Breast Cancer Stem-Like Cells in Drug Resistance: A Review of Mechanisms and Novel Therapeutic Strategies to Overcome Drug Resistance
Bibliographic record
Abstract
Breast cancer is the most frequent type of malignancy in women worldwide, and drug resistance to the available systemic therapies remains a major challenge. At the molecular level, breast cancer is heterogeneous, where the cancer-initiating stem-like cells (bCSCs) comprise a small yet distinct population of cells within the tumor microenvironment (TME) that can differentiate into cells of multiple lineages, displaying varying degrees of cellular differentiation, enhanced metastatic potential, invasiveness, and resistance to radio- and chemotherapy. Based on the expression of estrogen and progesterone hormone receptors, expression of human epidermal growth factor receptor 2 (HER2), and/or BRCA mutations, the breast cancer molecular subtypes are identified as TNBC, HER2 enriched, luminal A, and luminal B. Management of breast cancer primarily involves resection of the tumor, followed by radiotherapy, and systemic therapies including endocrine therapies for hormone-responsive breast cancers; HER2-targeted therapy for HER2-enriched breast cancers; chemotherapy and poly (ADP-ribose) polymerase inhibitors for TNBC, and the recent development of immunotherapy. However, the complex crosstalk between the malignant cells and stromal cells in the breast TME, rewiring of the many different signaling networks, and bCSC-mediated processes, all contribute to overall drug resistance in breast cancer. However, strategically targeting bCSCs to reverse chemoresistance and increase drug sensitivity is an underexplored stream in breast cancer research. The recent identification of dysregulated miRNAs/ncRNAs/mRNAs signatures in bCSCs and their crosstalk with many cellular signaling pathways has uncovered promising molecular leads to be used as potential therapeutic targets in drug-resistant situations. Moreover, therapies that can induce alternate forms of regulated cell death including ferroptosis, pyroptosis, and immunotherapy; drugs targeting bCSC metabolism; and nanoparticle therapy are the upcoming approaches to target the bCSCs overcome drug resistance. Thus, individualizing treatment strategies will eliminate the minimal residual disease, resulting in better pathological and complete response in drug-resistant scenarios. This review summarizes basic understanding of breast cancer subtypes, concept of bCSCs, molecular basis of drug resistance, dysregulated miRNAs/ncRNAs patterns in bCSCs, and future perspective of developing anticancer therapeutics to address breast cancer drug resistance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".