Silencing of PGK1 Promotes Sensitivity to Paclitaxel Treatment by Upregulating XAF1-Mediated Apoptosis in Triple-Negative Breast Cancer

Bibliometric analysis of phosphoglycerate kinase 1 expression in breast cancer and its distinct upregulation in triple-negative breast cancer

BACKGROUND

Phosphoglycerate kinase 1 (PGK1) has been identified as a possible biomarker for breast cancer (BC) and may play a role in the development and advancement of triple-negative BC (TNBC).

AIM

To explore the PGK1 and BC research status and PGK1 expression and mechanism differences among TNBC, non-TNBC, and normal breast tissue.

METHODS

PGK1 and BC related literature was downloaded from Web of Science Core Collection Core Collection. Publication counts, key-word frequency, cooperation networks, and theme trends were analyzed. Normal breast, TNBC, and non-TNBC mRNA data were gathered, and differentially expressed genes obtained. Area under the summary receiver operating characteristic curves, sensitivity and specificity of PGK1 expression were determined. Kaplan Meier revealed PGK1’s prognostic implication. PGK1 co-expressed genes were explored, and Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Disease Ontology applied. Protein-protein interaction networks were constructed. Hub genes identified.

RESULTS

PGK1 and BC related publications have surged since 2020, with China leading the way. The most frequent keyword was “Expression”. Collaborative networks were found among co-citations, countries, institutions, and authors. PGK1 expression and BC progression were research hotspots, and PGK1 expression and BC survival were research frontiers. In 16 TNBC vs non-cancerous breast and 15 TNBC vs non-TNBC datasets, PGK1 mRNA levels were higher in 1159 TNBC than 1205 non-cancerous breast cases [standardized mean differences (SMD): 0.85, 95% confidence interval (95%CI): 0.54-1.16, I² = 86%, P < 0.001]. PGK1 expression was higher in 1520 TNBC than 7072 non-TNBC cases (SMD: 0.25, 95%CI: 0.03-0.47, I² = 91%, P = 0.02). Recurrence free survival was lower in PGK1-high-expression than PGK1-low-expression group (hazard ratio: 1.282, P = 0.023). PGK1 co-expressed genes were concentrated in ATP metabolic process, HIF-1 signaling, and glycolysis/gluconeogenesis pathways.

CONCLUSION

PGK1 expression is a research hotspot and frontier direction in the BC field. PGK1 may play a strong role in promoting cancer in TNBC by mediating metabolism and HIF-1 signaling pathways.

XAF1 overexpression inhibits the malignant progression and cisplatin resistance of NSCLC by activating endoplasmic reticulum stress

BACKGROUND

XIAP-associated factor 1 (XAF1) has been found to participate in the progression of multiple human cancers. Nevertheless, its role as well as the reaction mechanism in non-small cell lung cancer (NSCLC) still remains obscure.

METHODS

In this study, the protein expression of XAF1 in NSCLC cell lines was evaluated using western blot. With the employment of CCK-8 assay, EdU staining, wound healing and transwell, capabilities of NSCLC cells to proliferate, migrate and invade were assessed. Cell apoptotic level and cell cycle were resolved utilizing flow cytometry. Western blot was applied for the estimation of apoptosis- and endoplasmic reticulum (ER) stress-related proteins.

RESULTS

It was discovered that XAF1 expression was conspicuously reduced in NSCLC cell lines. XAF1 overexpression suppressed H1299 cell proliferative, invasive and migrative capabilities, but exhibited promotive effects on cell cycle arrest. Meanwhile, XAF1 overexpression inhibited cisplatin resistance in H1299 and H1299/DDP cells by promoting cell apoptosis and enhanced the expression levels of ER stress-related proteins CHOP, GRP78 and ATF4. What's more, 4-PBA treatment reversed the impacts of XAF1 overexpression on the proliferative, invasive, migrative and apoptotic capabilities of H1299 cells, as well as cell cycle and cisplatin resistance.

CONCLUSION

In conclusion, XAF1 overexpression impeded the advancement of NSCLC and repressed cisplatin resistance of NSCLC cells through inducing ER stress, which indicated that XAF1 might be a novel targeted-therapy for NSCLC.

Extracellular vesicles released by hypoxia-induced tumor-associated fibroblasts impart chemoresistance to breast cancer cells via long noncoding RNA H19 delivery

Recently, extracellular vesicles (EVs) have been emphasized in regulating the hypoxic tumor microenvironment of breast cancer (BC), where tumor-associated fibroblasts (TAFs) play a significant role. In this study, we describe possible molecular mechanisms behind the pro-tumoral effects of EVs, secreted by hypoxia (HP)-induced TAFs, on BC cell growth, metastasis, and chemoresistance. These mechanisms are based on long noncoding RNA H19 (H19) identified by microarray analysis. We employed an in silico approach to identify differentially expressed lncRNAs that were associated with BC. Subsequently, we explored possible downstream regulatory mechanisms. We isolated EVs from TAFs that were exposed to HP, and these EVs were denoted as HP-TAF-EVs henceforth. MTT, transwell, flow cytometry, and TUNEL assays were performed to assess the malignant phenotypes of BC cells. A paclitaxel (TAX)-resistant BC cell line was constructed, and xenograft tumor and lung metastasis models were established in nude mice for in vivo verification. Our observation revealed that lncRNA H19 was significantly overexpressed, whereas miR-497 was notably downregulated in BC. HP induced activation of TAFs and stimulated the secretion of EVs. Coculture of HP-TAF-EVs and BC cells led to an increase in TAX resistance of the latter. HP-TAF-EVs upregulated methylation of miR-497 by delivering lncRNA H19, which recruited DNMT1, thus lowering the expression of miR-497. In addition, lncRNA H19-containing HP-TAF-EVs hindered miR-497 expression, enhancing tumorigenesis and TAX resistance of BC cells in vivo. Our study presents evidence for the contribution of lncRNA H19-containing HP-TAF-EVs in the reduction of miR-497 expression through the recruitment of DNMT1, which in turn promotes the growth, metastasis, and chemoresistance of BC cells.

Oncogenic Alterations of Metabolism Associated with Resistance to Chemotherapy

Metabolic reprogramming in cancer cells is a strategy to meet high proliferation rates, invasion, and metastasis. Also, several researchers indicated that the cellular metabolism changed during the resistance to chemotherapy. Since glycolytic enzymes play a prominent role in these alterations, the ability to reduce resistance to chemotherapy drugs is promising for cancer patients. Oscillating gene expression of these enzymes was involved in the proliferation, invasion, and metastasis of cancer cells. This review discussed the roles of some glycolytic enzymes associated with cancer progression and resistance to chemotherapy in the various cancer types.

Synthetic Reader-Actuators Targeted to Polycomb-Silenced Genes Block Triple-Negative Breast Cancer Proliferation and Invasion

Scientists have used pharmacological inhibitors of polycomb proteins to restore the expression of tumor suppressor genes and stop cancer proliferation and invasion. A major limitation of this approach is that key transcriptional activators, such as TP53 and BAF SWI/SNF, are often mutated in cancer. Poor clinical results for polycomb-targeting therapies in solid cancers, including triple-negative breast cancer (TNBC), could discourage the further development of epigenetic monotherapies. Here, we performed epigenome actuation with a synthetic reader-actuator (SRA) that binds trimethylated histone H3 lysine 27 in polycomb chromatin and modulates core transcriptional activators. In SRA-expressing TNBC BT-549 cells, 122 genes become upregulated ≥2-fold, including the genes involved in cell death, cell cycle arrest, and migration inhibition. The SRA-expressing spheroids showed reduced size in Matrigel and loss of invasion. Therefore, targeting Mediator-recruiting regulators to silenced chromatin can activate tumor suppressors and stimulate anti-cancer phenotypes, and further development of robust gene regulators might benefit TNBC patients.

Development and validation of a combined hypoxia and ferroptosis prognostic signature for breast cancer

Background

Hypoxia is involved in tumor biological processes and disease progression. Ferroptosis, as a newly discovered programmed cell death process, is closely related to breast cancer (BC) occurrence and development. However, reliable prognostic signatures based on a combination of hypoxia and ferroptosis in BC have not been developed.

Method

We set The Cancer Genome Atlas (TCGA) breast cancer cohort as training set and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) BC cohort as the validation set. Least Absolute Shrinkage and Selection Operator (LASSO) and COX regression approaches were used to construct ferroptosis-related genes (FRGs) and hypoxia-related genes (HRGs) prognostic signature (HFRS). The CIBERSORT algorithm and ESTIMATE score were used to explore the relationship between HFRS and tumor immune microenvironment. Immunohistochemical staining was used to detect protein expression in tissue samples. A nomogram was developed to advance the clinical application of HFRS signature.

Results

Ten ferroptosis-related genes and hypoxia-related genes were screened to construct the HFRS prognostic signature in TCGA BC cohort, and the predictive capacity was verified in METABRIC BC cohort. BC patients with high-HFRS had shorter survival time, higher tumor stage, and a higher rate of positive lymph node. Moreover, high HFRS was associated with high hypoxia, ferroptosis, and immunosuppression status. A nomogram that was constructed with age, stage, and HFRS signature showed a strong prognostic capability to predict overall survival (OS) for BC patients.

Conclusion

We developed a novel prognostic model with hypoxia and ferroptosis-related genes to predict OS, and characterize the immune microenvironment of BC patients, which might provide new cures for clinical decision-making and individual treatment of BC patients.

X-Box Binding Protein 1 (XBP1): A Potential Role in Chemotherapy Response, Clinical Pathologic Features, Non-Inflamed Tumour Microenvironment for Breast Cancer

X-box binding protein 1 (XBP1) is mainly expressed in breast cancer (BC) in human cancers. Its tumorigenesis and favourable prognosis are contradictory, and its essential role in chemotherapeutic response and immunosuppression is unknown in BC. The study firstly identified XBP1 who received neoadjuvant chemotherapy (NAC) from GSE25055 and GSE24460. Associations between XBP1 expression and clinicopathological characteristics was investigated using Oncomine, TCGA, UALCAN and bc-GenExMiner. The prognostic value of XBP1 was assessed using the Kaplan–Meier Plotter, bc-GenExMiner, GSE25055, and GSE25056. Furthermore, we systematically correlated XBP1 and immunological characteristics in the BC tumour microenvironment (TME) using TISIDB, TIMER, GSE25055, GSE25056 and TCGA dataset. Finally, an essential role of XBP1 in chemotherapy response was evaluated based on GSE25055, GSE25065, GSE24460, GSE5846, ROC Plotter and CELL databases. Furthermore, XBP1 mRNA expression levels were obviously highest in BC among human cancers and were significantly related to a good prognosis. In addition, XBP1 mRNA and protein levels were higher in the luminal subtype than in normal tissues and basal-like subtype, which might be attributed to membrane transport-related processes. Apart from BC, negative immunological correlations of XBP1 were not observed in other malignancies. XBP1 might shape the non-inflamed TME in BC. Finally, XBP1 expression was higher in chemo-resistive than chemo-sensitive cases, it had a predictive value and could independently predict chemotherapy response in BC patients receiving NAC. Our study suggests that the essential role of XBP1 in clinical pathologic features, non-inflamed TME, chemotherapy response in BC.

Detecting prognostic biomarkers of breast cancer by regularized Cox proportional hazards models

BACKGROUND

The successful identification of breast cancer (BRCA) prognostic biomarkers is essential for the strategic interference of BRCA patients. Recently, various methods have been proposed for exploring a small prognostic gene set that can distinguish the high-risk group from the low-risk group.

METHODS

Regularized Cox proportional hazards (RCPH) models were proposed to discover prognostic biomarkers of BRCA from gene expression data. Firstly, the maximum connected network with 1142 genes by mapping 956 differentially expressed genes (DEGs) and 677 previously BRCA-related genes into the gene regulatory network (GRN) was constructed. Then, the 72 union genes of the four feature gene sets identified by Lasso-RCPH, Enet-RCPH, [Formula: see text]-RCPH and SCAD-RCPH models were recognized as the robust prognostic biomarkers. These biomarkers were validated by literature checks, BRCA-specific GRN and functional enrichment analysis. Finally, an index of prognostic risk score (PRS) for BRCA was established based on univariate and multivariate Cox regression analysis. Survival analysis was performed to investigate the PRS on 1080 BRCA patients from the internal validation. Particularly, the nomogram was constructed to express the relationship between PRS and other clinical information on the discovery dataset. The PRS was also verified on 1848 BRCA patients of ten external validation datasets or collected cohorts.

RESULTS

The nomogram highlighted that the importance of PRS in guiding significance for the prognosis of BRCA patients. In addition, the PRS of 301 normal samples and 306 tumor samples from five independent datasets showed that it is significantly higher in tumors than in normal tissues ([Formula: see text]). The protein expression profiles of the three genes, i.e., ADRB1, SAV1 and TSPAN14, involved in the PRS model demonstrated that the latter two genes are more strongly stained in tumor specimens. More importantly, external validation illustrated that the high-risk group has worse survival than the low-risk group ([Formula: see text]) in both internal and external validations.

CONCLUSIONS

The proposed pipelines of detecting and validating prognostic biomarker genes for BRCA are effective and efficient. Moreover, the proposed PRS is very promising as an important indicator for judging the prognosis of BRCA patients.