Advancement of mass spectrometry-based proteomics technologies to explore triple negative breast cancer

Application of the Human Proteome in Disease, Diagnosis, and Translation into Precision Medicine: Current Status and Future Prospects

This review summarizes the existing studies of human proteomics technology in the medical field with a focus on the development mechanism of a disease and its potential in discovering biomarkers. Through a systematic review of the relevant literature, we found the significant advantages and application scenarios of proteomics technology in disease diagnosis, drug development, and personalized treatment. However, the review also identifies the challenges facing proteomics technologies, including sample preparation of low-abundance proteins, massive amounts of data analysis, and how research results can be better used in clinical practice. Finally, this work discusses future research directions, including the development of more effective proteomics technologies, strengthening the integration of multi-source omics technologies, and promoting the application of AI in the human proteome.

Mass Spectrometry-Based Proteomics for Classification and Treatment Optimisation of Triple Negative Breast Cancer

Triple-negative breast cancer (TNBC) presents a significant medical challenge due to its highly invasive nature, high rate of metastasis, and lack of drug-targetable receptors, which together lead to poor prognosis and limited treatment options. The traditional treatment guidelines for early TNBC are based on a multimodal approach integrating chemotherapy, surgery, and radiation and are associated with low overall survival and high relapse rates. Therefore, the approach to treating early TNBC has shifted towards neoadjuvant treatment (NAC), given to the patient before surgery and which aims to reduce tumour size, reduce the risk of recurrence, and improve the pathological complete response (pCR) rate. However, recent studies have shown that NAC is associated with only 30% of patients achieving pCR. Thus, novel predictive biomarkers are essential if treatment decisions are to be optimised and chemotherapy toxicities minimised. Given the heterogeneity of TNBC, mass spectrometry-based proteomics technologies offer valuable tools for the discovery of targetable biomarkers for prognosis and prediction of toxicity. These biomarkers can serve as critical targets for therapeutic intervention. This review aims to provide a comprehensive overview of TNBC diagnosis and treatment, highlighting the need for a new approach. Specifically, it highlights how mass spectrometry-based can address key unmet clinical needs by identifying novel protein biomarkers to distinguish and early prognostication between TNBC patient groups who are being treated with NAC. By integrating proteomic insights, we anticipate enhanced treatment personalisation, improved clinical outcomes, and ultimately, increased survival rates for TNBC patients.

Targeted proteomics using parallel reaction monitoring confirms salivary proteins indicative of metastatic triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype due to the absence of hormonal receptors. Our study aimed to identify and determine the effectiveness of salivary proteins as candidate markers for metastatic TNBC subtype using parallel reaction monitoring mass spectrometry (PRM-MS). Three salivary proteins (lipocalin-1, SMR3B, and plastin-2) that showed significant differential expression in label-free quantitation (LFQ) between TNBC (N = 6) and health subjects (HS; N = 6) were selected for further validation. The developed PRM assay was used to quantify peptides GLST and NNLE (lipocalin-1), VYAL and MINL (Plastin-2) and GPYP, and IPPP (SMR3B) on a different cohort of TNBC patients (N = 20) and HS (N = 20) for evaluating their discriminating performances. Quantitative validation using PRM correlated well with the LFQ results, and 5 peptides from three proteins showed a similar up-or down-regulation. Subsequently, these proteins were validated by Western blot analysis. Compared to one protein's performance as an individual marker, the five-signature panel with salivary GLST, VYAL, MINL, GPYP, and IPPP achieved better performance in differentiating aggressive TNBC and HS with sensitivity (80%) and specificity (95%). Targeted proteomic analysis of the prioritized proteins highlights a peptide-based signature in saliva as the potential predictor to distinguish between TNBC and HS. SIGNIFICANCE OF THE STUDY: This study was designed to identify and quantify potential markers in saliva from the triple-negative breast cancer (TNBC) patients using parallel reaction monitoring assay. Three salivary proteins, Lipocalin-1 (LCN-1), Submaxillary androgen-regulated protein 3B (SMR3B), and Plastin-2 (LCP-1) selected in the discovery-phase were further quantified by targeted proteomics and Western blots. The salivary proteins successfully differentiated TNBC patients from healthy subjects with a sensitivity (80%) and specificity (95%).

A Gene Selection Method Based on Outliers for Breast Cancer Subtype Classification

Breast cancer is the second most common cancer type and is the leading cause of cancer-related deaths worldwide. Since it is a heterogeneous disease, subtyping breast cancer plays an important role in performing a specific treatment. Gene expression data is a viable alternative to be employed on cancer subtype classification, as they represent the state of a cell at the molecular level, but generally has a relatively small number of samples compared to a large number of genes. Gene selection is a promising approach that addresses this uneven high-dimensional matrix of genes versus samples and plays an important role in the development of efficient cancer subtype classification. In this work, an innovative outlier-based gene selection (OGS) method is proposed to select relevant genes for efficiently and effectively classify breast cancer subtypes. Experiments show that our strategy presents an F₁ score of 1.0 for basal and 0.86 for her 2, the two subtypes with the worst prognoses, respectively. Compared to other methods, our proposed method outperforms in the F₁ score using 80% less genes. In general, our method selects only a few highly relevant genes, speeding up the classification, and significantly improving the classifier's performance.

Comprehensive proteomics and sialiomics of the anti-proliferative activity of safranal on triple negative MDA-MB-231 breast cancer cell lines

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with no efficient treatment. Researchers have indicated the importance of quantitative approaches on proteome and different post-translation modifications studies both in diagnosis and treatment purposes. Sialic acid-containing glycopeptides (the sialiome) is one of these modifications which can be used as a tool in cancer diagnosis or therapeutic strategies since the sialylation is strongly associated with cancer migration and metastasis. Based on our study, safranal, which is a non-toxic compound in orally intakes, exhibits a significant cytotoxic effect on MDA-MB-231 in comparison to normal cells. We conducted a comprehensive proteomics and sialiomics analysis of safranal treated MDA-MB-231 cells by using a combination of TMT labeling and titanium dioxide enrichment of sialylated N-linked glycopeptides to investigate the underlying molecular mechanism behind safranal-induced apoptosis. Safranal has main effect on the inhibition of metabolism and mitochondrial dysfunction. It regulates proteins considered as activator of DNA fragmentation and apoptosis mediators. Moreover, safranal regulates sialylation of glycoproteins involving in cellular adhesion, migration and survival. It suppresses cell survival and metastasis through the alteration of the sialylation level on important signaling receptors. These results highlight the impact of safranal as a potent anticancer compound on TNBCs which also can be strongly used in daily diets. SIGNIFICANCE: In first step, we evaluated the cell viability of MDA-MB-231 cell lines against the purified saffron components (total crocin, picrocrocin, crocin I and safranal). Safranal was the only compound demonstrated the anti-proliferation effect. In order to obtain an understanding of safranal cytotoxic effect on MDA-MB-231, we designed the three set of treated cell lines in 30 min, 12 h and 24 h time-points in three replicates and a combination of TMT-based labeling quantitative proteomics and titanium dioxide (TiO2)-based enrichment of sialylated N-linked glycopeptides for sialiomics analysis as a strategy to follow the more detailed mechanisms of safranal effect. The results of bioinformatics analysis revealed the multifunction role of safranal on MDA-MB-231 cell lines. Safranal mainly dysregulates mitochondrial function, inhibits metabolism and starts initial signaling of apoptosis which lead to DNA fragmentation. Moreover, safranal caused the majority of down-regulation in sialylation profile in all time-points. Safranal also declines the cell survival, adhesion and migration by dysregulation of the sialylation level in important proteins including integrins, tumor necrosis factor receptor and cell adhesion molecules (CAMs). The results provide a set of therapeutic targets for triple negative breast cancer which can help designing of effective anticancer drugs specially in targeted therapies.

Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.

High-throughput, Label-Free Quantitative Proteomic Studies of the Anticancer Effects of Electrical Pulses with Turmeric Silver Nanoparticles: an in vitro Model Study

Triple negative breast cancer (TNBC) represents 15–20% of the over one million new breast cancer cases occurring each year. TNBC is an aggressive cancer phenotype, with low 5-year survival rates, high 3-year recurrence rates, and increased risk of metastasis. A lack of three commonly exploited hormone receptors renders TNBC resistant to endocrine therapies and lends to its critical absence of viable therapeutic targets. This necessitates the development of alternate and effective novel therapeutic strategies for TNBC. Towards this, our current work seeks to develop the technique of Electrical pulse (EP)-mediated Turmeric silver nanoparticles (TurNP) therapy, known as Electrochemotherapy (ECT), to effectively target TNBC cells. This technique involves the efficient delivery of natural bioactive molecules with anti-cancer effects via a biophysical means. In these experiments, the bioactive molecules are turmeric, a dried rhizome of Curcuma longa that has been used for centuries, both as a dietary supplement and as a medicine in Ayurveda (science of life) in the Indian subcontinent and in traditional Chinese medicine. Our results reveal the combined effect of TurNP + EP treatment in reducing MDA-MB-231 cell viability to as low as 9% at 12 h. Showing biological selectivity, this combination treatment has a substantially lower effect on non-tumorigenic mammary epithelial MCF10A cells (67% viability). To gain mechanistic insights into the actions of TurNP-based ECT treatment, we performed high-throughput, label-free quantitative proteomics studies. Proteomics results indicate that TurNP + EP treatment significantly influenced expression of a diverse list of proteins, including receptors, transcription factors, structural proteins, kinases, and metabolic enzymes. This include the downregulation of 25 proteins in PI3K-Akt signaling pathway (such as GRB2, EGFR, EPHA2, GNB1, GNB2, 14–3–3 family, and Integrin family proteins), and 12 proteins (AKR1A1, ALDOA, ALDOC, PGK1, PGM1, PGAM1, ENO1, ENO2, GAPDH, TPI1, LDHA, and LDHB) in the glycolytic pathway with concomitant reduction in metabolite levels (glucose uptake, and intracellular- lactate, glutamine, and glutamate). Compared to TurNP alone, TurNP + EP treatment upregulated 66 endoplasmic reticulum and 193 mitochondrial proteins, enhancing several processes and pathways, including Pyruvate Metabolism, Tricarboxylic acid (TCA) cycle, and Oxidative Phosphorylation (OXPHOS), which redirected the TNBC metabolism to mitochondria. This switch in the metabolism caused excessive production of H₂O₂ reactive oxygen species (ROS) to inflict cell death in MDA-MB-231 cells, demonstrating the potency of this treatment.

Use of Lectin-based Affinity Techniques in Breast Cancer Glycoproteomics: A Review

Changes in glycoprotein content, altered glycosylations, and aberrant glycan structures are increasingly recognized as cancer hallmarks. Because breast cancer is one of the most common causes of cancer deaths in the world, it is highly urgent to find other reliable biomarkers for its initial diagnosis and to learn as much as possible about this disease. In this Review, the applications of lectins to a screening of potential breast cancer biomarkers published during recent years are overviewed. These data provide a deeper insight into the use of modern strategies, technologies, and scientific knowledge in glycoproteomic breast cancer research. Particular attention is concentrated on the use of lectin-based affinity techniques, applied independently or most frequently in combination with mass spectrometry, as an effective tool for the targeting, separation, and reliable identification of glycoprotein molecules. Individual procedures and lectins used in published glycoproteomic studies of breast-cancer-related glycoproteins are discussed. The summarized approaches have the potential for use in diagnostic and predictive applications. Finally, the use of lectins is briefly discussed from the view of their future applications in the analysis of glycoproteins in cancer.

Polymeric nanoassemblies for enrichment and detection of peptides and proteins in human breast milk

Human breast milk is an understudied biological fluid that may be useful for early detection of breast cancer. Methods for enriching and detecting biomarkers in human breast milk, however, are not as well-developed as compared with other biological fluids. In this work, we demonstrate a new enrichment method based on polymeric nanoassemblies that is capable of enhancing the mass spectrometry-based detection of peptides and proteins in human breast milk. In this method, positively charged nanoassemblies are used to selectively deplete abundant proteins in milk based on electrostatic interactions, which simplifies the mixture and enhances detection of positively charged peptides and proteins. Negatively charged nanoassemblies are used in a subsequent enrichment step to further enhance the detection and quantification of trace-level peptides and proteins. Together the depletion and enrichment steps allow model biomarkers to be detected at low nM levels, which are close to instrumental limits of detection. This new method not only demonstrates the ability to detect proteins in human breast milk but also provides an alternative approach for targeted protein detection in complex biological matrices. Graphical abstract.

Proteomic investigation on bio-corona of Au, Ag and Fe nanoparticles for the discovery of triple negative breast cancer serum protein biomarkers

Nowadays, there are no targeted therapeutic modalities for triple negative breast cancer (TNBC). This disease is associated with poor prognosis and worst clinical outcome because of the aggressive nature of the tumor, delayed diagnosis, and non-specific symptoms in the early stages. Therefore, identification of novel specific TNBC serum biomarkers for screening and therapeutic purposes remains an urgent clinical requirement. New user-friendly and cheap methods for biomarker identification are needed, and nanotechnology offers new opportunities. When dispersed in blood, nanoparticles (NPs) are covered by a protein shell termed "protein corona" (PC). While alterations in protein patterns are challeging to detect by conventional blood analyses, PC acts as a "nano-concentrator" of serum proteins with affinity for NPs' surface. So, the characterization of PC could allow the detection of otherwise undetectable changes in protein concentration at an early stage of the disease or after chemotherapy or surgery. To explore this research idea, serum samples from 8 triple negative breast cancer (TNBC) patients and 8 patients without malignancy were allowed to interact with gold nanoparticles (AuNPs: 10.02 ± 0.91 nm), silver nanoparticles (AgNPs: 9.73 ± 1.70 nm) and magnetic nanoparticles (MNPs: (9.30 ± 0.67 nm). Here, in order to identify biomarker candidates in serum of TNBC patients, these nanomaterials were combined with electrophoretic separation (SDS-PAGE) to performed qualitative and quantitative comparisons of the serum proteomes of TNBC patients (n = 8) and healthy controls (n = 8) by liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis. The results were validated through a sequential window acquisition of all theoretical mass spectra (SWATH) analysis, performed in total serum samples (patients and controls) using this approach as a multiple reaction monitoring (MRM) analysis. SIGNIFICANCE: It is well known that several proteins presented in human serum are important biomarkers for the diagnosis or prognosis of different diseases, as triple negative breast cancer (TNBC). Determining how nanomaterials as gold nanoparticles (AuNPs: 10.02 ± 0.91 nm), silver nanoparticles (AgNPs: 9.73 ± 1.70 nm) and magnetic nanoparticles (MNPs: (9.30 ± 0.67 nm) interact with human serum will assist not only in understanding their effects on the biological system (biocompability and toxicity), but also to obtain information for developing novel nanomaterials with high specificity and selectivity towards proteins with an important biological function (prognostic and diagnostic protein biomarkers).

Quantitative proteomic analysis of enhanced cellular effects of electrochemotherapy with Cisplatin in triple-negative breast cancer cells

Due to the lack of the three main receptors, triple negative breast cancer (TNBC) is refractive to standard chemotherapy. Hence, alternate therapies are needed. TNBCs utilize glycolysis, which heightens their growth, proliferation, invasiveness, chemotherapeutic resistance and poor therapeutic response. This calls for novel therapeutic strategies to target these metabolic vulnerabilities present in TNBC. Electroporation-mediated chemotherapy, known as electrochemotherapy (ECT) is gaining momentum as an attractive alternative. However, its molecular mechanisms need better understanding. Towards this, label-free quantitative proteomics is utilized to gain insight into the anticancer mechanisms of ECT using electrical pulses (EP) and Cisplatin (CsP) on MDA-MB-231, human TNBC cells. The results indicate that EP + CsP significantly downregulated 14 key glycolysis proteins (including ENO1, LDHA, LDHB, ACSS2, ALDOA, and PGK1), compared to CsP alone. EP + CsP caused a switch in the metabolism with upregulation of 34 oxidative phosphorylation pathway proteins and 18 tricarboxylic acid (TCA) cycle proteins compared to CsP alone, accompanied by the upregulation of proteins linked to several metabolic reactions, which produce TCA cycle intermediates. Moreover, EP + CsP promoted multiple pathways to cause 1.3-fold increase in the reactive oxygen species concentration and induced apoptosis. The proteomics results correlate well with cell viability, western blot, and qPCR data. While some effects were similar for EP, more comprehensive and long-lasting effects were observed for EP + CsP, which demonstrate the potential of EP + CsP against TNBC cells.

A targeted mass spectrometry immunoassay to quantify osteopontin in fresh-frozen breast tumors and adjacent normal breast tissues

Osteopontin (OPN) is a multifunctional protein that can activate cell-signaling pathways and lead to cancer development and metastasis. Elevated OPN expression was reported in different cancer types, including breast tumors. Here, we present a new immuno-mass spectrometry method for OPN quantification in fresh-frozen malignant and adjacent normal human breast tissues. For quantification we used two proteotypic peptides: OPN-peptide-1 and OPN-peptide-2. Peptide concentrations were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode with stable isotope standards (SIS) and immuno-affinity enrichment for isolation of OPN peptides. Based on the OPN-peptide-1, the average OPN concentration in normal breast tissue was 19.42 μg/g, while the corresponding level in breast tumors was 603.9 μg/g. Based on OPN-peptide-2, the average concentration in normal breast tissue was 19.30 μg/g and in breast tumors 535.0 μg/g. In ER/PR/HER2(-) patients the OPN levels in breast tumors were significantly higher than in corresponding normal breast tissue samples, whereas in the single ER/PR/HER2(+) patient the OPN concentration in tumor samples was lower than in normal breast tissue sample. In conclusion, the current method is considered promising for the quantification of OPN in research and in clinical settings and should be further studied in breast cancer patients. SIGNIFICANCE: A new immuno-mass spectrometry method was successfully developed and applied to determine OPN concentrations in malignant tumor and normal breast tissues from six patients, and the method is promising for OPN quantification in both research and clinical settings.

Methodologies and Applications of Proteomics for Study of Yeast Strains: An Update

Yeasts are one of the mostly used microorganisms as models in several studies. A wide range of applications in different processes can be attributed to their intrinsic characteristics. They are eukaryotes and therefore valuable expression hosts that require elaborate post-translational modifications. Their arsenal of proteins has become a valuable biochemical tool for the catalysis of several reactions of great value to the food (beverages), pharmaceutical and energy industries. Currently, the main challenge in systemic yeast biology is the understanding of the expression, function and regulation of the protein pool encoded by such microorganisms. In this review, we will provide an overview of the proteomic methodologies used in the analysis of yeasts. This research focuses on the advantages and improvements in their most recent applications with an understanding of the functionality of the proteins of these microorganisms, as well as an update of the advances of methodologies employed in mass spectrometry.

Knockdown of DNA/RNA-binding protein KIN17 promotes apoptosis of triple-negative breast cancer cells

Effective therapy for breast cancer has been extensively studied worldwide, particularly for triple-negative breast cancer and drug-resistant subtypes. DNA/RNA-binding protein KIN17 (kin17) has been reported to be significantly upregulated in breast cancer cells, and is proposed to serve a role in the regulation of cell proliferation. The present study further investigated the association of kin17-knockdown with breast cancer cell apoptosis. Cell Counting kit-8, flow cytometry, TUNEL assay and caspase 3/7 analysis were performed on MDA-MB-231 cells to determine the association between kin17 and breast cancer cell apoptosis. In addition, western blot analysis was performed to investigate the mechanism of kin17 in the apoptosis of MDA-MB-231 cells. The results revealed that knockdown of kin17 inhibited proliferation and promoted apoptosis of MDA-MB-231 cells, and suggested a poly (adenosine diphosphate-ribose) polymerase-related mechanism behind the apoptosis of the cells. These findings suggested that kin17 could become a novel target for breast cancer therapy.

Differential expression of NPM, GSTA3, and GNMT in mouse liver following long-term in vivo irradiation by means of uranium tailings

Uranium tailings (UT) are formed as a byproduct of uranium mining and are of potential risk to living organisms. In the present study, we sought to identify potential biomarkers associated with chronic exposure to low dose rate γ radiation originating from UT. We exposed C57BL/6J mice to 30, 100, or 250 μGy/h of gamma radiation originating from UT samples. Nine animals were included in each treatment group. We observed that the liver central vein was significantly enlarged in mice exposed to dose rates of 100 and 250 μGy/h, when compared with nonirradiated controls. Using proteomic techniques, we identified 18 proteins that were differentially expressed (by a factor of at least 2.5-fold) in exposed animals, when compared with controls. We chose glycine N-methyltransferase (GNMT), glutathione S-transferase A3 (GSTA3), and nucleophosmin (NPM) for further investigations. Our data showed that GNMT (at 100 and 250 μGy/h) and NPM (at 250 μGy/h) were up-regulated, and GSTA3 was down-regulated in all of the irradiated groups, indicating that their expression is modulated by chronic gamma radiation exposure. GNMT, GSTA3, and NPM may therefore prove useful as biomarkers of gamma radiation exposure associated with UT. The mechanisms underlying those changes need to be further studied.

Evaluation and optimization of reduction and alkylation methods to maximize peptide identification with MS-based proteomics

Mass spectrometry (MS) has become an increasingly important technique to analyze proteins. In popular bottom-up MS-based proteomics, reduction and alkylation are routine steps to facilitate peptide identification. However, incomplete reactions and side reactions may occur, which compromise the experimental results. In this work, we systematically evaluated the reduction step with commonly used reagents, i.e., dithiothreitol, 2-mercaptoethanol, tris(2-carboxyethyl)phosphine, or tris(3-hydroxypropyl)phosphine, and alkylation with iodoacetamide, acrylamide, N-ethylmaleimide, or 4-vinylpyridine. By using digested peptides from a yeast whole-cell lysate, the number of proteins and peptides identified were very similar using four different reducing reagents. The results from four alkylating reagents, however, were dramatically different with iodoacetamide giving the highest number of peptides with alkylated cysteine and the lowest number of peptides with incomplete cysteine alkylation and side reactions. Alkylation conditions with iodoacetamide were further optimized. To identify more peptides with cysteine, thiopropyl-sepharose 6B resins were used to enrich them, and the optimal conditions were employed for the reduction and alkylation. The enrichment resulted in over three times more cysteine-containing peptides than without enrichment. Systematic evaluation of the reduction and alkylation with different reagents can aid in a better design of bottom-up proteomic experiments.

Expression and prognostic significance of ECT2 in invasive breast cancer

Aims

To investigate the expression of epithelial cell transforming sequence 2 (ECT2) in invasive breast cancer and its prognostic significance.

Methods

ECT2 immunohistochemical detection was performed in 165 breast cancer specimens and 100 normal control tissues. Univariable and multivariable Cox proportional hazards regression model analysis was used to confirm independent prognostic factors. The PHREG procedure linear hypotheses testing method was used to analyse survival data.

Results

Expression of ECT2 in breast cancer was significantly higher than that of the normal control group (p<0.001), and it was related to tumour grade, the status of lymph node metastasis, TNM staging, recurrence status, menopausal status, and the Ki-67 proliferation index (p<0.05), and not related to age, tumour size, tumour type, expression of estrogen receptor, progesterone receptor and human epidermal growth factor 2, and triple-negative disease (p>0.05). Univariable analysis showed that expression of ECT2, the status of lymph node metastasis, triple-negative disease and Ki-67 proliferation index were related to the overall survival of patients with breast cancer (p<0.001, p=0.006, p=0.001, p=0.041, respectively). PHREG procedure linear hypotheses testing results for overall survival revealed that high expression of ECT2, lymph node metastasis, triple-negative disease and high Ki-67 proliferation index predicted lower overall survival rates. Multivariable Cox regression indicated that high expression of ECT2 and triple-negative disease were independent prognostic factors for patients with breast cancer (p<0.001, p=0.004, respectively).

Conclusions

Expression of ECT2 may be one of the main causes of the occurrence and development of breast cancer, and high expression of ECT2 as an independent prognostic factor predicts a poor prognosis. ECT2 could also be a potential molecular target for designing therapeutic strategies for breast cancer.

Understanding breast cancer - The long and winding road

Background

Despite a remarkable increase in the depth of our understanding and management of breast cancer in the past 50 years, the disease is still a major public health problem worldwide and poses significant challenges. The palpability of breast tumors has facilitated diagnosis and documentation since ancient times. The earliest descriptions of breast cancer date back to around 3500 BCE. For centuries to follow, theories by Hippocrates (460 BCE) and Galen (200 CE), attributing the cause of breast cancer to an “excess of black bile” and treatment options including the use of opium and castor oil, prevailed. Surgical resection was introduced in the 18th century. The advent of modern medicine led to the development of novel treatment options that include hormonal, targeted and chemo-therapies. There are still several therapeutic challenges including the treatment of triple negative breast cancer (TNBC), and overcoming drug resistance.

Scope of review

The increased incidence and awareness of breast cancer has led to significant changes in diagnosis and treatment in recent decades. But, mankind has come a long way. Herein, I have traced how our understanding of breast cancer has evolved from the early description of the disease around 460 BCE as “black bile-containing crab-like tumors” to the conventional as a heterogeneous disease with high degree of diversity between and within tumors, as well as among breast cancer patients. How is breast cancer treated today and how do risk factors, breast cancer subtype and drug resistance contribute to the therapeutic challenges at the turn of the 21st century?

Major conclusions

Breast cancer remains a serious public health issue worldwide. However, appreciable growth in our understanding of breast cancer in the past century has led to remarkable progress in the early detection, treatment and prevention of the disease. The clinical focus is shifting more towards tailored therapy as more targets are characterized and novel highly innovative approaches are developed.

General significance

Tracing the history of breast cancer, highlights how increased awareness of the disease, and progress in research and development have enhance our understanding of the disease.

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The humoral, lymphatic and anti-hormonal theories of breast cancer

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Introduction of radical mastectomy, radiotherapy, mammography, and targeted therapy

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The introduction of randomized trial

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Breast cancer foundations, awareness and the Angelina Jolie effect

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Promising future for tailored therapy