Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer

Characteristics of sphingomyelin metabolism in the MCF7 and BT474 radiotherapy‑resistant HER2‑positive breast cancer cell lines

Breast cancer is the most common cancer globally in terms of incidence. This cancer is classified into subtypes based on histological or immunological characteristics. HER2-positive cases account for 15-25% of breast cancer cases, and one of the first events in breast carcinogenesis is HER2 upregulation. Furthermore, HER2 expression increases the detection rate of metastatic or recurrent breast cancers by 50-80%. The epidermal growth factor receptor family includes HER2, which is a transmembrane receptor protein. In our previous case report, patients who were resistant to anti-HER2 monoclonal antibody therapy, chemotherapy and radiotherapy had higher concentrations of phospholipid metabolites such as phosphatidylcholine and sphingomyelin (SM), which was associated with cancer recurrence progression. To better understand the relationship between radiotherapy resistance and SM expression, breast cancer cell lines with and without HER2 expression (MCF7 and BT474) after exposure to ionizing radiation (IR) were examined. In the cell culture supernatant, similar levels of SM in MCF7 cells were identified after 1-4 Gy exposure. However, SM levels in BT474 cells were upregulated compared with those of in the control group. Intracellular SM levels were upregulated in BT474 cells exposed to 1 and 4 Gy compared with the non-irradiated control group. Furthermore, significantly increased mRNA expression levels of sphingomyelin synthase 2 (SGMS2) in BT474 cells exposed to IR were observed compared with those in nonirradiated cells; however, the SGMS2 levels in MCF7 cells did not differ significantly among the 0, 2 and 4 Gy groups. These findings suggested that a higher dose of IR induced the secretion of SM and its associated gene expression in HER2-positive breast cancer cells.

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics

Breast cancer (BC) is a complex and multifactorial disease, driven by genetic alterations that promote tumor growth and progression. However, recent research has highlighted the importance of non-genetic factors in shaping cancer evolution and influencing therapeutic outcomes. Non-genetic heterogeneity refers to diverse subpopulations of cancer cells within breast tumors, exhibiting distinct phenotypic and functional properties. These subpopulations can arise through various mechanisms, including clonal evolution, genetic changes, epigenetic changes, and reversible phenotypic transitions. Although genetic and epigenetic changes are important points of the pathology of breast cancer yet, the immune system also plays a crucial role in its progression. In clinical management, histologic and molecular classification of BC are used. Immunological subtyping of BC has gained attention in recent years as compared to traditional techniques. Intratumoral heterogeneity revealed by immunological microenvironment (IME) has opened novel opportunities for immunotherapy research. This systematic review is focused on non-genetic variability to identify and interlink immunological subgroups in breast cancer. This review provides a deep understanding of adaptive methods adopted by tumor cells to withstand changes in the tumor microenvironment and selective pressure imposed by medications. These adaptive methods include alterations in drug targets, immune system evasion, activation of survival pathways, and alterations in metabolism. Understanding non-genetic heterogeneity is essential for the development of targeted therapies.

Long noncoding RNA profiling unveils LINC00960 as unfavorable prognostic biomarker promoting triple negative breast cancer progression

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.

Identifying miRNA Signatures Associated with Pancreatic Islet Dysfunction in a FOXA2-Deficient iPSC Model

The pathogenesis of diabetes involves complex changes in the expression profiles of mRNA and non-coding RNAs within pancreatic islet cells. Recent progress in induced pluripotent stem cell (iPSC) technology have allowed the modeling of diabetes-associated genes. Our recent study using FOXA2-deficient human iPSC models has highlighted an essential role for FOXA2 in the development of human pancreas. Here, we aimed to provide further insights on the role of microRNAs (miRNAs) by studying the miRNA-mRNA regulatory networks in iPSC-derived islets lacking the FOXA2 gene. Consistent with our previous findings, the absence of FOXA2 significantly downregulated the expression of islet hormones, INS, and GCG, alongside other key developmental genes in pancreatic islets. Concordantly, RNA-Seq analysis showed significant downregulation of genes related to pancreatic development and upregulation of genes associated with nervous system development and lipid metabolic pathways. Furthermore, the absence of FOXA2 in iPSC-derived pancreatic islets resulted in significant alterations in miRNA expression, with 61 miRNAs upregulated and 99 downregulated. The upregulated miRNAs targeted crucial genes involved in diabetes and pancreatic islet cell development. In contrary, the absence of FOXA2 in islets showed a network of downregulated miRNAs targeting genes related to nervous system development and lipid metabolism. These findings highlight the impact of FOXA2 absence on pancreatic islet development and suggesting intricate miRNA-mRNA regulatory networks affecting pancreatic islet cell development.

Multifaced roles of the long non-coding RNA DRAIC in cancer progression

Long non-coding RNAs (lncRNA) are functional RNAs, with over 200 nucleotides in length and lacking protein-coding potential. Studies have indicated that lncRNAs are important gene regulators under physiological conditions. Aberrant lncRNA expression is associated with the initiation and progression of various diseases, including cancers. High-throughput transcriptome analyses have revealed thousands of lncRNAs as putative tumor suppressors or promoters in various cancers, but the detailed molecular mechanisms of each lncRNA remain unclear. Downregulated RNA In Cancer, inhibitor of cell invasion and migration (DRAIC) (also known as LOC145837 and RP11-279F6.1) is a lncRNA that inhibits or promotes cancer progression with several modes of action. DRAIC was originally identified as a tumor-suppressive lncRNA in prostate adenocarcinoma. Subsequent studies also revealed that it has an anti-tumor role in glioblastoma, triple-negative breast cancer, and stomach adenocarcinoma. However, DRAIC exhibits oncogenic functions in other malignancies, such as lung adenocarcinoma and esophageal carcinoma, indicating its highly context-dependent effects on cancer progression and clinical outcomes. DRAIC and its associated pathways regulate various biological processes, including proliferation, invasion, metastasis, autophagy, and neuroendocrine function. This review introduces the multifaceted roles of DRAIC, particularly in cancer progression, and discusses its biological significance and clinical implications.

Identification of Interpretable Clusters and Associated Signatures in Breast Cancer Single-Cell Data: A Topic Modeling Approach

Topic modeling is a popular technique in machine learning and natural language processing, where a corpus of text documents is classified into themes or topics using word frequency analysis. This approach has proven successful in various biological data analysis applications, such as predicting cancer subtypes with high accuracy and identifying genes, enhancers, and stable cell types simultaneously from sparse single-cell epigenomics data. The advantage of using a topic model is that it not only serves as a clustering algorithm, but it can also explain clustering results by providing word probability distributions over topics. Our study proposes a novel topic modeling approach for clustering single cells and detecting topics (gene signatures) in single-cell datasets that measure multiple omics simultaneously. We applied this approach to examine the transcriptional heterogeneity of luminal and triple-negative breast cancer cells using patient-derived xenograft models with acquired resistance to chemotherapy and targeted therapy. Through this approach, we identified protein-coding genes and long non-coding RNAs (lncRNAs) that group thousands of cells into biologically similar clusters, accurately distinguishing drug-sensitive and -resistant breast cancer types. In comparison to standard state-of-the-art clustering analyses, our approach offers an optimal partitioning of genes into topics and cells into clusters simultaneously, producing easily interpretable clustering outcomes. Additionally, we demonstrate that an integrative clustering approach, which combines the information from mRNAs and lncRNAs treated as disjoint omics layers, enhances the accuracy of cell classification.

Locally Advanced Adenoid Cystic Carcinoma of the Breast-A Case Report with a Review of the Literature

Breast cancer (BC) is a heterogeneous disease distinguished by four main subtypes based on the expression of estrogen, progesterone receptors, and human epidermal growth factor-2 on the cancer cells. Triple-negative breast cancer (TNBC) consists of approximately 10-20% of all BCs and is characterized by a poor prognosis. Adenoid cystic carcinoma (ACC) of the breast is a rare, special type of TNBC with low metastatic potential and usually favorable prognosis. There are no established recommendations concerning systemic therapy in advanced ACC. We present a case of a 70-year-old woman with locally advanced ACC with progression after radical mastectomy, and review the literature concerning the treatment of metastatic disease focused on systemic therapy.

Unveiling the Immune Microenvironment's Role in Breast Cancer: A Glimpse into Promising Frontiers

Breast cancer (BC), one of the most widespread and devastating diseases affecting women worldwide, presents a significant public health challenge. This review explores the emerging frontiers of research focused on deciphering the intricate interplay between BC cells and the immune microenvironment. Understanding the role of the immune system in BC is critical as it holds promise for novel therapeutic approaches and precision medicine strategies. This review delves into the current literature regarding the immune microenvironment's contribution to BC initiation, progression, and metastasis. It examines the complex mechanisms by which BC cells interact with various immune cell populations, including tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs). Furthermore, this review highlights the impact of immune-related factors, such as cytokines and immune checkpoint molecules. Additionally, this comprehensive analysis sheds light on the potential biomarkers associated with the immune response in BC, enabling early diagnosis and prognostic assessment. The therapeutic implications of targeting the immune microenvironment are also explored, encompassing immunotherapeutic strategies and combination therapies to enhance treatment efficacy. The significance of this review lies in its potential to pave the way for novel therapeutic interventions, providing clinicians and researchers with essential knowledge to design targeted and personalized treatment regimens for BC patients.

A Review of the Advancements in Targeted Therapies for Breast Cancer

Breast cancer, the second-most common and lethal disease in women, poses a severe danger to global health. Breast cancer rates continue to climb despite advances in medical technology. Predictions indicate that by 2040, there will be more than three million new cases yearly. Targeted medicines have experienced a profound transformation in treating breast cancer, allowing for individualized strategies that lessen side effects and improve patient outcomes. This thorough analysis gives a rigorous investigation of current developments in breast cancer-targeted treatments. It carefully examines several subtypes, including hormone receptor-positive (HR+), HER2-positive (HER2+), and triple-negative breast cancer (TNBC), recognizing the illness' fundamental variety. It offers specialized treatment plans catered to each subtype's particular traits. The review also examines how precise genetic abnormalities like BRCA1/2 and PIK3CA mutations and molecular profiling facilitate therapy selection. Monoclonal antibodies and small molecule inhibitors are some of the targeted medicines examined in the study. It explains how each of these treatments works and supports its findings with data from clinical trials. It also considers potential new medications and addresses persistent problems, such as resistance mechanisms, chances for combining therapies, and cutting-edge patient classification techniques. This study seeks to give healthcare professionals, researchers, and patients a thorough overview of the recent advancements in breast cancer-targeted therapy by drawing on the opinions of top authorities in the area. The coordinated effort aims to create customized, efficient therapies, eventually bolstering the battle against this powerful illness.

Tumor Infiltrating Lymphocytes (TILS) and PD-L1 Expression in Breast Cancer: A Review of Current Evidence and Prognostic Implications from Pathologist's Perspective

With the rise of novel immunotherapies able to stimulate the antitumor immune response, increasing literature concerning the immunogenicity of breast cancer has been published in recent years. Numerous clinical studies have been conducted in order to identify novel biomarkers that could reflect the immunogenicity of BC and predict response to immunotherapy. In this regard, TILs have emerged as an important immunological biomarker related to the antitumor immune response in BC. TILs are more frequently observed in triple-negative breast cancer and HER2+ subtypes, where increased TIL levels have been linked to a better response to neoadjuvant chemotherapy and improved survival. PD-L1 is a type 1 transmembrane protein ligand expressed on T lymphocytes, B lymphocytes, and antigen-presenting cells and is considered a key inhibitory checkpoint involved in cancer immune regulation. PD-L1 immunohistochemical expression in breast cancer is observed in about 10-30% of cases and is extremely variable based on tumor stage and molecular subtypes. Briefly, TNBC shows the highest percentage of PD-L1 positivity, followed by HER2+ tumors. On the other hand, PD-L1 is rarely expressed (0-10% of cases) in hormone-receptor-positive BC. The prognostic role of PD-L1 expression in BC is still controversial since different immunohistochemistry (IHC) clones, cut-off points, and scoring systems have been utilized across published studies. In the present paper, an extensive review of the current knowledge of the immune landscape of BC is provided. TILS and PD-L1 expression across different BC subtypes are discussed, providing a guide for their pathological assessment and reporting.

Long non-coding RNA AC099850.4 correlates with advanced disease state and predicts worse prognosis in triple-negative breast cancer

Our understanding of the function of long non-coding RNAs (lncRNAs) in health and disease states has evolved over the past decades due to the many advances in genome research. In the current study, we characterized the lncRNA transcriptome enriched in triple-negative breast cancer (TNBC, n = 42) and estrogen receptor (ER+, n = 42) breast cancer compared to normal breast tissue (n = 56). Given the aggressive nature of TNBC, our data revealed selective enrichment of 57 lncRNAs in TNBC. Among those, AC099850.4 lncRNA was chosen for further investigation where it exhibited elevated expression, which was further confirmed in a second TNBC cohort (n = 360) where its expression correlated with a worse prognosis. Network analysis of AC099850.4high TNBC highlighted enrichment in functional categories indicative of cell cycle activation and mitosis. Ingenuity pathway analysis on the differentially expressed genes in AC099850.4high TNBC revealed the activation of the canonical kinetochore metaphase signaling pathway, pyridoxal 5'-phosphate salvage pathway, and salvage pathways of pyrimidine ribonucleotides. Additionally, upstream regulator analysis predicted the activation of several upstream regulator networks including CKAP2L, FOXM1, RABL6, PCLAF, and MITF, while upstream regulator networks of TP53, NUPR1, TRPS1, and CDKN1A were suppressed. Interestingly, elevated expression of AC099850.4 correlated with worse short-term relapse-free survival (log-rank p = 0.01). Taken together, our data are the first to reveal AC099850.4 as an unfavorable prognostic marker in TNBC, associated with more aggressive clinicopathological features, and suggest its potential utilization as a prognostic biomarker and therapeutic target in TNBC.

Advancing Cancer Therapy Predictions with Patient-Derived Organoid Models of Metastatic Breast Cancer

The poor outcome of metastasized breast cancer (BC) stresses the need for reliable personalized oncology and the significance of models recapitulating the heterogeneous nature of BC. Here, we cultured metastatic tumor cells derived from advanced BC patients with malignant ascites (MA) or malignant pleural effusion (MPE) using organoid technology. We identified the characteristics of tumor organoids by applying immunohistochemistry and mutation analysis. Tumor organoids preserved their expression patterns and hotspot mutations when compared to their original metastatic counterpart and are consequently a well-suited in vitro model for metastasized BC. We treated the tumor organoids to implement a reliable application for drug screenings of metastasized cells. Drug assays revealed that responses are not always in accord with expression patterns, pathway activation, and hotspot mutations. The discrepancy between characterization and functional testing underlines the relevance of linking IHC stainings and mutational analysis of metastasized BC with in vitro drug assays. Our metastatic BC organoids recapitulate the characteristics of their original sample derived from MA and MPE and serve as an invaluable tool that can be utilized in a preclinical setting for guiding therapy decisions.

Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes

Breast cancer (BC) is a heterogeneous disease, which is primarily classified according to hormone receptors and HER2 expression. Despite the many advances in BC diagnosis and management, the identification of novel actionable therapeutic targets expressed by cancerous cells has always been a daunting task due to the large heterogeneity of the disease and the presence of non-cancerous cells (i.e., immune cells and stromal cells) within the tumor microenvironment. In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER⁺), HER2⁺, ER⁺HER2⁺, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells' publicly available transcriptomic data derived from 26 BC patients. Restricting the analysis to EPCAM⁺Lin^- tumor epithelial cells, we identified the enriched gene sets in each BC molecular subtype. Integration of single-cell transcriptomic with CRISPR-Cas9 functional screen data identified 13 potential therapeutic targets for ER⁺, 44 potential therapeutic targets for HER2⁺, and 29 potential therapeutic targets for TNBC. Interestingly, several of the identified therapeutic targets outperformed the current standard of care for each BC subtype. Given the aggressive nature and lack of targeted therapies for TNBC, elevated expression of ENO1, FDPS, CCT6A, TUBB2A, and PGK1 predicted worse relapse-free survival (RFS) in basal BC (n = 442), while elevated expression of ENO1, FDPS, CCT6A, and PGK1 was observed in the most aggressive BLIS TNBC subtype. Mechanistically, targeted depletion of ENO1 and FDPS halted TNBC cell proliferation, colony formation, and organoid tumor growth under 3-dimensional conditions and increased cell death, suggesting their potential use as novel therapeutic targets for TNBC. Differential expression and gene set enrichment analysis in TNBC revealed enrichment in the cycle and mitosis functional categories in FDPS^high, while ENO1^high was associated with numerous functional categories, including cell cycle, glycolysis, and ATP metabolic processes. Taken together, our data are the first to unravel the unique gene signatures and to identify novel dependencies and therapeutic vulnerabilities for each BC molecular subtype, thus setting the foundation for the future development of more effective targeted therapies for BC.

Non-Coding RNAs Modulating Estrogen Signaling and Response to Endocrine Therapy in Breast Cancer

The largest part of human DNA is transcribed into RNA that does not code for proteins. These non-coding RNAs (ncRNAs) are key regulators of protein-coding gene expression and have been shown to play important roles in health, disease and therapy response. Today, endocrine therapy of ERα-positive breast cancer (BC) is a successful treatment approach, but resistance to this therapy is a major clinical problem. Therefore, a deeper understanding of resistance mechanisms is important to overcome this resistance. An increasing amount of evidence demonstrate that ncRNAs affect the response to endocrine therapy. Thus, ncRNAs are considered versatile biomarkers to predict or monitor therapy response. In this review article, we intend to give a summary and update on the effects of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) on estrogen signaling in BC cells, this pathway being the target of endocrine therapy, and their role in therapy resistance. For this purpose, we reviewed articles on these topics listed in the PubMed database. Finally, we provide an assessment regarding the clinical use of these ncRNA types, particularly their circulating forms, as predictive BC biomarkers and their potential role as therapy targets to overcome endocrine resistance.

Mechanisms of Resistance to CDK4/6 Inhibitors and Predictive Biomarkers of Response in HR+/HER2-Metastatic Breast Cancer-A Review of the Literature

The latest and newest discoveries for advanced and metastatic hormone receptor-positive (HR+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancer are the three cyclin-dependent kinases 4 and 6 inhibitors (CDK4/6i) in association with endocrine therapy (ET). However, even if this treatment revolutionized the world and continued to be the first-line treatment choice for these patients, it also has its limitations, caused by de novo or acquired drug resistance which leads to inevitable progression after some time. Thus, an understanding of the overview of the targeted therapy which represents the gold therapy for this subtype of cancer is essential. The full potential of CDK4/6i is yet to be known, with many trials ongoing to expand their utility to other breast cancer subtypes, such as early breast cancer, and even to other cancers. Our research establishes the important idea that resistance to combined therapy (CDK4/6i + ET) can be due to resistance to endocrine therapy, to treatment with CDK4/6i, or to both. Individuals' responses to treatment are based mostly on genetic features and molecular markers, as well as the tumor's hallmarks; therefore, a future perspective is represented by personalized treatment based on the development of new biomarkers, and strategies to overcome drug resistance to combinations of ET and CDK4/6 inhibitors. The aim of our study was to centralize the mechanisms of resistance, and we believe that our work will have utility for everyone in the medical field who wants to deepen their knowledge about ET + CDK4/6 inhibitors resistance.

Long non-coding RNA and RNA-binding protein interactions in cancer: Experimental and machine learning approaches

Understanding the complex and specific roles played by non-coding RNAs (ncRNAs), which comprise the bulk of the genome, is important for understanding virtually every hallmark of cancer. This large group of molecules plays pivotal roles in key regulatory mechanisms in various cellular processes. Regulatory mechanisms, mediated by long non-coding RNA (lncRNA) and RNA-binding protein (RBP) interactions, are well documented in several types of cancer. Their effects are enabled through networks affecting lncRNA and RBP stability, RNA metabolism including N⁶-methyladenosine (m⁶A) and alternative splicing, subcellular localization, and numerous other mechanisms involved in cancer. In this review, we discuss the reciprocal interplay between lncRNAs and RBPs and their involvement in epigenetic regulation via histone modifications, as well as their key role in resistance to cancer therapy. Other aspects of RBPs including their structural domains, provide a deeper knowledge on how lncRNAs and RBPs interact and exert their biological functions. In addition, current state-of-the-art knowledge, facilitated by machine and deep learning approaches, unravels such interactions in better details to further enhance our understanding of the field, and the potential to harness RNA-based therapeutics as an alternative treatment modality for cancer are discussed.

Identifying a 6-Gene Prognostic Signature for Lung Adenocarcinoma Based on Copy Number Variation and Gene Expression Data

The occurrence of lung adenocarcinoma (LUAD) is a complicated process, involving the genetic and epigenetic changes of proto-oncogenes and oncogenes. The objective of this study was to establish new predictive signatures of lung adenocarcinoma based on copy number variations (CNVs) and gene expression data. Next-generation sequencing was implemented to obtain gene expression and CNV information. According to univariate, multivariate survival Cox regression analysis, and LASSO analysis, the expression profiles of lung adenocarcinoma patients were screened and a risk score formula was established and experimentally validated in a local cohort. The model was evaluated by three independent cohorts (TCGA-LUAD, GSE31210, and GSE30219), and then validated by clinical samples from LUAD patients. A total of 844 CNV-related differentially expressed genes (CNV-related DEGs) were identified. These genes are significantly associated with the imbalance of various oxidative stress pathways. A CNV-associated-six gene signature was dramatically linked to overall survival in lung adenocarcinoma samples from both training and validation groups. Functional enrichment analysis further revealed involvement of genes in p53 signaling pathway and cell cycle as well as the mismatch repair pathway. Risk score is an independent marker considering clinical parameters and had better prediction in clinical subpopulation. The same signature also classified tumor tissues of clinical patients with CNV detected from their corresponding nontumorous tissues with an accuracy of 0.92. In conclusion, we identified a new class of 6 CNV-related gene markers that may act as efficient prognostic predictors of lung adenocarcinoma, thus contributing to individualized treatment decisions in patients.

LncRNA-Based Classification of Triple Negative Breast Cancer Revealed Inherent Tumor Heterogeneity and Vulnerabilities

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.