA in Peripheral Blood is a Potential Biomarker for Predicting Survival of Breast Cancer Patients

High CTLA-4 gene expression is an independent good prognosis factor in breast cancer patients, especially in the HER2-enriched subtype

BACKGROUND

Breast cancer (BC) is the most common cancer in women and the leading cause of cancer-related death worldwide. This heterogeneous disease has been historically considered a non-immunogenic type of cancer. However, recent advances in immunotherapy have increased the interest in knowing the role of the immune checkpoints (IC) and other immune regulation pathways in this neoplasia.

METHODS

In this retrospective study, we evaluated the correlation of mRNA expression of CTLA-4, PDCD1 (PD1), CD274 (PD-L1), PDCD1LG2 (PD-L2), CD276 (B7-H3), JAK2, and FOXO1 with clinicopathological factors and BC patient's outcome by real-time quantitative polymerase chain reaction (qPCR).

RESULTS

Our results showed that immunoregulatory gene expression depends on BC immunophenotype being CTLA-4 and PDCD1 (PD1) overexpressed on triple-negative/basal-like (TN/BL) and luminal B/HER2-positive phenotypes, respectively, and CD276 (B7-H3), JAK2 and FOXO1 associated with both luminal A and luminal B/HER2-negative tumors. In addition, we found that these genes can also be related to aggressive and non-aggressive clinicopathological characteristics in BC. Finally, survival analysis showed that CTLA-4 expression levels emerge as a significant independent factor of good prognosis in BC patients, especially in the HER2-enriched subtype.

CONCLUSION

Considering all these data, we can conclude that the expression of immunoregulatory genes depends on tumor phenotype and has potential clinical implications in BC patients.

An Open-Label Study of Subcutaneous CpG Oligodeoxynucleotide (PF03512676) in Combination with Trastuzumab in Patients with Metastatic HER2+ Breast Cancer

OBJECTIVES

CpG ODN is a Toll-like receptor 9 agonist with immunotherapeutic potential for many cancer types, including aggressive breast cancers. There is strong interest in utilizing CpG ODN as an adjuvant to improve clinical efficacy of current treatments and immunogenicity of breast cancers not traditionally responsive to active immunotherapy, such as those that are human epidermal growth factor receptor 2 (HER2)-positive. This study aimed to study the efficacy and safety of combination CpG ODN plus anti-HER2 antibody trastuzumab treatment in patients with advanced/metastatic breast cancer.

METHODS

This single-arm, open-label phase II clinical trial treated patients (n = 6) with advanced/metastatic HER2-positive breast cancer with weekly subcutaneous CpG ODN and trastuzumab. Patients may have received any number of prior therapies to be enrolled (most enrolled at median 1 prior line of chemotherapy). Peripheral blood was collected at baseline and weeks 2, 6, 12, and 18 for immune analyses. Six patients were enrolled and 50% achieved stable disease (SD) response.

RESULTS

Median PFS was 8.3 months. Three of the six patients enrolled opted to stop treatment due to tolerability issues. Multiplex assay for cytokine measurements revealed significantly higher VEGF-D levels at week 2 compared to baseline. Peripheral blood mononuclear cells analyzed by flow cytometry showed a significant increase in monocytic MDSC between weeks 6 and 12. Patients with progressive disease tended to have higher levels of week 6 monocytic MDSC and PD-1+ T cells than patients with SD. NK cell populations did not significantly change throughout treatment.

CONCLUSIONS

CpG ODN and trastuzumab treatment of metastatic HER2 + breast cancer was safe but was not tolerable for all patients. This combination did induce potentially predictive immune profile changes in treated patients with metastatic HER2 + breast cancer, the significance of which needs to be further explored.

FAM83H Expression Is Associated with Tumor-Infiltrating PD1-Positive Lymphocytes and Predicts the Survival of Breast Carcinoma Patients

BACKGROUND

FAM83H has been implicated in cancer progression, and PD1 is an important target for anti-cancer immune checkpoint therapy. Recent studies suggest an association between FAM83H expression and immune infiltration. However, studies on the roles of FAM83H and its relationship with PD1 in breast carcinomas have been limited.

METHODS

Immunohistochemical expression of FAM83H and PD1 and their prognostic significance were evaluated in 198 breast carcinomas.

RESULTS

The expression of FAM83H in cancer cells was significantly associated with the presence of PD1-positive lymphoid cells within breast carcinoma tissue. Individual and co-expression patterns of nuclear FAM83H and PD1 were significantly associated with shorter survival of breast carcinomas in univariate analysis. In multivariate analysis, the expression of nuclear FAM83H (overall survival, p < 0.001; relapse-free survival, p = 0.003), PD1 (overall survival, p < 0.001; relapse-free survival, p = 0.003), and co-expression patterns of nuclear FAM83H and PD1 (overall survival, p < 0.001; relapse-free survival, p < 0.001) were the independent indicators of overall survival and relapse-free survival of breast carcinoma patients.

CONCLUSIONS

This study suggests a close association between FAM83H expression and the infiltration of PD1-positive lymphoid cells in breast carcinomas and their expression as the prognostic indicators for breast carcinoma patients, and further studies are needed to clarify this relationship.

Soluble forms of PD-1/PD-L immune checkpoint receptor and ligand in blood serum of breast cancer patients: association with clinical pathologic factors and molecular type of the tumor

Results of enzyme-linked immunosorbent assay of the soluble forms of PD-1/PD-L immune checkpoint receptor and ligand (sPD-1 and sPD-L1) in pretreatment blood serum of 88 breast cancer patients at various disease stages aged 30-83 years are presented. The control group included 55 practically healthy women aged 19-82 years. Serum sPD-1 and sPD-L1 levels in breast cancer patients highly significantly (p<0.0001) differ from control and these changes are opposite: soluble receptor level is more than 6-fold decreased, while soluble ligand concentration - 5.5 fold increased. Both markers separately, as well as their ratio demonstrate very high sensitivity (94-100%) and specificity (95-100%) in relation to healthy control. No statistically significant associations of sPD-1 and sPD-L1 levels with clinical stage, individual TNM system criteria, tumor histological structure, grade, receptor status, and molecular type were established. In particular, no significant peculiarities of the markers' levels in triple negative breast cancer successfully treated with anti-PD-1/PD-L1 preparations were revealed. Long-term follow-up and dynamic studies of sPD-1 and sPD-L1serum levels in the course of treatment are required for evaluation of their independent from clinical and morphological factors prognostic significance and the possibility of application as low invasive tests for prediction and monitoring of corresponding targeted therapy efficiency.

Predictive Biomarkers of Immune Checkpoint Inhibitor Response in Breast Cancer: Looking beyond Tumoral PD-L1

Immune checkpoint inhibitors utilize the immune system to kill cancer cells and are now widely applied across numerous malignancies. Pembrolizumab has two breast-specific indications in triple-negative disease. Currently, programmed death ligand-1 (PD-L1) expression on tumor and surrounding immune cells is the only validated predictive biomarker for immune checkpoint inhibitors (ICIs) in breast cancer; however, it can be imprecise. Additional biomarkers are needed to identify the patient population who will derive the most benefit from these therapies. The tumor immune microenvironment contains many biomarker candidates. In tumor cells, tumor mutational burden has emerged as a robust biomarker across malignancies in general, with higher burden cancers demonstrating improved response, but will need further refinement for less mutated cancers. Preliminary studies suggest that mutations in breast cancer gene 2 (BRCA-2) are associated with increased immune infiltration and response to ICI therapy. Other genomic alterations are also being investigated as potential predictive biomarkers. In immune cells, increased quantity of tumor-infiltrating lymphocytes and CD8+ cytotoxic T cells have correlated with response to immunotherapy treatment. The role of other immune cell phenotypes is being investigated. Peripherally, many liquid-based biomarker strategies such as PD-L1 expression on circulating tumor cells and peripheral immune cell quantification are being studied; however, these strategies require further standardization and refinement prior to large-scale testing. Ultimately, multiple biomarkers utilized together may be needed to best identify the appropriate patients for these treatments.

Programmed Death-Ligand 1 Expression in Breast Cancer Patients: Clinicopathological Associations from a Single-Institution Study

PURPOSE

Tumor expression of programmed death-ligand 1 (PD-L1) is associated with evasion of immune response in several types of malignancies and such expression may render patients eligible for PD-L1 inhibitors. The use of immune checkpoint blockade therapy has been recently approved for the treatment of breast cancer. However, PD-L1 expression data are lacking among Jordanian breast cancer patients. In this study, the tumor PD-L1 expression was characterized in breast cancer patients to assess their eligibility for immune checkpoint blockade therapy. The study also aimed to explore the association between tumoral PD-L1 expression and the clinicopathologic characteristics and the prognostic factors in patients with breast cancer.

PATIENTS AND METHODS

Tissue samples were available from 153 female patients with primary invasive breast cancer. Immunohistochemistry was performed on paraffin-embedded tumor sections that were stained with a PD-L1 antibody. Expression of tumor PD-L1 was correlated with demographics, clinicopathologic characteristics, and prognosis.

RESULTS

The mean age at diagnosis was 54.2±12.8 years (median 52, interquartile range 45-65). The percentage of PD-L1-positive tumors was 26.1%. PD-L1 expression on tumor cells significantly and positively correlated with tumor size (rho=0.174, p=0.032). PD-L1 positivity was significantly associated with the grade of carcinoma (p=0.001), HER2-positivity (p=0.015), and lymphovascular invasion (p=0.036). PD-L1 intensity was significantly associated with tumor stage (p=0.046). No significant associations were observed for the PD-L1 expression status or intensity with patient menopausal status, hormone receptor expression, and molecular subtypes. PD-L1 expression significantly correlated with a worse prognosis of breast cancer patients at the time of diagnosis (rho=0.230, p=0.005).

CONCLUSION

Tumor PD-L1 expression was associated with advanced clinicopathologic features and worse prognosis in this cohort of Jordanian breast cancer patients. Future studies are needed to better understand the impact of PD-L1 blockade therapy on treatment outcomes in eligible breast cancer patients in Jordan.

The application of immune checkpoint blockade in breast cancer and the emerging role of nanoparticle

Breast cancer is the most common malignancy in the female population with a high mortality rate. Despite the satisfying depth of studies evaluating the contributory role of immune checkpoints in this malignancy, few articles have reviewed the pros and cons of immune checkpoint blockades (ICBs). In the current review, we provide an overview of immune-related inhibitory molecules and also discuss the original data obtained from international research laboratories on the aberrant expression of T and non-T cell-associated immune checkpoints in breast cancer. Then, we especially focus on recent studies that utilized ICBs as the treatment strategy in breast cancer and provide their efficiency reports. As there are always costs and benefits, we discuss the limitations and challenges toward ICB therapy such as adverse events and drug resistance. In the last section, we allocate an overview of the recent data concerning the application of nanoparticle systems for cancer immunotherapy and propose that nano-based ICB approaches may overcome the challenges related to ICB therapy in breast cancer. In conclusion, it seems it is time for nanoscience to more rapidly move forward into clinical trials and illuminates the breast cancer treatment area with its potent features for the target delivery of ICBs.

Construction of a Prognostic Immune-Related LncRNA Risk Model for Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) originates mainly from the mucous epithelium and glandular epithelium of the bronchi. It is the most common pathologic subtype of non-small cell lung cancer (NSCLC). At present, there is still a lack of clear criteria to predict the efficacy of immunotherapy. The 5-year survival rate for LUAD patients remains low.

Methods

All data were downloaded from The Cancer Genome Atlas (TCGA) database. We used Gene Set Enrichment Analysis (GSEA) database to obtain immune-related mRNAs. Immune-related lncRNAs were acquired by using the correlation test of the immune-related genes with R version 3.6.3 (Pearson correlation coefficient cor = 0.5, P < 0.05). The TCGA-LUAD dataset was divided into the testing set and the training set randomly. Based on the training set to perform univariate and multivariate Cox regression analyses, we screened prognostic immune-related lncRNAs and given a risk score to each sample. Samples were divided into the high-risk group and the low-risk group according to the median risk score. By the combination of Kaplan–Meier (KM) survival curve, the receiver operating characteristic (ROC) (AUC) curve, the independent risk factor analysis, and the clinical data of the samples, we assessed the accuracy of the risk model. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the differentially expressed mRNAs between the high-risk group and the low-risk group. The differentially expressed genes related to immune response between two risk groups were analyzed to evaluate the role of the model in predicting the efficacy and effects of immunotherapy. In order to explain the internal mechanism of the risk model in predicting the efficacy of immunotherapy, we analyzed the differentially expressed genes related to epithelial-mesenchymal transition (EMT) between two risk groups. We extracted RNA from normal bronchial epithelial cell and LUAD cells and verified the expression level of lncRNAs in the risk model by a quantitative real-time polymerase chain reaction (qRT-PCR) test. We compared our risk model with other published prognostic signatures with data from an independent cohort. We transfected LUAD cell with siRNA-LINC0253. Western blot analysis was performed to observed change of EMT-related marker in protein level.

Results

Through univariate Cox regression analysis, 24 immune-related lncRNAs were found to be strongly associated with the survival of the TCGA-LUAD dataset. Utilizing multivariate Cox regression analysis, 10 lncRNAs were selected to establish the risk model. The K-M survival curves and the ROC (AUC) curves proved that the risk model has a fine predictive effect. The GO enrichment analysis indicated that the effect of the differentially expressed genes between high-risk and low-risk groups is mainly involved in immune response and intercellular interaction. The KEGG enrichment analysis indicated that the differentially expressed genes between high-risk and low-risk groups are mainly involved in endocytosis and the MAPK signaling pathway. The expression of genes related to the efficacy of immunotherapy was significantly different between the two groups. A qRT-PCR test verified the expression level of lncRNAs in LUAD cells in the risk model. The AUC of ROC of 5 years in the independent validation dataset showed that this model had superior accuracy. Western blot analysis verified the change of EMT-related marker in protein level.

Conclusion

The immune lncRNA risk model established by us could better predict the prognosis of patients with LUAD.