Targeting EMT using low-dose Teniposide by downregulating ZEB2-driven activation of RNA polymerase I in breast cancer.

Metastatic dissemination from the primary tumor is a complex process that requires crosstalk between tumor cells and the surrounding milieu and involves the interplay between numerous cellular-signaling programs. Epithelial-mesenchymal transition (EMT) remains at the forefront of orchestrating a shift in numerous cellular programs, such as stemness, drug resistance, and apoptosis that allow for successful metastasis. Till date, there is limited success in therapeutically targeting EMT. Utilizing a high throughput screen of FDA-approved compounds, we uncovered a novel role of the topoisomerase inhibitor, Teniposide, in reversing EMT. Here, we demonstrate Teniposide as a potent modulator of the EMT program, specifically through an IRF7-NMI mediated response. Furthermore, Teniposide significantly reduces the expression of the key EMT transcriptional regulator, Zinc Finger E-Box Binding Homeobox 2 (ZEB2). ZEB2 downregulation by Teniposide inhibited RNA polymerase I (Pol I) activity and rRNA biogenesis. Importantly, Teniposide treatment markedly reduced pulmonary colonization of breast cancer cells. We have uncovered a novel role of Teniposide, which when used at a very low concentration, mitigates mesenchymal-like invasive phenotype. Overall, its ability to target EMT and rRNA biogenesis makes Teniposide a viable candidate to be repurposed as a therapeutic option to restrict breast cancer metastases.

E3 ubiquitin ligase BCA2 promotes breast cancer stemness by up-regulation of SOX9 by LPS.

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer. Breast cancer stem cells (BCSCs) are believed to play a crucial role in the carcinogenesis, therapy resistance, and metastasis of TNBC. It is well known that inflammation promotes stemness. Several studies have identified breast cancer-associated gene 2 (BCA2) as a potential risk factor for breast cancer incidence and prognosis. However, whether and how BCA2 promotes BCSCs has not been elucidated. Here, we demonstrated that BCA2 specifically promotes lipopolysaccharide (LPS)-induced BCSCs through LPS induced SOX9 expression. BCA2 enhances the interaction between myeloid differentiation primary response protein 88 (MyD88) and Toll-like receptor 4 (TLR4) and inhibits the interaction of MyD88 with deubiquitinase OTUD4 in the LPS-mediated NF-κB signaling pathway. And SOX9, an NF-κB target gene, mediates BCA2's pro-stemness function in TNBC. Our findings provide new insights into the molecular mechanisms by which BCA2 promotes breast cancer and potential therapeutic targets for the treatment of breast cancer.

Identification of molecular subtypes based on chromatin regulator-related genes and experimental verification of the role of ASCL1 in conferring chemotherapy resistance to breast cancer.

Objective: The aim of this study was to identify the molecular subtypes of breast cancer based on chromatin regulator-related genes. Methods: The RNA sequencing data of The Cancer Genome Atlas-Breast Cancer cohort were obtained from the official website, while the single-cell data were downloaded from the Gene Expression Omnibus database (GSE176078). Validation was performed using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Furthermore, the immune characteristics, tumor stemness, heterogeneity, and clinical characteristics of these molecular subtypes were analyzed. The correlation between chromatin regulators and chemotherapy resistance was examined in vitro using the quantitative real-time polymerase chain reaction (qRT-PCR) and Cell Counting Kit-8 (CCK8) assays. Results: This study identified three stable molecular subtypes with different prognostic and pathological features. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses revealed that the differentially expressed genes were associated with disease processes, such as mitotic nuclear division, chromosome segregation, condensed chromosome, and specific chromosome region. The T stage and subtypes were correlated with the clinical features. Tumor heterogeneity (mutant-allele tumor heterogeneity, tumor mutational burden, purity, and homologous recombination deficiency) and tumor stemness (RNA expression-based stemness score, epigenetically regulated RNA expression-based stemness score, DNA methylation-based stemness score, and epigenetically regulated DNA methylation-based stemness score) significantly varied between the three subtypes. Furthermore, Western blotting, qRT-PCR, and CCK8 assays demonstrated that the expression of ASCL1 was positively correlated with chemotherapy resistance in breast cancer. Conclusion: This study identified the subtypes of breast cancer based on chromatin regulators and analyzed their clinical features, gene mutation status, immunophenotype, and drug sensitivity. The results of this study provide effective strategies for assessing clinical prognosis and developing personalized treatment strategies.

Mutation of SIVA, a candidate metastasis gene identified from clonally related bilateral breast cancers, promotes breast cancer cell spread in vitro and in vivo.

Metastasis is the most dreaded outcome after a breast cancer diagnosis, and little is known regarding what triggers or promotes breast cancer to spread distally, or how to prevent or eradicate metastasis effectively. Bilateral breast cancers are an uncommon form of breast cancers. In our study, a percentage of bilateral breast cancers were clonally related based on copy number variation profiling. Whole exome sequencing and comparative sequence analysis revealed that a limited number of somatic mutations were acquired in this "breast-to-breast" metastasis that might promote breast cancer distant spread. One somatic mutation acquired was SIVA-D160N that displayed pro-metastatic phenotypes in vivo and in vitro. Over-expression of SIVA-D160N promoted migration and invasion of human MB-MDA-231 breast cancer cells in vitro, consistent with a dominant negative interfering function. When introduced via tail vein injection, 231 cells over-expressing SIVA-D160N displayed enhanced distant spread on IVIS imaging. Over-expression of SIVA-D160N promoted invasion and anchorage independent growth of mouse 4T1 breast cancer cells in vitro. When introduced orthotopically via mammary fat pad injection in syngeneic Balb/c mice, over-expression of SIVA-D160N in 4T1 cells increased orthotopically implanted mammary gland tumor growth as well as liver metastasis. Clonally related bilateral breast cancers represented a novel system to investigate metastasis and revealed a role of SIVA-D160N in breast cancer metastasis. Further characterization and understanding of SIVA function, and that of its interacting proteins, may elucidate mechanisms of breast cancer metastasis, providing clinically useful biomarkers and therapeutic targets.

A 3'-pre-tRNA-derived small RNA tRF-1-Ser regulated by 25(OH)D promotes proliferation and stemness by inhibiting the function of MBNL1 in breast cancer.

BACKGROUND: We explored the potential novel anticancer mechanisms of 25-hydroxyvitamin D (25(OH)D), a vitamin D metabolite with antitumour effects in breast cancer. It is stable in serum and is used to assess vitamin D levels in clinical practice. Transfer RNA-derived small RNAs are small noncoding RNAs that generate various distinct biological functions, but more research is needed on their role in breast cancer. METHODS: Small RNA microarrays were used to explore the novel regulatory mechanism of 25(OH)D. High-throughput RNA-sequencing technology was used to detect transcriptome changes after 25(OH)D treatment and tRF-1-Ser knockdown. RNA pull-down and high-performance liquid chromatography-mass spectrometry/mass spectrometry were used to explore the proteins bound to tRF-1-Ser. In vitro and in vivo functional experiments were conducted to assess the influence of 25(OH)D and tRF-1-Ser on breast cancer. Semi-quantitative PCR was performed to detect alternative splicing events. Western blot assay and qPCR were used to assess protein and mRNA expression. RESULTS: The expression of tRF-1-Ser is negatively regulated by 25(OH)D. In our breast cancer (BRCA) clinical samples, we found that the expression of tRF-1-Ser was higher in cancer tissues than in paired normal tissues, and was significantly associated with tumour invasion. Moreover, tRF-1-Ser inhibits the function of MBNL1 by hindering its nuclear translocation. Functional experiments and transcriptome data revealed that the downregulation of tRF-1-Ser plays a vital role in the anticancer effect of 25(OH)D. CONCLUSIONS: In brief, our research revealed a novel anticancer mechanism of 25(OH)D, unveiled the vital function of tRF-1-Ser in BRCA progression, and suggested that tRF-1-Ser could emerge as a new therapeutic target for BRCA.

Identification of Breast Cancer Subtypes Based on Endoplasmic Reticulum Stress-Related Genes and Analysis of Prognosis and Immune Microenvironment in Breast Cancer Patients.

Introduction: Endoplasmic reticulum stress (ERS) was a response to the accumulation of unfolded proteins and plays a crucial role in the development of tumors, including processes such as tumor cell invasion, metastasis, and immune evasion. However, the specific regulatory mechanisms of ERS in breast cancer (BC) remain unclear. Methods: In this study, we analyzed RNA sequencing data from The Cancer Genome Atlas (TCGA) for breast cancer and identified 8 core genes associated with ERS: ELOVL2, IFNG, MAP2K6, MZB1, PCSK6, PCSK9, IGF2BP1, and POP1. We evaluated their individual expression, independent diagnostic, and prognostic values in breast cancer patients. A multifactorial Cox analysis established a risk prognostic model, validated with an external dataset. Additionally, we conducted a comprehensive assessment of immune infiltration and drug sensitivity for these genes. Results: The results indicate that these eight core genes play a crucial role in regulating the immune microenvironment of breast cancer (BRCA) patients. Meanwhile, an independent diagnostic model based on the expression of these eight genes shows limited independent diagnostic value, and its independent prognostic value is unsatisfactory, with the time ROC AUC values generally below 0.5. According to the results of logistic regression neural networks and risk prognosis models, when these eight genes interact synergistically, they can serve as excellent biomarkers for the diagnosis and prognosis of breast cancer patients. Furthermore, the research findings have been confirmed through qPCR experiments and validation. Conclusion: In conclusion, we explored the mechanisms of ERS in BRCA patients and identified 8 outstanding biomolecular diagnostic markers and prognostic indicators. The research results were double-validated using the GEO database and qPCR.

Identification of the new molecular subtypes related to inflammation in breast cancer.

Breast cancer is a prevalent ailment among women, and the inflammatory response plays a crucial role in the management and prediction of breast cancer (BRCA). However, the new subtypes based on inflammation in BRCA research are still undefined. The databases including The Cancer Genome Atlas and gene expression omnibus were utilized to gather clinical data and somatic mutation information for approximately 1069 BRCA patients. Through Consensus Clustering, novel subtypes linked to inflammation were identified. A comparative analysis was conducted on the prognosis, and immune cell infiltration, and somatic mutation of the new subtypes. Additionally, an investigation into drug therapy and immunotherapy was conducted to distinguish high-risk individuals from low-risk ones. The findings of this investigation proposed the categorization of BRCA into innovative subtypes predicated on the inflammatory response and 6 key genes were a meaningful approach. Specifically, the low-, medium-, and high-inflammation subtypes exhibited varying degrees of association with clinicopathological features, tumor microenvironment, and prognosis. Notably, the high-inflammation subtype was characterized by a strong correlation with immunosuppressive microenvironments and a higher frequency of somatic mutations, which was an indication of poorer health. This study revealed that a brand-new classification could throw new light on the effective prognosis. The integration of multiple key genes was a new characterization that could promote more immunotherapy strategies and contribute to predicting the efficacy of the chemotherapeutic drugs.

The discerning influence of dynamic contrast-enhanced MRI in anticipating molecular subtypes of breast cancer through the artistry of artificial intelligence - a narrative review.

Radio genomics is an exciting new area that uses diagnostic imaging to discover genetic features of diseases. In this review, we carefully examined existing literature to evaluate the role of artificial intelligence (AI) and machine learning (ML) on dynamic contrastenhanced MRI (DCE-MRI) data to distinguish molecular subtypes of breast cancer (BC). Implications to noninvasive assessment of molecular subtype include reduction in procedure risks, tailored treatment approaches, ability to examine entire lesion, follow-up of tumour biology in response to treatment and evaluation of treatment resistance and failure secondary to tumour heterogeneity. Recent studies leverage radiomics and AI on DCE-MRI data for reliable, non-invasive breast cancer subtype classification. This review recognizes the potential of AI to predict the molecular subtypes of breast cancer non-invasively.

Molecular monitoring by CDKN2A/p16INK4A and RB1 gene methylation in breast cancer.

OBJECTIVE: This prospective study aimed to provide a comprehensive analysis of the methylation status of two pivotal genes, CDKN2A/p16INK4A (cyclin-dependent kinase inhibitor 2A) and RB1 (retinoblastoma transcriptional corepressor 1), in breast cancer patients. METHODS: Samples were obtained from 15 women diagnosed with breast cancer and who underwent a total mastectomy. DNA was extracted from the tumor, non-tumor tissue, and peripheral blood (circulating cell-free DNA). The methylation pattern of cell-free DNA extracted from blood collected on the day of mastectomy was compared with the methylation pattern of cell-free DNA from blood collected 1 year post-surgery. The methylation analysis was carried out by sodium bisulfite conversion and polymerase chain reaction, followed by electrophoresis. RESULTS: Methylation of CDKN2A/p16INK4A was identified in 13 tumor samples and 12 non-tumor tissue samples. Two patients exhibited CDKN2A/p16INK4A methylation in the cell-free DNA of the first blood collection, while another showed methylation only in the cell-free DNA of the subsequent blood collection. Regarding RB1, 11 tumors and 8 non-tumor tissue samples presented methylation of the gene. CONCLUSION: This study presents a novel approach for monitoring breast cancer patients through the analysis of cell-free DNA methylation. This analysis can detect changes in methylation patterns before any visible sign of cancer appears in breast tissue and could help predict the recurrence of malignant breast tumors.

Multiomics-based molecular subtyping based on the commensal microbiome predicts molecular characteristics and the therapeutic response in breast cancer.

The gut microbiota has been demonstrated to be correlated with the clinical phenotypes of diseases, including cancers. However, there are few studies on clinical subtyping based on the gut microbiota, especially in breast cancer (BC) patients. Here, using machine learning methods, we analysed the gut microbiota of BC, colorectal cancer (CRC), and gastric cancer (GC) patients to identify their shared metabolic pathways and the importance of these pathways in cancer development. Based on the gut microbiota-related metabolic pathways, human gene expression profile and patient prognosis, we established a novel BC subtyping system and identified a subtype called "challenging BC". Tumours with this subtype have more genetic mutations and a more complex immune environment than those of other subtypes. A score index was proposed for in-depth analysis and showed a significant negative correlation with patient prognosis. Notably, activation of the TPK1-FOXP3-mediated Hedgehog signalling pathway and TPK1-ITGAE-mediated mTOR signalling pathway was linked to poor prognosis in "challenging BC" patients with high scores, as validated in a patient-derived xenograft (PDX) model. Furthermore, our subtyping system and score index are effective predictors of the response to current neoadjuvant therapy regimens, with the score index significantly negatively correlated with both treatment efficacy and the number of immune cells. Therefore, our findings provide valuable insights into predicting molecular characteristics and treatment responses in "challenging BC" patients.

BMP Stimulation Differentially Affects Phosphorylation and Protein Stability of ß-Catenin in Breast Cancer Cell Lines.

Increased expression and nuclear translocation of ß-CATENIN is frequently observed in breast cancer, and it correlates with poor prognosis. Current treatment strategies targeting ß-CATENIN are not as efficient as desired. Therefore, detailed understanding of ß-CATENIN regulation is crucial. Bone morphogenetic proteins (BMP) and Wingless/Integrated (WNT) pathway crosstalk is well-studied for many cancer types including colorectal cancer, whereas it is still poorly understood for breast cancer. Analysis of breast cancer patient data revealed that BMP2 and BMP6 were significantly downregulated in tumors. Since mutation frequency in genes enhancing ß-CATENIN protein stability is relatively low in breast cancer, we aimed to investigate whether decreased BMP ligand expression could contribute to a high protein level of ß-CATENIN in breast cancer cells. We demonstrated that downstream of BMP stimulation, SMAD4 is required to reduce ß-CATENIN protein stability through the phosphorylation in MCF7 and T47D cells. Consequently, BMP stimulation reduces ß-CATENIN levels and prevents its nuclear translocation and target gene expression in MCF7 cells. Conversely, BMP stimulation has no effect on ß-CATENIN phosphorylation or stability in MDA-MB-231 and MDA-MB-468 cells. Likewise, SMAD4 modulation does not alter the response of those cells, indicating that SMAD4 alone is insufficient for BMP-induced ß-CATENIN phosphorylation. While our data suggest that considering BMP activity may serve as a prognostic marker for understanding ß-CATENIN accumulation risk, further investigation is needed to elucidate the differential responsiveness of breast cancer cell lines.

Grainyhead-like-2, an epithelial master programmer, promotes interferon induction and suppresses breast cancer recurrence.

Type-I and -III interferons play a central role in immune rejection of pathogens and tumors, thus promoting immunogenicity and suppressing tumor recurrence. Double strand RNA is an important ligand that stimulates tumor immunity via interferon responses. Differentiation of embryonic stem cells to pluripotent epithelial cells activates the interferon response during development, raising the question of whether epithelial vs. mesenchymal gene signatures in cancer potentially regulate the interferon pathway as well. Here, using genomics and signaling approaches, we show that Grainyhead-like-2 (GRHL2), a master programmer of epithelial cell identity, promotes type-I and -III interferon responses to double-strand RNA. GRHL2 enhanced the activation of IRF3 and relA/NF-kB and the expression of IRF1; a functional GRHL2 binding site in the IFNL1 promoter was also identified. Moreover, time to recurrence in breast cancer correlated positively with GRHL2 protein expression, indicating that GRHL2 is a tumor recurrence suppressor, consistent with its enhancement of interferon responses. These observations demonstrate that epithelial cell identity supports interferon responses in the context of cancer.

Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection.

BACKGROUND: Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. METHODS: We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. RESULTS: We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA-protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. CONCLUSIONS: This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

CRISPR-Cas13d screens identify KILR, a breast cancer risk-associated lncRNA that regulates DNA replication and repair.

BACKGROUND: Long noncoding RNAs (lncRNAs) have surpassed the number of protein-coding genes, yet the majority have no known function. We previously discovered 844 lncRNAs that were genetically linked to breast cancer through genome-wide association studies (GWAS). Here, we show that a subset of these lncRNAs alter breast cancer risk by modulating cell proliferation, and provide evidence that a reduced expression on one lncRNA increases breast cancer risk through aberrant DNA replication and repair. METHODS: We performed pooled CRISPR-Cas13d-based knockdown screens in breast cells to identify which of the 844 breast cancer-associated lncRNAs alter cell proliferation. We selected one of the lncRNAs that increased cell proliferation, KILR, for follow-up functional studies. KILR pull-down followed by mass spectrometry was used to identify binding proteins. Knockdown and overexpression studies were performed to assess the mechanism by which KILR regulates proliferation. RESULTS: We show that KILR functions as a tumor suppressor, safeguarding breast cells against uncontrolled proliferation. The half-life of KILR is significantly reduced by the risk haplotype, revealing an alternative mechanism by which variants alter cancer risk. Mechanistically, KILR sequesters RPA1, a subunit of the RPA complex required for DNA replication and repair. Reduced KILR expression promotes breast cancer cell proliferation by increasing the available pool of RPA1 and speed of DNA replication. Conversely, KILR overexpression promotes apoptosis in breast cancer cells, but not normal breast cells. CONCLUSIONS: Our results confirm lncRNAs as mediators of breast cancer risk, emphasize the need to annotate noncoding transcripts in relevant cell types when investigating GWAS variants and provide a scalable platform for mapping phenotypes associated with lncRNAs.

Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity.

BACKGROUND: Early prediction of pathological complete response (pCR) is important for deciding appropriate treatment strategies for patients. In this study, we aimed to quantify the dynamic characteristics of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) and investigate its value to improve pCR prediction as well as its association with tumor heterogeneity in breast cancer patients. METHODS: The DCE-MRI, clinicopathologic record, and full transcriptomic data of 785 breast cancer patients receiving neoadjuvant chemotherapy were retrospectively included from a public dataset. Dynamic features of DCE-MRI were computed from extracted phase-varying radiomic feature series using 22 CAnonical Time-sereis CHaracteristics. Dynamic model and radiomic model were developed by logistic regression using dynamic features and traditional radiomic features respectively. Various combined models with clinical factors were also developed to find the optimal combination and the significance of each components was evaluated. All the models were evaluated in independent test set in terms of area under receiver operating characteristic curve (AUC). To explore the potential underlying biological mechanisms, radiogenomic analysis was implemented on patient subgroups stratified by dynamic model to identify differentially expressed genes (DEGs) and enriched pathways. RESULTS: A 10-feature dynamic model and a 4-feature radiomic model were developed (AUC = 0.688, 95%CI: 0.635-0.741 and AUC = 0.650, 95%CI: 0.595-0.705) and tested (AUC = 0.686, 95%CI: 0.594-0.778 and AUC = 0.626, 95%CI: 0.529-0.722), with the dynamic model showing slightly higher AUC (train p = 0.181, test p = 0.222). The combined model of clinical, radiomic, and dynamic achieved the highest AUC in pCR prediction (train: 0.769, 95%CI: 0.722-0.816 and test: 0.762, 95%CI: 0.679-0.845). Compared with clinical-radiomic combined model (train AUC = 0.716, 95%CI: 0.665-0.767 and test AUC = 0.695, 95%CI: 0.656-0.714), adding the dynamic component brought significant improvement in model performance (train p < 0.001 and test p = 0.005). Radiogenomic analysis identified 297 DEGs, including CXCL9, CCL18, and HLA-DPB1 which are known to be associated with breast cancer prognosis or angiogenesis. Gene set enrichment analysis further revealed enrichment of gene ontology terms and pathways related to immune system. CONCLUSION: Dynamic characteristics of DCE-MRI were quantified and used to develop dynamic model for improving pCR prediction in breast cancer patients. The dynamic model was associated with tumor heterogeniety in prognostic-related gene expression and immune-related pathways.

The Human Intermediate Prolactin Receptor I-tail Contributes Breast Oncogenesis by Targeting Ras/MAPK Pathway.

Prolactin and its receptor (PRLr) in humans are significantly involved in breast cancer pathogenesis. The intermediate form of human PRLr (hPRLrI) is produced by alternative splicing and has a novel 13 amino acid tail ("I-tail") gain. hPRLrI induces significant proliferation and anchorage-independent growth of normal mammary epithelia in vitro when coexpressed with the long form hPRLr (hPRLrL). hPRLrL and hPRLrI coexpression is necessary to induce the transformation of mammary epithelia in vivo. The I-tail is associated with the ubiquitin-like protein neural precursor cell expressed developmentally downregulated protein 8. Treatment with the neural precursor cell expressed developmentally downregulated protein 8-activating enzyme inhibitor pevonedistat resulted in increased hPRLrL and the death of breast cancer cells. The goal of this study was to determine the function of the hPRLrI I-tail in hPRLrL/hPRLrI-mediated mammary transformation. hPRLrL/hPRLrI and hPRLrL/hPRLrIΔ13 (I-tail removal mutant) were delivered to MCF10AT cells. Cell proliferation was decreased when hPRLrI I-tail was removed. I-tail deletion decreased anchorage-independent growth and attenuated cell migration. The I-tail was involved in Ras/MAPK signaling but not PI3K/Akt signaling pathway as shown by western blot. I-tail removal resulted in decreased hPRLrI stability. RNA-sequencing data revealed that I-tail removal resulted in differential gene expression induced by prolactin. Ingenuity Pathway Analysis revealed that the activity of ERK was attenuated. Treatment of breast cancer cells with ERK1/2 inhibitor ulixertinib resulted in decreased colony-forming ability and less proliferation. These studies suggest that the hPRLrI I-tail contributed to breast oncogenesis and may be a promising target for the development of new breast cancer therapies.

Additional prognostic value of polymorphisms within the 3'-untranslated region of programmed cell death pathway genes in early-stage breast cancer.

Introduction: The programmed cell death (PCD) pathway plays an important role in restricting cancer cell survival and proliferation. However, limited studies have investigated the association between genetic variants in the 3'-untranslated region of the PCD pathway genes and breast cancer outcomes. Methods: In this study, we genotyped 28 potentially functional single nucleotide polymorphisms (SNPs) in 23 PCD pathway genes in 1,177 patients with early-stage breast cancer (EBC) from a Han Chinese population. The median follow-up period was 174 months. Results: Among all the candidate SNPs, four independent SNPs (rs4900321 and rs7150025 in ATG2B, rs6753785 in BCL2L11, and rs2213181 in c-Kit) were associated with invasive disease-free survival (iDFS), distant disease-free survival (DDFS), breast cancer-specific survival (BCSS) and overall survival (OS), respectively. Further combined genotypes of these four SNPs revealed that the survival decreased as the number of unfavorable genotypes increased (Ptrend = 1.0 × 10-6, 8.5 × 10-8, 3.6 × 10-4, and 1.3 × 10-4 for iDFS, DDFS, BCSS, and OS, respectively). Receiver operating characteristic curve analysis demonstrated that incorporating unfavorable genotypes and clinicopathological variables improved the ability to predict EBC survival (P = 0.006, 0.004, 0.029, and 0.019 for iDFS, DDFS, BCSS, and OS, respectively). Additionally, rs6753785 and rs2213181 were associated with BCL2L11 and c-Kit mRNA expression, respectively. Conclusions: Our results suggest that these four SNPs may act as novel biomarkers for EBC survival, possibly by modulating the expression of the corresponding genes.

Circulating tumor DNA: from discovery to clinical application in breast cancer.

Breast cancer (BC) stands out as the cancer with the highest incidence of morbidity and mortality among women worldwide, and its incidence rate is currently trending upwards. Improving the efficiency of breast cancer diagnosis and treatment is crucial, as it can effectively reduce the disease burden. Circulating tumor DNA (ctDNA) originates from the release of tumor cells and plays a pivotal role in the occurrence, development, and metastasis of breast cancer. In recent years, the widespread application of high-throughput analytical technology has made ctDNA a promising biomarker for early cancer detection, monitoring minimal residual disease, early recurrence monitoring, and predicting treatment outcomes. ctDNA-based approaches can effectively compensate for the shortcomings of traditional screening and monitoring methods, which fail to provide real-time information and prospective guidance for breast cancer diagnosis and treatment. This review summarizes the applications of ctDNA in various aspects of breast cancer, including screening, diagnosis, prognosis, treatment, and follow-up. It highlights the current research status in this field and emphasizes the potential for future large-scale clinical applications of ctDNA-based approaches.

RPGRIP1L as a new biomarker for prognosis and tumor immune of breast cancer.

The Retinitis pigmentosa GTPase regulator interacting protein 1-like (RPGRIP1L) gene encodes an important protein that performs various physiological functions. Variants of RPGRIP1L are related to a number of diseases. However, it is currently unknown whether RPGRIP1L is correlated with breast invasive carcinoma (BRCA). In BRCA tissue specimens, the expression of RPGRIP1L was found to be elevated in comparison to its levels in normal breast tissue. A notable decline in survival rates was associated with patients exhibiting heightened RPGRIP1L gene expression. Consistent with these findings, our data also show the above results. Furthermore, elevated expression of RPGRIP1L corresponded with a spectrum of unfavorable clinicopathological features, including the presence of human epidermal growth factor receptor 2 (HER2) positive, estrogen receptor (ER) positive, over 60 years old, T2, N0, and N3. At the same time, our research indicated that 50 genes and 15 proteins were positively related to RPGRIP1L, and that these proteins and genes were mostly involved in T cell proliferation, immune response, cytokine activity, and metabolic regulation. In addition, in the present study, there was a significant correlation between RPGRIP1L expression and immune cell infiltration. Finally, we found that four Chemicals could downregulate the expression of RPGRIP1L. Altogether, our results strongly indicated that RPGRIP1L might serve as a new prognostic biomarker for BRCA.

Exploration of poly (ADP-ribose) polymerase inhibitor resistance in the treatment of BRCA1/2-mutated cancer.

Breast cancer susceptibility 1/2 (BRCA1/2) genes play a crucial role in DNA damage repair, yet mutations in these genes increase the susceptibility to tumorigenesis. Exploiting the synthetic lethality mechanism between BRCA1/2 mutations and poly(ADP-ribose) polymerase (PARP) inhibition has led to the development and clinical approval of PARP inhibitor (PARPi), representing a milestone in targeted therapy for BRCA1/2 mutant tumors. This approach has paved the way for leveraging synthetic lethality in tumor treatment strategies. Despite the initial success of PARPis, resistance to these agents diminishes their efficacy in BRCA1/2-mutant tumors. Investigations into PARPi resistance have identified replication fork stability and homologous recombination repair as key factors sensitive to PARPis. Additionally, studies suggest that replication gaps may also confer sensitivity to PARPis. Moreover, emerging evidence indicates a correlation between PARPi resistance and cisplatin resistance, suggesting a potential overlap in the mechanisms underlying resistance to both agents. Given these findings, it is imperative to explore the interplay between replication gaps and PARPi resistance, particularly in the context of platinum resistance. Understanding the impact of replication gaps on PARPi resistance may offer insights into novel therapeutic strategies to overcome resistance mechanisms and enhance the efficacy of targeted therapies in BRCA1/2-mutant tumors.