Breast Cancer: Current Research
Open Access

Breast cancer; Metabolism; Treatment resistance; Metabolic reprogramming; Therapeutic strategies; Positron emission tomography (PET); Magnetic resonance spectroscopy (MRS); Dichloroacetate (DCA)

Introduction

Metabolism plays a crucial role in cancer development and progression, with alterations in metabolic pathways facilitating tumor growth and survival. In breast cancer, metabolic reprogramming has emerged as a hallmark feature, driving the adaptation of cancer cells to the tumor microenvironment and therapeutic interventions. Understanding the metabolic changes occurring in breast cancer is essential for developing novel therapeutic approaches to overcome treatment resistance and improve patient outcomes [1].

Methodology

Metabolic changes in breast cancer: Breast cancer cells exhibit profound alterations in glucose metabolism, characterized by increased aerobic glycolysis, also known as the Warburg effect. This metabolic shift allows cancer cells to meet their energy demands and support rapid proliferation, even in oxygen-rich environments. Additionally, breast cancer cells display enhanced glutamine metabolism, utilizing glutamine as a source of energy and biosynthetic precursors for macromolecule synthesis [2].

Recent studies have also highlighted the role of lipid metabolism in breast cancer progression. Lipid metabolic pathways are dysregulated in breast cancer cells, leading to increased lipogenesis and lipid uptake to sustain tumor growth and metastasis. Moreover, alterations in amino acid metabolism, including serine and glycine metabolism, contribute to the metabolic plasticity of breast cancer cells and their ability to adapt to changing nutrient conditions.

Impact on treatment resistance: Metabolic changes in breast cancer have significant implications for treatment resistance. Enhanced glycolysis and altered lipid metabolism confer resistance to conventional chemotherapy and targeted therapies, such as hormone therapy and HER2-targeted agents. Metabolic reprogramming enables cancer cells to survive under nutrient-deprived conditions and evade cell death pathways activated by anticancer agents [3].

Furthermore, metabolic plasticity in breast cancer cells contributes to the emergence of therapy-resistant phenotypes, including cancer stem cells and dormant tumor cells. These therapy-resistant populations rely on specific metabolic pathways for their survival and may fuel disease recurrence and metastasis following initial treatment [4].

Potential therapeutic strategies: Targeting metabolic vulnerabilities in breast cancer represents a promising therapeutic approach to overcome treatment resistance and improve patient outcomes. Preclinical and clinical studies have identified several metabolic inhibitors and repurposed drugs that selectively target cancer cell metabolism while sparing normal cells [5].

Inhibitors of glycolysis, such as 2-deoxyglucose (2-DG) and dichloroacetate (DCA), have shown promising results in preclinical models of breast cancer, sensitizing cancer cells to chemotherapy and radiotherapy. Additionally, inhibitors of glutamine metabolism, fatty acid synthesis, and amino acid metabolism are being actively investigated as potential therapeutic agents for breast cancer treatment.

Combination therapies targeting multiple metabolic pathways represent a rational approach to circumvent metabolic heterogeneity and prevent the emergence of treatment-resistant phenotypes. By disrupting the metabolic adaptations of breast cancer cells, these combination strategies hold the potential to enhance treatment efficacy and prolong patient survival [6].

Applications: Treatment personalization: Understanding metabolic changes in breast cancer cells can help tailor treatment strategies based on the specific metabolic profiles of individual tumors, potentially improving treatment response and minimizing resistance.

Therapeutic targets: Metabolic pathways dysregulated in breast cancer cells, such as glycolysis, fatty acid synthesis, and glutamine metabolism, can serve as potential therapeutic targets for novel anti-cancer agents, offering new avenues for treatment development [7].

Drug resistance mechanisms: Metabolic reprogramming contributes to drug resistance in breast cancer by altering cellular energy metabolism, promoting detoxification pathways, and enhancing antioxidant defenses, highlighting the importance of targeting metabolic vulnerabilities to overcome resistance.

Combination Therapies: Combining metabolic inhibitors with conventional chemotherapeutic agents or targeted therapies may overcome treatment resistance and improve treatment outcomes by targeting multiple pathways essential for cancer cell survival and proliferation [8].

Imaging biomarkers: Metabolic imaging techniques such as positron emission tomography (PET) using glucose analogs or magnetic resonance spectroscopy (MRS) can non-invasively assess metabolic changes in breast tumors, providing valuable biomarkers for treatment response prediction and monitoring.

Nutritional Interventions: Dietary interventions targeting specific metabolic pathways, such as caloric restriction, ketogenic diets, or nutrient modulation, may complement conventional treatments and enhance their efficacy by sensitizing cancer cells to therapy or inhibiting tumor progression [9].

Metabolomics profiling: Comprehensive metabolomics profiling of breast cancer tissues, biofluids or circulating tumor cells can identify metabolic biomarkers associated with treatment resistance, disease progression, and prognosis, guiding personalized treatment decisions and therapeutic interventions.

Tumor microenvironment modulation: Metabolic changes in the tumor microenvironment, such as hypoxia, acidosis, and nutrient deprivation, influence cancer cell behavior and treatment response, suggesting potential strategies to manipulate the tumor microenvironment to enhance therapeutic efficacy [10].

Precision medicine: Integrating metabolic profiling with genomic, transcriptomic, and proteomic data can improve the molecular classification of breast cancer subtypes and identify metabolic vulnerabilities specific to each subtype, facilitating precision medicine approaches and personalized treatment strategies.

Translational research: Translational research efforts focused on elucidating the molecular mechanisms underlying metabolic changes in breast cancer and developing innovative therapeutic interventions hold promise for improving patient outcomes and addressing unmet clinical needs in the management of treatment-resistant and advanced disease.

Discussion

Breast cancer remains a significant global health concern, with treatment resistance and disease progression posing significant challenges in patient management. In recent years, growing evidence has highlighted the intricate relationship between metabolic changes in breast cancer cells and their impact on treatment response and disease progression. Understanding these metabolic alterations is crucial for developing more effective therapeutic strategies to combat this deadly disease.

Conclusion

Metabolic changes in breast cancer play a crucial role in treatment resistance and disease progression. Understanding the complex interplay between metabolic reprogramming and therapeutic responses is essential for developing more effective treatment strategies to combat this deadly disease. Targeting metabolic vulnerabilities in breast cancer represents a promising avenue for overcoming treatment resistance and improving patient outcomes, offering hope for a future where breast cancer is no longer a life-threatening illness.

References

1. Mavragani IV, Nikitaki Z, Kalospyros SA, Georgakilas GA (2019) Ionizing Radiation and Complex DNA Damage: From Prediction to Detection Challenges and Biological Significance. Cancers 11: 1789.

Indexed at, Google Scholar, Crossref

2. Apetoh L, Ghiringhelli F, Tesniere A, Criollo A, Ortiz C, et.al (2007) The Interaction Between HMGB1 and TLR4 Dictates the Outcome of Anticancer Chemotherapy and Radiotherapy. Immunol Rev 220: 47-59.

Indexed at, Google Scholar, Crossref

3. Fucikova J, Kepp O, Kasikova L, Petroni G, Yamazaki T, et.al (2020) Detection of Immunogenic Cell Death and Its Relevance for Cancer Therapy. Cell Death Dis 11: 1013.

Indexed at, Google scholar , Crossref

4. Burnette BC, Liang H, Lee Y, Chlewicki L, Khodarev NN, et.al (2011) The Efficacy of Radiotherapy Relies upon Induction of Type I Interferon-Dependent Innate and Adaptive Immunity. Cancer Res 71: 2488-2496

Indexed at, Google Scholar, Crossref

5. Jarand J, Levin A, Zhang L, Huitt G, Mitchell JD, et al. (2011) Clinical and microbiologic outcomes in patients receiving treatment for Mycobacterium abscessus pulmonary disease. Clin Infect Dis 52: 565-571.

Indexed at, Google Scholar, Crossref

6. Wu Q, Li J, Zhu S, Wu J, Chen C, et al. (2017) Breast Cancer Subtypes Predict the Preferential Site of Distant Metastases: A SEER Based Study. Oncotarget 8: 27990-27996.

Indexed at, Google Scholar, Crossref

7. Yoneyama K, Nakagawa M, Hara A (2018) Bladder Metastasis from Primary Breast Cancer: A Case Report. Surg Case Rep 4: 73.

Indexed at, Google Scholar, Crossref

8. Rothman N, Garcia-Closas M, Chatterjee N, Malats N, Wu X, et al. (2010) A Multi-Stage Genome-Wide Association Study of Bladder Cancer Identifies Multiple Susceptibility Loci. Nat Genet 42: 978-984

Indexed at, Google Scholar, Crossref

9. Sampson JN, Wheeler WA, Yeager M, Panagiotou O, Wang Z, et al. (2015) Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types. J Natl Cancer Inst 107: djv279.

Indexed at, Google Scholar, Crossref

10. Hong R, Sun H, Li D, Yang W, Fan K, et al. (2022) A Review of Biosensors for Detecting Tumor Markers in Breast Cancer. Life 12: 342.

Indexed at, Google Scholar, Crossref