Tumor Cell-Autonomous Pro-Metastatic Activities of PD-L1 in Human Breast Cancer Are Mediated by PD-L1-S283 and Chemokine Axes

Multi-objective context-guided consensus of a massive array of techniques for the inference of Gene Regulatory Networks

BACKGROUND AND OBJECTIVE

Gene Regulatory Network (GRN) inference is a fundamental task in biology and medicine, as it enables a deeper understanding of the intricate mechanisms of gene expression present in organisms. This bioinformatics problem has been addressed in the literature through multiple computational approaches. Techniques developed for inferring from expression data have employed Bayesian networks, ordinary differential equations (ODEs), machine learning, information theory measures and neural networks, among others. The diversity of implementations and their respective customization have led to the emergence of many tools and multiple specialized domains derived from them, understood as subsets of networks with specific characteristics that are challenging to detect a priori. This specialization has introduced significant uncertainty when choosing the most appropriate technique for a particular dataset. This proposal, named MO-GENECI, builds upon the basic idea of the previous proposal GENECI and optimizes consensus among different inference techniques, through a carefully refined multi-objective evolutionary algorithm guided by various objective functions, linked to the biological context at hand.

METHODS

MO-GENECI has been tested on an extensive and diverse academic benchmark of 106 gene regulatory networks from multiple sources and sizes. The evaluation of MO-GENECI compared its performance to individual techniques using key metrics (AUROC and AUPR) for gene regulatory network inference. Friedman's statistical ranking provided an ordered classification, followed by non-parametric Holm tests to determine statistical significance.

RESULTS

MO-GENECI's Pareto front approximation facilitates easy selection of an appropriate solution based on generic input data characteristics. The best solution consistently emerged as the winner in all statistical tests, and in many cases, the median precision solution showed no statistically significant difference compared to the winner.

CONCLUSIONS

MO-GENECI has not only demonstrated achieving more accurate results than individual techniques, but has also overcome the uncertainty associated with the initial choice due to its flexibility and adaptability. It is shown intelligently to select the most suitable techniques for each case. The source code is hosted in a public repository at GitHub under MIT license: https://github.com/AdrianSeguraOrtiz/MO-GENECI. Moreover, to facilitate its installation and use, the software associated with this implementation has been encapsulated in a Python package available at PyPI: https://pypi.org/project/geneci/.

Clinical significance of the CXCL8/CXCR1/R2 signalling axis in patients with invasive breast cancer

The C-X-C motif chemokine ligand 8 (CXCL8)-C-X-C chemokine receptor (CXCR)1/2 signalling axis is among numerous mechanisms which stimulate the immune system to defend against tumour growth and influence the tumour microenvironment to promote tumour growth. This pathway plays an important role in the development of a number of cancers including breast cancer (BC). The aim of the present study was to analyse the levels of the chemokine CXCL8 and its receptors, CXCR1 and CXCR2, in the serum of female patients with invasive BC and to assess the expression of these parameters at the mRNA level, considering molecular subtypes and degrees of cancer malignancy. The study group consisted of 62 patients with histopathologically confirmed invasive BC. The control group consisted of 18 patients with histopathologically confirmed fibroadenoma, a benign breast tumour. The levels of CXCL8, CXCR1 and CXCR2 were determined by sandwich ELISA using the CLOUD-CLONE ELISA kit. CXCL8, CXCR1 and CXCR2 transcript levels were analysed using reverse transcription-quantitative PCR. Results showed that serum CXCL8 levels in female patients with invasive BC were significantly higher compared with those in the control group (P<0.05). In addition, significantly elevated CXCR1 levels were observed in luminal B human epidermal growth factor receptor 2+ carcinoma compared with those in the control group. Analysis of CXCL8 in the serum of female patients with BC showed a statistically significant difference between clinical stage G1 and G2 (P<0.05), G2 and G3 (P<0.01), and G1 and G3 (P<0.0001). On the other hand, the analysis of CXCR1 and CXCR2 levels in the serum of the patients revealed a statistically significant difference between G2 and G3 (P<0.05). The current study showed that abnormalities in the immune response involving the CXCL8-CXCR1/2 signalling axis in patients with invasive BC are involved in the development of these tumours. Moreover, the demonstrated severity of changes occurring at protein level may suggest the potential usefulness of their determination as potential diagnostic markers in the clinic.

The Cell-Autonomous Pro-Metastatic Activities of PD-L1 in Breast Cancer Are Regulated by N-Linked Glycosylation-Dependent Activation of STAT3 and STAT1

PD-L1 has been characterized as an inhibitory immune checkpoint, leading to the suppression of potential anti-tumor immune activities in many cancer types. In view of the relatively limited efficacy of immune checkpoint blockades against PD-L1 in breast cancer, our recent study addressed the possibility that in addition to its immune-inhibitory functions, PD-L1 promotes the pro-metastatic potential of the cancer cells themselves. Indeed, our published findings demonstrated that PD-L1 promoted pro-metastatic functions of breast cancer cells in a cell-autonomous manner, both in vitro and in vivo. These functions fully depended on the integrity of the S283 intracellular residue of PD-L1. Here, using siRNAs and the S283A-PD-L1 variant, we demonstrate that the cell-autonomous pro-metastatic functions of PD-L1-tumor cell proliferation and invasion, and release of the pro-metastatic chemokine CXCL8-required the activation of STAT3 and STAT1 in luminal A and triple-negative breast cancer cells. The cell-autonomous pro-metastatic functions of PD-L1 were potently impaired upon inhibition of N-linked glycosylation (kifunensine). Site-specific mutants at each of the N-linked glycosylation sites of PD-L1 (N35, N192, N200, and N219) revealed that they were all required for PD-L1-induced pro-metastatic functions to occur; the N219 site was the main regulator of STAT3 and STAT1 activation, with accompanying roles for N192 and N200 (depending on the cell type). Using a T cell-independent mouse system, we found that cells expressing N35A-PD-L1 and N219A-PD-L1 had a significantly lower tumorigenic and metastatic potential than cells expressing WT-PD-L1. TCGA analyses revealed significant associations between reduced survival and high levels of α-mannosidase II (inferring on N-linked glycosylation) in breast cancer patients. These findings suggest that N-linked glycosylation of PD-L1 may be used to screen for patients who are at greater risk of disease progression, and that modalities targeting N-linked glycosylated PD-L1 may lead to the inhibition of its cell-autonomous pro-metastatic functions and to lower tumor progression in breast cancer.

A Tumor Microenvironment-Driven Network Regulated by STAT3 and p65 Negatively Controls the Enrichment of Cancer Stem Cells in Human HR+/HER2- Breast Cancer

Hormone receptor-positive and HER2-negative (HR+/HER2-; luminal A) tumors are prevalent in breast cancer. Our past studies demonstrated that "TME Stimulation" (estrogen + TNFα + EGF, representing three arms of the tumor microenvironment, TME) has enriched metastasis-forming cancer stem cells (CSCs) in HR+/HER2- human breast cancer cells. Here, following information obtained by RNAseq analyses of TME-stimulated CSCs and Non-CSCs, we found that TME Stimulation has induced the activation of S727-STAT3, Y705-STAT3, STAT1 and p65. Upon TME Stimulation, stattic (STAT3 inhibitor) usage demonstrated that Y705-STAT3 activation negatively controlled CSC enrichment and epithelial-to-mesenchymal transition (EMT) traits, while inducing CXCL8 (IL-8) and PD-L1 expression. However, STAT3 knock-down (siSTAT3) had no effect on these functions; in terms of CSC enrichment, p65 had down-regulatory roles that compensated for the loss of an entire STAT3 protein. Y705-STAT3 and p65 acted additively in reducing CSC enrichment, and Y705A-STAT3 variant + sip65 has enriched chemo-resistant CSCs. Clinical data analyses revealed an inverse correlation between Y705-STAT3 + p65 phosphorylation and CSC signature in luminal A patients, and connection to improved disease course. Overall, we find regulatory roles for Y705-STAT3 and p65 in TME-stimulated HR+/HER2- tumors, with the ability to limit CSC enrichment. These findings raise concerns about using inhibitors of STAT3 and p65 as therapeutic strategies in the clinic.

PD-1/PD-L1 blockade inhibits epithelial-mesenchymal transition and improves chemotherapeutic response in breast cancer

Therapies targeting the PD-1/PD-L1 axis have recently been implemented for triple negative breast cancer (TNBC) management with limited efficacy, indicating that this axis may promote tumor growth by means other than immune suppression. Because PD-L1 overexpression causes resistance to the chemotherapeutic response in many cancers, here we explored the tumor promoting role of the PD-1/PD-L1 axis in breast cancer. We observed that the downregulation of PD-L1 by specific siRNA and pharmacological inhibitor significantly suppressed tumor cell proliferation, invasion and migration thereby enhancing T cell-mediated cell killing in vitro. We also showed that inhibiting PD-L1 improves cytotoxic sensitivity to chemotherapy in TNBC cells. Our in vivo results confirmed that combining a PD-L1 inhibitor with chemotherapy could significantly reduce tumor progression by inhibiting epithelial-mesenchymal transition. Overall, our results proved that PD-L1 contributes to the transformation and progression of breast cancer cells and that its intervention is a promising therapeutic strategy against breast cancer.

CT-based machine learning radiomics predicts CCR5 expression level and survival in ovarian cancer

OBJECTIVE

We aimed to evaluate the prognostic value of C-C motif chemokine receptor type 5 (CCR5) expression level for patients with ovarian cancer and to establish a radiomics model that can predict CCR5 expression level using The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) database.

METHODS

A total of 343 cases of ovarian cancer from the TCGA were used for the gene-based prognostic analysis. Fifty seven cases had preoperative computed tomography (CT) images stored in TCIA with genomic data in TCGA were used for radiomics feature extraction and model construction. 89 cases with both TCGA and TCIA clinical data were used for radiomics model evaluation. After feature extraction, a radiomics signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. A prognostic scoring system incorporating radiomics signature based on CCR5 expression level and clinicopathologic risk factors was proposed for survival prediction.

RESULTS

CCR5 was identified as a differentially expressed prognosis-related gene in tumor and normal sample, which were involved in the regulation of immune response and tumor invasion and metastasis. Four optimal radiomics features were selected to predict overall survival. The performance of the radiomics model for predicting the CCR5 expression level with 10-fold cross- validation achieved Area Under Curve (AUCs) of 0.770 and of 0.726, respectively, in the training and validation sets. A predictive nomogram was generated based on the total risk score of each patient, the AUCs of the time-dependent receiver operating characteristic (ROC) curve of the model was 0.8, 0.673 and 0.792 for 1-year, 3-year and 5-year, respectively. Along with clinical features, important imaging biomarkers could improve the overall survival accuracy of the prediction model.

CONCLUSION

The expression levels of CCR5 can affect the prognosis of patients with ovarian cancer. CT-based radiomics could serve as a new tool for prognosis prediction.

Emerging Roles of Chemokines in Cancer Immunotherapy

This series of 15 articles (4 original articles and 11 reviews) is presented by international leaders in chemokine research [...]

Inflammation-Driven Regulation of PD-L1 and PD-L2, and Their Cross-Interactions with Protective Soluble TNFα Receptors in Human Triple-Negative Breast Cancer

Simple Summary

Immune checkpoint blockades (ICBs) to PD-L1 have led to major breakthroughs in cancer therapy, but in triple-negative breast cancer (TNBC) success rates are rather limited. Following studies suggesting that chronic inflammation may limit ICB efficacy, we found that pro-inflammatory cytokines up-regulated the proportion of TNBC cells co-expressing the inhibitory immune checkpoint PD-L1 and its cognate PD-L2 molecule. Moreover, we demonstrated that in the context of inflammation-driven signals, PD-L1 down-regulated the cell-derived levels of sTNFR1 and sTNFR2, the soluble receptors of tumor necrosis factor α (TNFα); these soluble receptors were found to exert protective/anti-metastatic effects in TNBC cells, manifested by their ability to down-regulate TNFα-induced production of pro-metastatic chemokines by TNBC cells. Our findings possibly testify for a novel mechanism of PD-L1-mediated tumor progression in which PD-L1 prevents the anti-metastatic effects of sTNFR1 and sTNFR2 in TNBC cells. This mechanism may also act in vivo, in parallel to immune suppression under inflammatory conditions.

Abstract

Pro-inflammatory cytokines play key roles in elevating cancer progression in triple-negative breast cancer (TNBC). We demonstrate that specific combinations between TNFα, IL-1β and IFNγ up-regulated the proportion of human TNBC cells co-expressing the inhibitory immune checkpoints PD-L1 and PD-L2: TNFα + IL-1β in MDA-MB-231 cells and IFNγ + IL-1β in BT-549 cells; in the latter cells, the process depended entirely on STAT1 activation, with no involvement of p65 (CRISPR-Cas9 experiments). Highly significant associations between the pro-inflammatory cytokines and PD-L1/PD-L2 expression were revealed in the TCGA dataset of basal-like breast cancer patients. In parallel, we found that the pro-inflammatory cytokines regulated the expression of the soluble receptors of tumor necrosis factor α (TNFα), namely sTNFR1 and sTNFR2; moreover, we revealed that sTNFR1 and sTNFR2 serve as anti-metastatic and protective factors in TNBC, reducing the TNFα-induced production of inflammatory pro-metastatic chemokines (CXCL8, CXCL1, CCL5) by TNBC cells. Importantly, we found that in the context of inflammatory stimulation and also without exposure to pro-inflammatory cytokines, elevated levels of PD-L1 have down-regulated the production of anti-tumor sTNFR1 and sTNFR2. These findings suggest that in addition to its immune-suppressive activities, PD-L1 may promote disease course in TNBC by inhibiting the protective effects of sTNFR1 and sTNFR2.

Correction: Erlichman et al. Tumor Cell-Autonomous Pro-Metastatic Activities of PD-L1 in Human Breast Cancer Are Mediated by PD-L1-S283 and Chemokine Axes. Cancers 2022, 14, 1042

The authors apologize for several typos/technical inaccuracies in the original article [...].