Breast cancer remains the world’s most prevalent cancer, responsible for around 685,000 deaths globally despite international research efforts and advances in clinical management. While estrogen receptor positive (ER+), progesterone receptor positive (PR+), and human epidermal growth factor receptor positive (HER2+) subtypes are easily classified and can be targeted, there remains no direct diagnostic test for triple-negative breast cancer (TNBC), except for the lack of receptors expression. The identification of long non-coding RNAs (lncRNAs) and the roles they play in cancer progression has recently proven to be beneficial. In the current study, we utilize RNA sequencing data to identify lncRNA-based biomarkers associated with TNBC, ER+ subtypes, and normal breast tissue. The Marker Finder algorithm identified the lncRNA transcript panel most associated with each molecular subtype and the receiver operating characteristic (ROC) analysis was used to validate the diagnostic potential (area under the curve (AUC) of ≥8.0 and p value < 0.0001). Focusing on TNBC, findings from the discovery cohort were validated in an additional two cohorts, identifying 13 common lncRNA transcripts enriched in TNBC. Binary regression analysis identified a four lncRNA transcript signature (ENST00000425820.1, ENST00000448208.5, ENST00000521666.1, and ENST00000650510.1) with the highest diagnostic power for TNBC. The ENST00000671612.1 lncRNA transcript correlated with worse refractory free survival (RFS). Our data provides a step towards finding a novel diagnostic lncRNA-based panel for TNBC with potential therapeutic implications.

Breast cancer poses a significant clinical challenge due to its complex molecular landscape, underscoring the need for improved prognostic and therapeutic strategies. In this study, we explored the expression profiles and therapeutic relevance of circular RNAs (circRNAs) in a cohort of 96 breast cancer patients from Qatar representing the MENA region. Our data identified distinct expression patterns in relation to breast cancer subtypes, tumor grade, and age, with fifty circRNAs found to be associated with unfavorable relapse-free survival (RFS). The expression of sixteen of these circRNAs was validated in triple-negative breast cancer (TNBC) model using RNase R resistance assay. Among these, the expression of circ_0001522, circ_0001278, and circ_0001801 was validated using divergent primers, and their backsplice junctions were confirmed using Sanger sequencing. Functionally, siRNA-mediated knockdown of these circRNAs significantly suppressed cell proliferation, colony formation, three-dimensional organoid growth, and cell migration in TNBC models. Mechanistic investigations revealed that circRNA depletion altered a subset of miRNA and mRNA expressions, with key interactions involving miR-4458, miR-145-5p, and miR-760, regulating critical targets such as CCND1, ROBO4, and MMP1. Additionally, circRNA-RBP bioinformatic analysis identified common binding partners, including AGO2, CPSF7, TARDBP, UPF1, and LIN28B, suggesting roles in post-transcriptional regulation. Our data highlight circ_0001522, circ_0001278, and circ_0001801 as promising prognostic and therapeutic circRNA targets for breast cancer, offering new avenues for improving breast cancer prognosis and treatment.

Previous studies have suggested that breast cancer (BC) from the Middle East and North Africa (MENA) is presented at younger age with advanced tumor stage, indicating underlying biological differences. Given the scant transcriptomic data on BC from the MENA region and to better understand the biology of this disease, we performed mRNA and microRNA (miRNA) transcriptomic profiling on a local cohort of BC (n = 96) from Qatar. Our data revealed the differentially expressed genes and miRNAs as function of BC molecular subtypes (HR⁺, HER2⁺, HER2⁺HR⁺, and TNBC), tumor grade (GIII vs GI-II), patients’ age (young (≤40) vs old (>40)), and ethnicity (MENA vs non-MENA). Our profiling data revealed close similarity between TNBC and HER2⁺, while the transcriptome of HER2⁺HR⁺tumor was resemblant of that from HR⁺tumors. Network analysis identified complex miRNA-mRNA regulatory networks in each BC molecular subtype, in highvslow grade tumors, in tumors from young vs old patients, and in tumors from MENA vs non-MENA, thus implicating miRNA-mediated gene regulation as an essential mechanism in shaping the transcriptome of BC. Integration of our transcriptomic data with CRISPR-Cas9 functional screen data and the OncoKB database identified numerous dependencies and therapeutic vulnerabilities in each BC molecular subtype, while CDC123 was functionally validated as potential therapeutic target for TNBC. Cox regression survival analyses identified mRNA and miRNA-based signatures predicative of worse and better relapse free survival (RFS), which were validated in larger BC cohorts. Our data provides comprehensive transcriptomic profiling and unraveled the miRNA-mRNA regulatory networks in BC patients from the region and identified novel actionable gene targets, employing integrated approach. Findings from the current study have potential implications to improve the current standard-of-care for BC from the MENA as well as patients from other ethnicities.

Long noncoding RNAs (lncRNAs) play a critical role in breast cancer pathogenesis, including Triple-Negative Breast Cancer (TNBC) subtype. Identifying the lncRNA expression patterns across different breast cancer subtypes could provide valuable insights into their potential utilization as disease biomarkers and therapeutic targets. In this study, we profiled lncRNA expression in 96 breast cancer cases, revealing significant differences compared to normal breast tissue. Variations across breast cancer subtypes, including Hormone Receptor-positive (HR + ), HER2-positive (HER2 + ), HER2 + HR + , and TNBC, as well as in relation to tumor grade and patients’ age at diagnosis were observed. TNBC and HER2+ subtypes showed distinct clustering, while HER2 + HR+ tumors clustered closer to HR+ tumors based on their lncRNA profiles. Our data identified numerous enriched lncRNAs in TNBC, notably the elevated expression of LINC00960, which was subsequently validated in two additional datasets. Analysis of LINC00960 expression in an independent TNBC cohort (n = 360) revealed elevated expression of LINC00960 to correlate with cell movement, invasion, proliferation, and migration functional categories. Depletion of LINC00960 significantly reduced TNBC cell viability, colony formation, migration, and three-dimensional growth, while increasing cell death. Mechanistically, transcriptomic profiling of LINC00960-depleted cells confirmed its tumor-promoting role, likely through sponging of hsa-miR-34a-5p, hsa-miR-16-5p, and hsa-miR-183-5p, leading to the upregulation of cancer-promoting genes including BMI1, KRAS, and AKT3. Our findings highlight the distinct lncRNA expression patterns in breast cancer subtypes and underscore the crucial role for LINC00960 in promoting TNBC pathogenesis, suggesting its potential utilization as a prognostic marker and therapeutic target.

Triple negative breast cancer (TNBC) represents a diverse group of cancers based on their gene expression profiles. While the current mRNA-based classification of TNBC has contributed to our understanding of the heterogeneity of this disease, whether such heterogeneity can be resolved employing a long noncoding RNA (lncRNA) transcriptome has not been established thus far. Herein, we used iterative clustering and guide-gene selection (ICGS) and uniform manifold approximation and projection (UMAP) dimensionality reduction analysis on a large cohort of TNBC transcriptomic data (TNBC = 360, normal = 88) and classified TNBC into four main clusters: LINC00511-enriched, LINC00393-enriched, FIRRE-enriched, and normal tissue-like. Delving into associated gene expression profiles revealed remarkable differences in canonical, casual, upstream, and functional categories among different lncRNA-derived TNBC clusters, suggesting functional consequences for altered lncRNA expression. Correlation and survival analysis comparing mRNA- and lncRNA-based clustering revealed similarities and differences between the two classification approaches. To provide insight into the potential role of the identified lncRNAs in TNBC biology, CRISPR-Cas9 mediated LINC00511 promoter deletion reduced colony formation and enhanced the sensitivity of TNBC cells to paclitaxel, suggesting a role for LINC00511 in conferring tumorigenicity and resistance to therapy. Our data revealed a novel lncRNA-based classification of TNBC and suggested their potential utilization as disease biomarkers and therapeutic targets.

Breast cancer remains a major global health challenge. Yet, genomic data from Middle Eastern and North African (MENA) populations are limited, restricting insights into disease drivers and therapeutic opportunities in this demographic. To address this gap, we performed whole-exome sequencing (WES) on 52 breast cancer samples, including 51 from the MENA region, to characterize somatic mutations and potential therapeutic targets. Across the cohort, 37,369 somatic variants matched entries in the COSMIC database, and driver prediction tools (BoostDM and OncodriveMUT) identified 2451 predicted driver mutations, including 648 known driver variants in genes such as TP53, PIK3CA, GATA3, PTEN, SF3B1, and KMT2C. In addition, 1803 novel predicted drivers were detected, many affecting DNA repair pathways, including homologous recombination (BRCA2, RAD51C), mismatch repair (MLH1, MSH2), and nucleotide excision repair (ERCC2, ERCC3), as well as regulators such as TP53 and ATM. Mutational signature analysis revealed a predominance of C>T substitutions and subtype-specific patterns, with SBS22 and SBS43 enriched in Luminal A tumors. Therapeutic annotation using OncoKB identified 223 actionable or likely oncogenic variants, highlighting potential targets for precision oncology. This study provides a comprehensive characterization of the breast cancer mutational landscape in MENA patients and offers a valuable resource for advancing genomic and therapeutic research in this demographic.