Diletta Favero
Daniele Generali
Francesco Schettini- 1Department of Medical Oncology, IRCCS Ospedale Policlinico San Martino, Genova, Italy
- 2Translational Genomics and Targeted Therapies in Solid Tumors Group, August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- 3Breast and Brain Unit, ASST Cremona, Cremona, Italy
- 4Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
- 5Medical Oncology Department, Hospital Clinic of Barcelona, Barcelona, Spain
- 6Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
Editorial on the Research Topic
Diagnostic, prognostic and predictive factors of response in the era of precision oncology in breast cancer
Breast cancer (BC) is a multifaceted disease, characterized by distinct molecular subtypes and various biological features with different prognostic and therapeutic implications (1). The prognosis of patients diagnosed with BC has undergone a remarkable transformation in the last twenty years, nonetheless there is still a subset of women who experience a poor response to treatment strategies, and the outcomes for these individuals are frequently unfavorable (2). The examination of the cancer genome and the increasing utilization of next-generation sequencing (NGS) platforms have led to a revolution in our capacity to investigate, diagnose and treat cancers, including breast tumors (3). Specifically, multi-gene tests can now refine the prognosis of early-stage BC patients beyond standard clinicopathological features, supporting also the decision for the treatment escalation or de-escalation (4, 5). It might also be helpful in guiding potential therapeutical approaches in advanced hormone receptor-positive (HR+) disease, at least in the clinical research setting (6–8). Several mutations detectable in tumor tissue or via liquid biopsy can lead to targeted therapeutic treatments, like the novel oral selective estrogen degrader (SERD) elacestrant in ESR1-mutant advanced HR+ BC, the selective PI3K inhibitor alpelisib in combination with endocrine treatment in PIK3CA-mutant HR+ metastatic BC (MBC) or the small molecules inhibitors larotrectinib and entrectinib in MBC with rare but detectable NTRAK fusions (9–12). Nevertheless, although giant steps have been made, much research is still needed to bring a broader personalized molecularly-driven approach to the clinical management of patients affected by breast tumors.
This Research Topic embodies 32 novel studies derived from basic, translational and clinical research in the field of precision medicine in BC, with a particular focus on the discovery of molecular diagnostic and/or prognostic tools as well as predictive biomarkers of response to targeted therapies. Specifically, this Research Topic includes 23 original articles, 5 reviews and 4 case reports, which can be regrouped into four different thematic sections: 1) Predictive tools of response to therapies; 2) Diagnostic and prognostic biomarkers; 3) Diagnostic models based on imaging data; 4) Tailored therapeutic strategies. We will briefly revise the most significant contributions.
Predictive tools of response to therapies
The first section consists of two original research articles focusing on predictive tools of BC response to oncological treatments.
The importance of achieving a pathological complete response (pCR) and the possibility of adjusting therapies is the Research Topic of the work by Xu et al. in which they identified “Volume change rate” (δV) as a good quantitative efficacy evaluation index to monitor the therapeutic effect of neoadjuvant chemotherapy (NAC) and to predict pCR, to guide the adjustment of individualized NAC regimen. Tashireva et al. conducted a study on a limited cohort of triple-negative breast cancer (TNBC) patients treated with eribulin. They successfully identified immunological predictive markers, including tumor-infiltrating lymphocytes, CD8+, CD4+, FoxP3+, CD20+ lymphocytes, and their PD1 positivity or negativity, associated with treatment response; these findings are consistent with the existing immunomodulant effect of eribulin in addition to its antimitotic effect.
Diagnostic and prognostic biomarkers
The second section features studies investigating novel clinical or biological markers playing a critical role in the early diagnosis and prognostic assessment of BC, for a more personalized patients care.
The first two articles in this section highlighted the challenge of testing new biomarkers in blood samples.
Zhang et al. focused on the possible role of carnitine compounds in BC development and progression, and in a 1:1 age-matched retrospective case-control study identified increased butyrylcarnitine (C4) levels in whole blood as a risk factor for the disease. The review by Yi et al. is a comprehensive overview regarding small extracellular vesicles (sEVs) and their involvement in BC pathogenesis: the significant role of sEVs in facilitating intracellular communication through the transportation of a variety of biomolecules, with regard to their use as liquid biopsy biomarkers for both the diagnosis and prognosis of BC. Moving on to genomic and transcriptomic techniques, by integrating data of almost 3000 BC patients collected in public database Fan et al. identified a total of 15 hub genes associated with BC long-term survival. Song et al. investigated the role of small nucleolar RNAs (snoRNAs) in tumor development. Their original article, in which they analyzed public database and 77 BC patients’ biopsies, showed a significant up-regulation of SNORA38 and its correlation with tumor size, lymph-node metastasis, and TNM stage. SNORA38 seems to have a relevant carcinogenic role in BC and it was ultimately suggested as a potential prognostic biomarker. Moreover, interestingly, Huang et al. provided a comprehensive analysis of the oncogenic roles of the myelin protein zero-like 3 (MPZL3) pan-cancer gene across different tumors, and its potential role as a prognostic biomarker and therapeutic target for BC.
The importance of the immune system in controlling cancer development, treatment responses and long-term survival of cancer patients by manipulating immune response with several therapeutic immunotherapeutic strategies has already been established or under intensive investigation (13–15); consequently, numerous researchers have directed their efforts toward investigating immune-related genes in the pursuit of developing reliable predictive models for immunotherapy outcomes and patients prognosis. On this Research Topic of Tian et al., Yang et al. and Liu et al. developed prognostic models based on different immune-related genes, which seem to be promising in effectively assist clinicians with medical diagnoses, evaluating patient prognosis and formulating diverse treatment strategies. Moreover, Zhang et al. attempted to assess the immunological and prognostic significance of the V-domain Ig-containing suppressor of T cell activation (VISTA), a crucial immune checkpoint protein, in patients with TNBC. They found that VISTA exhibited a significant correlation with favorable prognosis and increased immune infiltration in TNBC patients. Fan et al. explored the potential connection between molecular subtypes and the preferential distant metastasis sites among BC patients, providing an example of how precision medicine may guide decisions related to surveillance and the development of tailored screening and cancer management strategies for personalized follow-up. Similarly, Cai et al. endeavored to identify high-risk factors for HER2-positive BC patients who would likely develop brain metastasis, a novel approach to support clinicians during the follow-up.
When striving to provide a precision medicine-based treatments, it is imperative to merge it with the clinical and pharmacological anamnesis of the patient. Recent studies have shown a connection between body composition and the prognosis of BC patients. In this context, Liu et al.‘s retrospective study illustrates that visceral obesity is linked to a greater risk of disease recurrence in a Chinese cohort, consistently supporting some already published literature in non-asian populations (16–19). The authors also found sarcopenia was significantly associated with increased recurrence and overall mortality among patients with BC. This underscored and confirmed the significance of body composition assessment as a simple and useful approach to complement the management of BC.
In the last three notable articles of this section, the authors (Zhu et al., Ma et al.) created novel prognostic nomograms by combining various statistically significant variables in order to enhance accuracy in predicting survival of BC patients. Interestingly, Pu et al. focused on predicting the need of chemotherapy in elderly patients solely using clinicopathological data, irrespective of HR, HER2 status, and lymph-node metastasis, without genomic data, with the advantage of being more easily appliable in resource-limited regions or in elderly patients who do not meet indications for genomic tests.
Diagnostic models based on imaging data
The third section includes three intriguing examples of the role held by imaging techniques in the era of personalized oncology.
Miao et al. evaluated the clinical utility of 68Ga-HER2 affibody PET/CT to non-invasively assess the HER2 expression in BC lesions with uncertain HER2 status, suggesting the potential for this approach to evolve into a personalized “image and treat” strategy for monitoring changes in receptor expression during treatment and optimize therapeutic decisions. Zheng et al. developed and validated a radiomic model based on gray-scale ultrasound and contrast-enhanced ultrasound (GSCEUS) images to effectively differentiate invasive ductal carcinoma from other inflammatory masses, which can help preventing unnecessary biopsies. Sheng et al. showed interesting results from a radiomic machine learning analysis able to integrate the clinical features and the radiomic variables on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to successfully predict distinct molecular subtypes of breast cancer.
Tailored therapeutic strategies
The last section features papers discussing the potential role of precision medicine in providing personalized treatments tailored to the specific characteristics of both the patient and the tumor.
Over the past years, the role of the immune system in cancer development and progression has gained increasing attention. In their review Gianni et al. identify lymphocytic indexes as new potential prognostic and predictive markers for advanced BC treatment, mainly because of their easiness of detection and applicability in daily clinical practice. Moreover, the authors provided an overview of the possible value of systemic inflammatory cells as therapeutic target or vehicle of treatment. The role of immune checkpoint blockade is addressed by Chen et al., who focus their attention on CD47 as novel attractive target for the treatment of BC. An interesting paper by Xia et al. reported four cases of individualized treatment for advanced BC using the patient-derived tumor-like cell cluster (PTC) model, shedding light on the possible role of this experimental model as an efficient tool for drug resistance screening and for selecting personalized treatments. Another compelling example of precision medicine as a strategy for disease treatment was described by López de Sá et al. The authors reported a case of a metastatic BC patient harboring a BRAF V600E mutation that achieved complete response with dabrafenib and trametinib combination. In addition, Wang et al. explored the therapeutic potential of histone deacetylase inhibitors (HDACi) in patients with acquired resistance to endocrine therapy, and Houssiau et al. reported a case of radium-223 treatment in a 59-year-old patient with bone-only metastatic disease. Finally, the role of radiotherapy after BC surgery was explored by Dai et al. and Yang et al. who aimed at developing a nomogram to predict the survival benefit of radiotherapy across various patient groups, with the aim of offering more finely-tailored treatment recommendations.
In summary, this compilation of original articles and reviews provides a valuable insight into prognostic, predictive, diagnostic and therapeutic innovations supporting the implementation of precision medicine in the field of breast cancer treatment. The Editors yearn that the research findings presented in this Research Topic will serve as an inspiration for scientists and clinicians and support the development of clinical trials and breast cancer research, thereby promoting ongoing advancements in personalized care for BC patients in the years to come.
Author contributions
DF: Writing – original draft. DG: Conceptualization, Supervision, Writing – review & editing. FS: Conceptualization, Supervision, Writing – review & editing.
Funding
The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
Acknowledgments
FS is supported by a Rio Hortega clinical scientist contract from the Instituto de Salud Carlos III (ISCIII). Opinions and hypotheses generated are solely of the article’s authors.
Conflict of interest
FS reports honoraria from Novartis, Gilead and Daiichy-Sankyo for educational events/materials, advisory role for Pfizer and travel expenses from Novartis, Gilead and Daiichy-Sankyo. DG declares personal fees for educational events by Novartis, Lilly, Pfizer, Daiichy-Sankyo, Roche; research funds from Astrazeneca, Novartis and LILT.
The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
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References
1. Schettini F, Brasó-Maristany F, Kuderer NM, Prat A. A perspective on the development and lack of interchangeability of the breast cancer intrinsic subtypes. NPJ Breast Cancer (2022) 8:85. doi: 10.1038/s41523-022-00451-9
2. SEER statistics for breast cancer. Available at: https://seer.cancer.gov (Accessed July 25, 2021).
3. Mosele F, Remon J, Mateo J, Westphalen CB, Barlesi F, Lolkema MP, et al. Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: a report from the ESMO Precision Medicine Working Group. Ann Oncol (2020) 31:1491–505. doi: 10.1016/j.annonc.2020.07.014
4. Burstein HJ, Curigliano G, Thürlimann B, Weber WP, Poortmans P, Regan MM, et al. Customizing local and systemic therapies for women with early breast cancer: the St. Gallen International Consensus Guidelines for treatment of early breast cancer 2021. Ann Oncol (2021) 32:1216–35. doi: 10.1016/j.annonc.2021.06.023
5. Prat A, Guarneri V, Pascual T, Brasó-Maristany F, Sanfeliu E, Paré L, et al. Development and validation of the new HER2DX assay for predicting pathological response and survival outcome in early-stage HER2-positive breast cancer. EBioMedicine (2022) 75:103801. doi: 10.1016/j.ebiom.2021.103801
6. Falato C, Schettini F, Pascual T, Brasó-Maristany F, Prat A. Clinical implications of the intrinsic molecular subtypes in hormone receptor-positive and HER2-negative metastatic breast cancer. Cancer Treat Rev (2023) 112:102496. doi: 10.1016/j.ctrv.2022.102496
7. Schettini F, Martínez-Sáez O, Falato C, De Santo I, Conte B, Garcia-Fructuoso I, et al. Prognostic value of intrinsic subtypes in hormone-receptor-positive metastatic breast cancer: systematic review and meta-analysis. ESMO Open (2023) 8:101214. doi: 10.1016/j.esmoop.2023.101214
8. Schettini F, Seguí E, Conte B, Sanfeliu E, Gonzalez-Farre B, Jares P, et al. Intrinsic subtypes and therapeutic decision-making in hormone receptor-positive/HER2-negative metastatic breast cancer with visceral crisis: A case report. Front Oncol (2022) 12:1009352. doi: 10.3389/fonc.2022.1009352
9. Drilon A, Laetsch TW, Kummar S, DuBois SG, Lassen UN, Demetri GD, et al. Efficacy of larotrectinib in TRK fusion-positive cancers in adults and children. N Engl J Med (2018) 378:731–9. doi: 10.1056/NEJMoa1714448
10. Doebele RC, Drilon A, Paz-Ares L, Siena S, Shaw AT, Farago AF, et al. Entrectinib in patients with advanced or metastatic NTRK fusion-positive solid tumours: integrated analysis of three phase 1-2 trials. Lancet Oncol (2020) 21:271–82. doi: 10.1016/S1470-2045(19)30691-6
11. Seguí E, Schettini F. Liquid biopsy to tailor the treatment of advanced hormone receptor-positive breast cancer in the era of novel endocrine agents and CDK4/6-inhibitors. Ann Trans Med (2023). Publish Ahead of Print. doi: 10.21037/atm-23-1804
12. Schettini F, Giuliano M, Giudici F, Conte B, De Placido P, Venturini S, et al. Endocrine-based treatments in clinically-relevant subgroups of hormone receptor-positive/HER2-negative metastatic breast cancer: systematic review and meta-analysis. Cancers (Basel) (2021) 13:1458. doi: 10.3390/cancers13061458
13. Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discovery (2022) 12:31–46. doi: 10.1158/2159-8290.CD-21-1059
14. Garcia-Corbacho J, Indacochea A, González Navarro A, Victoria I, Moreno D, Pesántez D, et al. Determinants of activity and efficacy of anti-PD1/PD-L1 therapy in patients with advanced solid tumors recruited in a clinical trials unit: a longitudinal prospective biomarker-based study. Cancer Immunology Immunotherapy (2023). doi: 10.1007/s00262-022-03360-9. ahead of print.
15. Schettini F, Barbao P, Brasó-Maristany F, Galván P, Martínez D, Paré L, et al. Identification of cell surface targets for CAR-T cell therapies and antibody-drug conjugates in breast cancer. ESMO Open (2021) 6:100102. doi: 10.1016/j.esmoop.2021.100102
16. Harborg S, Cronin-Fenton D, Jensen M-BR, Ahern TP, Ewertz M, Borgquist S. Obesity and risk of recurrence in patients with breast cancer treated with aromatase inhibitors. JAMA Netw Open (2023) 6:e2337780. doi: 10.1001/jamanetworkopen.2023.37780
17. Acevedo F, Walbaum B, Muñiz S, Petric M, Martínez R, Guerra C, et al. Obesity is associated with early recurrence on breast cancer patients that achieved pathological complete response to neoadjuvant chemotherapy. Sci Rep (2022) 12:21145. doi: 10.1038/s41598-022-25043-2
18. Buono G, Crispo A, Giuliano M, De Angelis C, Schettini F, Forestieri V, et al. Combined effect of obesity and diabetes on early breast cancer outcome: a prospective observational study. Oncotarget (2017) 8:115709–17. doi: 10.18632/oncotarget.22977
Keywords: breast cancer, prognosis, prediction, biomarker, precision oncology
Citation: Favero D, Generali D and Schettini F (2023) Editorial: Diagnostic, prognostic and predictive factors of response in the era of precision oncology in breast cancer. Front. Oncol. 13:1337315. doi: 10.3389/fonc.2023.1337315
Received: 12 November 2023; Accepted: 17 November 2023;
Published: 23 November 2023.
Edited and Reviewed by:
Tao Liu, University of New South Wales, AustraliaCopyright © 2023 Favero, Generali and Schettini. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Francesco Schettini, schettini@recerca.clinic.cat