TGF-β1 Reverses Inhibition of COX-2 With NS398 and Increases Invasion in Prostate Cancer Cells

The PD-L1 metabolic interactome intersects with choline metabolism and inflammation

Background

Harnessing the power of the immune system by using immune checkpoint inhibitors has resulted in some of the most exciting advances in cancer treatment. The full potential of this approach has, however, not been fully realized for treating many cancers such as pancreatic and breast cancer. Cancer metabolism influences many aspects of cancer progression including immune surveillance. An expanded understanding of how cancer metabolism can directly impact immune checkpoints may allow further optimization of immunotherapy. We therefore investigated, for the first time, the relationship between the overexpression of choline kinase-α (Chk-α), an enzyme observed in most cancers, and the expression of the immune checkpoint PD-L1.

Methods

We used small interfering RNA to downregulate Chk-α, PD-L1, or both in two triple-negative human breast cancer cell lines (MDA-MB-231 and SUM-149) and two human pancreatic ductal adenocarcinoma cell lines (Pa09C and Pa20C). The effects of the downregulation were studied at the genomic, proteomic, and metabolomic levels. The findings were compared with the results obtained by the analysis of public data from The Cancer Genome Atlas Program.

Results

We identified an inverse dependence between Chk-α and PD-L1 at the genomic, proteomic, and metabolomic levels. We also found that prostaglandin-endoperoxide synthase 2 (COX-2) and transforming growth factor beta (TGF-β) play an important role in this relationship. We independently confirmed this relationship in human cancers by analyzing data from The Cancer Genome Atlas Program.

Conclusions

Our data identified previously unknown roles of PD-L1 in cancer cell metabolic reprogramming, and revealed the immunosuppressive increased PD-L1 effect of Chk-α downregulation. These data suggest that PD-L1 regulation of metabolism may be mediated through Chk-α, COX-2, and TGF-β. The observations provide new insights that can be applied to the rational design of combinatorial therapies targeting immune checkpoints and cancer metabolism.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-021-00245-w.

Cyclooxygenase-2 inhibitor prevents radiation-enhanced infiltration of F98 glioma cells in brain of Fischer rat

PURPOSE

Radiation induces a neuro-inflammation that is characterized by the expression of genes known to increase the invasion of cancer cells. In Fischer rats, brain irradiation increases the infiltration of cancer cells and reduced the median survival of the animals. In this study, we have determined whether these adverse effects of radiation can be prevented with the cyclooxygenase-2 (COX-2) inhibitor meloxicam.

MATERIALS AND METHODS

Brain of Fischer rats treated or not with meloxicam were irradiated (15 Gy) and then implanted with the F98 glioma cells. The median survival of the animals, the infiltration of F98 cells, and the expression of inflammatory cytokines and pro-migration molecules were measured.

RESULTS

Meloxicam reduced by 75% the production of prostaglandin E2 (bioproduct of COX-2) in irradiated brains validating its anti-inflammatory effect. Median survival was increased to control levels by the treatment of meloxicam following brain irradiation. This protective effect was associated with a reduction of the infiltration of F98 cells in the brain, a complete inhibition of radiation-enhancement of matrix metalloproteinase-2, and a significant reduction of tumor necrosis factor α (TNF-α) and tumor growth factor β1 (TGF-β1) expression. Using invasion chambers, interleukin-1β (IL-1β) stimulated by 5-fold the invasiveness of F98 cells, but this stimulation was completely inhibited by meloxicam. This suggests that a cooperation between IL-1β and COX-2 are involved in radiation-enhancement of F98 cell invasion.

CONCLUSIONS

Our results indicate the importance of reducing the inflammatory response of normal brain tissue following irradiation in an effort to extend median survival in F98 tumor-bearing rats.

Prostate cancer invasion and metastasis: insights from mining genomic data

Prostate cancer (PCa) is the second most commonly diagnosed malignancy in men in the Western world and the second leading cause of cancer-related deaths among men worldwide. Although most cancers have the potential to metastasize under appropriate conditions, PCa favors the skeleton as a primary site of metastasis, suggesting that the bone microenvironment is conducive to its growth. PCa metastasis proceeds through a complex series of molecular events that include angiogenesis at the site of the original tumor, local migration within the primary site, intravasation into the blood stream, survival within the circulation, extravasation of the tumor cells to the target organ and colonization of those cells within the new site. In turn, each one of these steps involves a complicated chain of events that utilize multiple protein-protein interactions, protein signaling cascades and transcriptional changes. Despite the urgent need to improve current biomarkers for diagnosis, prognosis and drug resistance, advances have been slow. Global gene expression methods such as gene microarrays and RNA sequencing enable the study of thousands of genes simultaneously and allow scientists to examine molecular pathways of cancer pathogenesis. In this review, we summarize the current literature that explored high-throughput transcriptome analysis toward the advancement of biomarker discovery for PCa. Novel biomarkers are strongly needed to enable more accurate detection of PCa, improve prediction of tumor aggressiveness and facilitate the discovery of new therapeutic targets for tailored medicine. Promising molecular markers identified from gene expression profiling studies include HPN, CLU1, WT1, WNT5A, AURKA and SPARC.

Analysis of normal-tumour tissue interaction in tumours: prediction of prostate cancer features from the molecular profile of adjacent normal cells

Statistical modelling, in combination with genome-wide expression profiling techniques, has demonstrated that the molecular state of the tumour is sufficient to infer its pathological state. These studies have been extremely important in diagnostics and have contributed to improving our understanding of tumour biology. However, their importance in in-depth understanding of cancer patho-physiology may be limited since they do not explicitly take into consideration the fundamental role of the tissue microenvironment in specifying tumour physiology. Because of the importance of normal cells in shaping the tissue microenvironment we formulate the hypothesis that molecular components of the profile of normal epithelial cells adjacent the tumour are predictive of tumour physiology. We addressed this hypothesis by developing statistical models that link gene expression profiles representing the molecular state of adjacent normal epithelial cells to tumour features in prostate cancer. Furthermore, network analysis showed that predictive genes are linked to the activity of important secreted factors, which have the potential to influence tumor biology, such as IL1, IGF1, PDGF BB, AGT, and TGFβ.