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Čelešnik, H.; Potočnik, U. Tissue- and Blood-Based mRNA Tests in Breast Cancer. Encyclopedia. Available online: https://encyclopedia.pub/entry/41204 (accessed on 16 October 2024).
Čelešnik H, Potočnik U. Tissue- and Blood-Based mRNA Tests in Breast Cancer. Encyclopedia. Available at: https://encyclopedia.pub/entry/41204. Accessed October 16, 2024.
Čelešnik, Helena, Uroš Potočnik. "Tissue- and Blood-Based mRNA Tests in Breast Cancer" Encyclopedia, https://encyclopedia.pub/entry/41204 (accessed October 16, 2024).
Čelešnik, H., & Potočnik, U. (2023, February 14). Tissue- and Blood-Based mRNA Tests in Breast Cancer. In Encyclopedia. https://encyclopedia.pub/entry/41204
Čelešnik, Helena and Uroš Potočnik. "Tissue- and Blood-Based mRNA Tests in Breast Cancer." Encyclopedia. Web. 14 February, 2023.
Tissue- and Blood-Based mRNA Tests in Breast Cancer
Edit

Molecular diagnostic tests help clinicians understand the underlying biological mechanisms of their patients’ breast cancer (BC) and facilitate clinical management. Several tissue-based mRNA tests are used routinely in clinical practice, particularly for assessing the BC recurrence risk, which can guide treatment decisions. Blood-based mRNA assays have only recently started to emerge.

breast cancer peripheral blood diagnostic assay mRNA test transcriptome early detection cancer screening

1. Introduction

Breast cancer (BC) is the most diagnosed cancer in women, and among the leading causes of cancer mortality. It is estimated that over 86,000 European women will die of this disease in 2022 [1][2]. BC is a heterogeneous cancer comprised of distinct subtypes with specific pathological characteristics and clinical implications. Based on the expression of the estrogen receptor (ER), progesterone receptor (PR), and the amplification of the HER2 (ERBB2) receptor, BC is categorised into four clinical subtypes: hormone receptor (HR)-positive (ER+/PR+/HER2−), triple positive (ER+/PR+/HER2+), HER2-positive (ER−/PR−/HER2+), and triple-negative breast cancer (TNBC) (ER−/PR−/HER2−, also HR−/HER2−) [3][4]. This classification is clinically important, because it helps to assess cancer prognosis, and, in company with other traditional prognostic and predictive factors, select an appropriate treatment strategy. ER-positive tumours respond to drugs that target the ER pathway, such as the selective ER modulators and ER degraders (tamoxifen, fulvestrant) or aromatase inhibitors (letrozole, anastrozole, exemestane) [5]. Tumours with HER2 amplification respond to anti-HER2 therapies (i.e., monoclonal antibodies targeting HER2, such as trastuzumab and pertuzumab) [6]. However, TNBC does not express ER, PR, and lacks HER2 amplification, and therefore targeted therapies are lacking for this subtype, since targeted therapies are commonly aimed at these receptors. Consequently, TNBC represents a major clinical challenge, and is associated with a poor prognosis connected with metastasis, post-treatment relapse, and reduced survival. While the standard treatment for TNBC involves chemotherapy, new immunotherapy options have become available in recent years [7][8]. One important characteristic of TNBC is its high mutational burden [9][10], which is associated with tumour immunogenicity, and may aid in the selection of TNBC patients likely to benefit from certain immunotherapies [11]. Treatment decisions for this heterogeneous cancer may also be guided by RNA-based molecular subtyping. The web-based TNBCtype algorithm was developed as an online tool to distinguish six TNBC subtypes with different biological characteristics and therapy options [12][13].
In addition to the clinical subtyping of BC, a detailed molecular characterisation of BC tissues, which employed DNA analyses (DNA mutations, copy number, DNA methylation), mRNA profiling and protein expression of tumour tissues, has led to the classification of four molecular/intrinsic BC subtypes with different prognoses and survival: Luminal A (ER+/PR+/HER2−, low proliferation factor Ki67+, low grade), Luminal B (ER+/PR±/HER2±, high Ki67+ (≥14%), high grade), HER2-enriched (ER−/PR−/HER2+, high proliferation, any Ki67 level), and basal-like (ER−/PR−/HER2−, high proliferation, any Ki67 level, high grade, necrosis) [3][14]. Intrinsic and clinical subtypes overlap to some degree, but not completely. For instance, basal-like breast cancers are mostly enriched in TNBC. However, about 21% of TNBCs are not basal-like [15].

2. Molecular Diagnostic Tests and Companion Diagnostic Devices for Breast Cancer Approved by the US Food and Drug Administration (FDA)

The diagnostic tests available for BC are intended to detect variations in DNA sequence, analyse RNA profiles, or measure protein expression, in order to determine the genetic carrier status, classify BC and its subtypes, detect cancer spreading, facilitate prognosis, and/or assess recurrence risk. In clinical care, a number of nucleic acid-based tests have been adopted for BC in recent years. Some of them have been cleared or approved by the FDA [16]. These include multigene expression assays, tests for variant detection in BRCA1, BRCA2, PIK3CA, and Topoisomerase II Alpha genes, and assays for determination of HER2 status. In addition, a number of companion diagnostic devices for BC have been approved by the FDA [16]. These are in vitro diagnostic (IVD) devices and imaging tools that provide information needed for the safe and effective use of corresponding therapeutics. For BC, FDA-approved IVD devices include testing for BRCA 1, BRCA2, and PIK3CA mutations, HER2 gene amplification, and protein expression of HER-2, PD-L1, and Ki67. These DNA and protein-level tests facilitate decisions on therapy with Herceptin, Kadcyla, Perjeta, Lynparza, Talzenna, Piqray, Verzenio, and Keytruda. Some tests are classified both as a nucleic acid-based test and IVDs.

3. Cancer Diagnostics Based on mRNA Can Offer Prognostically Useful Information beyond DNA Variation

Messenger RNA diagnostics are able to provide important information that cannot be learned directly from mutation data [17]. For instance, although evaluating a predisposition to hereditary cancer using DNA genetic testing is becoming widespread, it can often be challenging to interpret the detected variants accurately, especially when DNA alterations are predicted to impact splicing. In these cases, the variants are frequently classified as uncertain, or likely pathogenic. However, RNA testing can help interpret the impact of these changes by enabling their classification as pathogenic/clinically actionable or benign [18], thereby informing clinical decisions. According to Karam et al., blood RNA testing provided as a supplement to DNA genetic testing has the potential to affect medical management in at least 1 in 43 patients [18].
Additionally, although hereditary BC risk has been linked to highly penetrant genetic variants, many of their carriers never develop BC, and many BC patients do not carry these variants [19][20]. This can create uncertainty for both the patients and the physicians when it comes to making decisions whether to pursue aggressive prevention strategies (e.g., prophylactic surgery, chemopreventive intervention). To get a more accurate assessment of individual risk, examining gene-expression patterns can make it easier to differentiate individuals from high-risk families who are likely to develop BC from those who are not [21]. This way, women who carry known susceptibility variants can be assigned different individual risks based on their gene expression profiles, which may facilitate personalised prevention decisions [21].
The clinical contribution of mRNA testing beyond that of DNA becomes particularly apparent in early-stage BC diagnosis and assessment of BC recurrence risk, which can guide treatment decisions [17]. For example, the 21-gene expression tissue assay Oncotype DX can identify pathway changes on a very detailed level, and predict recurrence within the HR-positive BC more precisely than any DNA-based assay [17][22]. While genomic mutations can lead to changes in the downstream pathways, there may be several intermediate steps between the driver mutations and the disease phenotype. However, distinct expression patterns that can result from the driver mutations can be identified easily by examining the mRNA levels. Consequently, mRNA analysis can be more informative than analysis of genomic variation.
While several tissue-based mRNA assays are used and/or FDA-approved, only a few blood-based mRNA tests (described below) are commercially available, and none have so far been approved by the FDA. Additionally, none of the current FDA-approved companion devices for BC are based on mRNA detection, either in blood or in tissues.

4. Tissue-Based mRNA Expression Assays for Breast Cancer

Tissue gene expression assays investigate the patterns of a selected number of different genes in cancer cells obtained during surgery or biopsy, to help inform clinical decisions (Table 1). For instance, several multigene prognostic assays (e.g., Oncotype DX, Prosigna, EndoPredict), enable estimation of the residual risk of recurrence following surgery. This can guide clinical decisions, such as whether chemotherapy or other treatments are needed to reduce risk after surgery. Consequently, this can facilitate safe avoidance of patient over-treatment.

4.1. Prosigna Breast Cancer Prognostic Gene Signature Assay (Formerly Called the PAM50 Test)

Prosigna (Veracyte, San Francisco, CA) is an FDA-approved test that uses a 50-gene expression profile of BC tumour tissue to inform prognostic, recurrence and therapeutic management of BC [23][24][25][26]. It is intended for post-menopausal women with stage I or II, lymph node (LN) negative or positive (1–3 positive LNs), hormone-receptor (HR)-positive BC, with a tumour size of <5.0 cm. Prosigna can help assign BC to one of four intrinsic subtypes and provide a risk assessment for distant recurrence at ten years. The results of this test, together with other clinical information, can be used by physicians for assessing the recurrence risk. Based on the low, intermediate or high risk of distant recurrence, physicians can decide if patients can safely avoid adjuvant chemotherapy [25][27].

4.2. MammaPrint Test (also Called the 70-Gene Signature)

MammaPrint (Agendia, Inc., Amsterdam, The Netherlands) is an FDA-cleared prognostic assay, which analyses the expression of 70 genes to help predict if BC will spread to other parts of the body or return [28][29][30]. Based on the calculated recurrence score, women are categorised into a high or low risk group, which can guide decisions on adjuvant endocrine and chemotherapy [28][31]. MammaPrint is performed on fresh or preserved tissues from biopsy or surgery, and is intended for early-stage invasive HR-positive or HR-negative, stage I or II cancers, smaller than 5.0 cm, present in three or fewer lymph nodes [32]. It can be integrated into diagnostic workups for quicker, more informed decisions on pre- and post-operative treatment. BluePrint, another assay by Agendia, Inc., is a molecular classification system that analyses 80 genes to identify the underlying biology of individual breast cancers. It enables BC subtyping into luminal type (luminal A or luminal B), HER2-type, and basal-like type. This classification reveals valuable information about long-term prognosis and response to systemic therapy, and can enable patient selection for either chemotherapy or endocrine treatment [33].

4.3. Oncotype DX Breast Recurrence Score Test

Oncotype DX (Genomic Health, Redwood City, CA, USA) [34] is a gene expression profiling assay intended for HR+/HER2− BC, stage I, II or IIIa, LN-negative, or up to three positive LNs. It analyses the expression of 21 genes in cancer cells obtained by biopsy or surgery, and helps assess the risk of BC recurrence. The calculated recurrence score enables an individualised estimate of 9-year distant recurrence risk and the likelihood of adjuvant chemotherapy benefit [35][36]. Oncotype DX became commercially available in 2004, and, as a laboratory-developed test, did not require FDA-approval [37]. The assay is included in international treatment guidelines, and is performed at a CLIA-certified central laboratory in the USA. It has been validated extensively in clinical studies. A large adjuvant BC treatment clinical trial (TAILORx, NCT00310180), which included 10,253 patients worldwide, demonstrated that, by using Oncotype DX, it is possible to identify BC patients who may not need chemotherapy to increase their chance of survival [37][38][39][40][41].

4.4. Breast Cancer Index, BCI

BCI (Biotheranostics, Inc., San Diego, CA, USA) is a predictive multi-gene expression assay that incorporates: (1) the HOXB13:IL17BR ratio, which is associated with tumour responsiveness to endocrine therapy; and (2) the molecular grade index, which is associated with tumour proliferation, and is based on the average expression of five cell cycle-associated genes [42][43]. BCI helps to predict the risk of early-stage HR+ BC coming back 5 to 10 years after diagnosis. According to the American Society of Clinical Oncology (ASCO) guidelines and NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®), this assay can also help physicians decide if extending hormonal therapy in patients with HR+/HER2−, LN-negative or LN-positive (1–3 nodes) BC beyond five years (for a total of 10 years) would be beneficial [31]. The clinical validation and the indication of prognostic utility for this molecular signature was provided by the TransATAC and the Stockholm trials [42][44].

4.5. EndoPredict Breast Cancer Prognostic Test

EndoPredict (Myriad Genetics, Salt Lake City, UT, USA) is a gene expression test for patients with early-stage, ER+/HER2− BC. It analyses 12 genes related to tumour proliferation and hormone receptor activity. It calculates a risk score, which can be used together with clinical pathological factors (such as tumour size and nodal status) to guide treatment decisions for chemotherapy and extended endocrine therapy [45][46]. It enables prediction of early and up to 15 years distant recurrence (metastatic disease) [47][48][49]. It has been validated clinically in both post- and pre-menopausal patients [50][51]. By using EndoPredict, it was possible to identify 65% of premenopausal patients with low-risk disease who could safely forgo adjuvant chemotherapy (independent from nodal status) [51].

4.6. GeneSearch Breast Lymph Node (BLN) Test Kit

GeneSearch BLN (Veridex, LLC., Raritan, NJ, USA) is an FDA-approved gene expression test for patients with invasive BC, intended to detect whether BC cells have spread to lymph nodes under the arm [52]. The assessment is based on the analysis of two gene expression markers, mammaglobin (MG) and cytokeratin 19 (CK19) in lymph node(s) removed during surgery. These mRNA markers are expressed at high levels in breast tissue, but only at low levels in normal lymph node tissue (i.e., cell-type-specific mRNAs) [53][54][55][56]. Metastases greater than 0.2 mm can be detected by the BLN Test in nodal tissue removed from sentinel lymph node biopsies, and the assay results can be used to guide the decision to remove additional lymph nodes [52].
Table 1. Tissue mRNA-level diagnostic tests for breast cancer.

5. The Advantages of Using Peripheral Blood (i.e., a Blood-Based Liquid Biopsy) for Cancer Diagnostics

Cancer biomarker research has concentrated largely on the molecular characteristics of tumour cells, and on immune responses in the tumour microenvironment, leading to the emergence of tissue-based diagnostic assays. However, focusing on blood biomarkers has many advantages for cancer screening, diagnosis, monitoring, and prognosis.
First, drawing peripheral blood offers simple, cost-effective and minimally invasive sampling. Additionally, it is well known that patient survival rates are greatly increased if cancer is identified at its early stages [62], and several lines of evidence indicate that analysing blood allows the detection of very early systemic changes, which is crucial for cancer screening [63][64][65][66]. On the other hand, biopsies may not be appropriate for cancer screening, and may deter healthy people with no symptoms [67]. Currently, almost 50% of cancers are diagnosed at the later stages, when the symptoms begin to manifest. At that time, the disease outcomes are poorer and the treatments more expensive [68]. The less invasive blood sampling may make early cancer detection and accompanying medical intervention more feasible. A liquid biopsy may also offer advantages compared to the existing imaging methods. About half of women have dense breast tissue, which is associated with reduced sensitivity on mammography [69]. Additionally, the tumour has to reach a certain size to be detectable by imaging [70]. Moreover, although close to 20% of patients with invasive BC are women under 50, in some countries, women in this age group are not typically referred for mammography screenings [71]. A liquid biopsy could represent a solution to these issues.
Although repeated tissue biopsies can be useful in clinical practice to help monitor how the tumour evolves, tissue collection comes with risk of complications [66]. It may also provide insufficient material, and can have selection bias due to tumour heterogeneity (e.g., single-site tissue biopsies may give only a snapshot of the tumour) [72]. In contrast, peripheral blood is readily available, and not prone to selection bias or heterogeneity problems.
Since blood testing has the potential to circumvent all the above-mentioned disadvantages of biopsies and imaging, liquid biopsy has been gaining considerable interest in BC precision medicine. A variety of biomarkers with clinically useful information can be detected in blood, such as circulating tumour cells (CTCs), circulating tumour-derived material (e.g., circulating tumour DNA—ctDNA), extracellular vesicles, cell-free microRNAs (cfmiRNAs), methylation markers, and others. These have been reviewed in several excellent papers, e.g., [73][74][75][76][77]. Here, the researchers will focus on mRNA biomarkers from peripheral blood cells and their use in cancer diagnostics.

6. Research Focusing on BC-Specific Transcriptional Profiles in Peripheral Blood Has Established Their Diagnostic and Prognostic Value

During cancer, the proportion of effector and regulatory immune cells and their gene expression profiles change in the tumour microenvironment. Similar immune changes can be detected in peripheral blood cells, since the circulatory system participates in physiological and pathological activities throughout the body [78][79]. Tumours release a variety of signalling molecules that are detected by the circulating blood cells. These respond with phenotypic and functional changes that enable them to modulate the cancer’s progression. This can result either in the killing of tumour cells and cancer rejection, or the promotion of cancer proliferation and spreading [80][81][82].
In recent years, high-throughput transcriptomic studies have revealed meaningful differences in peripheral blood cells between BC and healthy subjects, and within BC patient subpopulations. Specific transcriptome changes have been identified with clinical utility for BC patients, indicating a clear potential for liquid biopsy and the development of blood-based messenger RNA diagnostic tests [83][84][85].

7. Commercially Available Blood-Based mRNA Tests for Breast Cancer

Currently, blood analysis in clinical management of BC is aimed mostly at detecting DNA-level and protein-level biomarkers. Examples include the BRCA1 and BRCA2 genes, which are the classical blood-based biomarkers for genetic screening of individuals with hereditary BC susceptibility [86]. Other blood BC biomarkers include proteins that can help assess disease progression, predict recurrence, and facilitate the monitoring of treatment response, such as carcinoembryonic antigen (CEA), gene products of MUC1 (e.g., cancer antigen (CA) 15-3 and CA 27.29), circulating cytokeratins, and serum HER2 [87][88].
However, recent years have brought a gradual emergence of mRNA-level blood diagnostics, with new mRNA assays finding their way increasingly into the clinical setting (Table 2). As detailed below, these blood tests can facilitate healthcare decisions in several ways; by supplementing hereditary DNA-testing for better diagnostic outcome (i.e., helping to classify DNA variants) (+RNAinsight), by enabling early BC detection (Syantra DX Breast Cancer, BCtect), and by facilitating simultaneous screening of several cancers (multi-cancer blood test Aristotle).
Table 2. Commercially available blood mRNA-level diagnostic tests for breast cancer.

Assay Trade Name (Manufacturer)

Number of Genes

Assay Indicated for

Description

Methodology/

Platform

References

+RNAinsight (Ambry Genetics)

Up to 91 genes (for maximum coverage)

Assessing hereditary cancer predisposition

+RNAinsight analyses functional RNA data to classify DNA variants and identify deep-intronic mutations;

intended for paired RNA/DNA analyses, as a supplement to Ambry Genetics DNA-level hereditary cancer panels CancerNext, CancerNext-Expanded, CustomNext-Cancer.

RNA sequencing

[89]

Syantra DX Breast Cancer (Syantra Inc.)

12-gene multi-biomarker panel

Breast cancer screening for women aged 25–80

Enables classification of a sample as positive or negative for BC signature;

demonstrated utility for early cancer screening, for women with high breast density, and for women under 50.

qRT-PCR-based assay

[90][91]

Multi-cancer blood test Aristotle (Stage Zero Life Sciences Ltd.)

Multi-biomarker panel

Pan-cancer screening (breast, bladder, colorectum, cervix, endometrium, liver, ovary, prostate, and stomach)

Enables detection of multiple cancer molecular signatures from a single blood sample (early cancer detection).

Microarray-based assay

[92]

BCtect (DiaGenic ASA)

96-assay signature

Breast cancer screening

Enables classification of a sample as positive or negative for BC signature;

utility for early BC detection in both pre- and post-menopausal women, and across cancer stages and types.

qRT-PCR-based assay

[93][94][95]

References

  1. Dalmartello, M.; La Vecchia, C.; Bertuccio, P.; Boffetta, P.; Levi, F.; Negri, E.; Malvezzi, M. European cancer mortality predictions for the year 2022 with focus on ovarian cancer. Ann Oncol. 2022, 33, 330–339.
  2. International Agency for Research on Cancer, WHO. Cancer Today. 2022. Available online: https://gco.iarc.fr/today/home. (accessed on 19 October 2022).
  3. Szymiczek, A.; Lone, A.; Akbari, M.R. Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review. Clin. Genet. 2021, 99, 613–637.
  4. Čelešnik, H.; Potočnik, U. Peripheral Blood Transcriptome in Breast Cancer Patients as a Source of Less Invasive Immune Biomarkers for Personalized Medicine, and Implications for Triple Negative Breast Cancer. Cancers 2022, 14, 591.
  5. McAndrew, N.P.; Finn, R.S. Clinical Review on the Management of Hormone Receptor-Positive Metastatic Breast Cancer. JCO Oncol. Pract. 2022, 18, 319–327.
  6. Ferrario, C.; Christofides, A.; Joy, A.A.; Laing, K.; Gelmon, K.; Brezden-Masley, C. Novel Therapies for the Treatment of HER2-Positive Advanced Breast Cancer: A Canadian Perspective. Curr. Oncol. 2022, 29, 2720–2734.
  7. Bianchini, G.; De Angelis, C.; Licata, L.; Gianni, L. Treatment landscape of triple-negative breast cancer—expanded options, evolving needs. Nat. Rev. Clin. Oncol. 2022, 19, 91–113.
  8. Čelešnik, H.S.; Potočnik, U. Immunotherapy in Breast Cancer. In: Encyclopedia. Available online: https://encyclopedia.pub/entry/21561 (accessed on 27 November 2022).
  9. Skok, K.; Gradišnik, L.; Čelešnik, H.; Milojević, M.; Potočnik, U.; Jezernik, G.; Gorenjak, M.; Sobočan, M.; Takač, I.; Kavalar, R.; et al. MFUM-BrTNBC-1, a Newly Established Patient-Derived Triple-Negative Breast Cancer Cell Line: Molecular Characterisation, Genetic Stability, and Comprehensive Comparison with Commercial Breast Cancer Cell Lines. Cells 2021, 11, 117.
  10. Skok, K.; Gradišnik, L.; Čelešnik, H.; Potočnik, U.; Kavalar, R.; Takač, I.; Maver, U. Isolation and characterization of the first Slovenian human triple-negative breast cancer cell line. Breast J. 2020, 26, 328–330.
  11. O’Meara, T.A.; Tolaney, S.M. Tumor mutational burden as a predictor of immunotherapy response in breast cancer. Oncotarget. 2021, 12, 394–400.
  12. Chen, X.; Li, J.; Gray, W.H.; Lehmann, B.D.; Bauer, J.A.; Shyr, Y.; Pietenpol, J.A. TNBCtype: A Subtyping Tool for Triple-Negative Breast Cancer. Cancer Inform. 2012, 11, 147–156.
  13. Hartung, C.; Porsch, M.; Stückrath, K.; Kaufhold, S.; Staege, M.S.; Hanf, V.; Lantzsch, T.; Uleer, C.; Peschel, S.; John, J.; et al. Identifying High-Risk. Triple-Negative Breast Cancer Patients by Molecular Subtyping. Breast Care 2021, 16, 637–647.
  14. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 2012, 490, 61–70.
  15. Prat, A.; Adamo, B.; Cheang, M.C.; Anders, C.K.; Carey, L.A.; Perou, C.M. Molecular characterization of basal-like and non-basal-like triple-negative breast cancer. Oncologist 2013, 18, 123–133.
  16. U.S. Food & Drug Administration, FDA. 2022. Available online: www.fda.gov (accessed on 20 October 2022).
  17. Ravkin, H.D.; Givton, O.; Geffen, D.B.; Rubin, E. Direct comparison shows that mRNA-based diagnostics incorporate information which cannot be learned directly from genomic mutations. BMC Bioinform. 2020, 21, 196.
  18. Karam, R.; Conner, B.; LaDuca, H.; McGoldrick, K.; Krempely, K.; Richardson, M.E.; Zimmermann, H.; Gutierrez, S.; Reineke, P.; Hoang, L.; et al. Assessment of Diagnostic Outcomes of RNA Genetic Testing for Hereditary Cancer. JAMA Netw. Open 2019, 2, e1913900.
  19. Chen, S.; Parmigiani, G. Meta-analysis of BRCA1 and BRCA2 penetrance. J. Clin. Oncol. 2007, 25, 1329–1333.
  20. Vietri, M.T.; Caliendo, G.; Casamassimi, A.; Cioffi, M.; De Paola, M.L.; Napoli, C.; Molinari, A.M. A novel PALB2 truncating mutation in an Italian family with male breast cancer. Oncol. Rep. 2015, 33, 1243–1247.
  21. Piccolo, S.R.; Andrulis, I.L.; Cohen, A.L.; Conner, T.; Moos, P.J.; Spira, A.E.; Buys, S.S.; Johnson, W.E.; Bild, A.H. Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility. BMC Med. Genomics. 2015, 8, 72.
  22. Schaafsma, E.; Zhang, B.; Schaafsma, M.; Tong, C.Y.; Zhang, L.; Cheng, C. Impact of Oncotype DX testing on ER+ breast cancer treatment and survival in the first decade of use. Breast Cancer Res. 2021, 23, 74.
  23. Martín, M.; González-Rivera, M.; Morales, S.; de la Haba-Rodriguez, J.; González-Cortijo, L.; Manso, L.; Albanell, J.; González-Martín, A.; González, S.; Arcusa, A.; et al. Prospective study of the impact of the Prosigna assay on adjuvant clinical decision-making in unselected patients with estrogen receptor positive, human epidermal growth factor receptor negative, node negative early-stage breast cancer. Curr. Med. Res. Opin. 2015, 31, 1129–1137.
  24. Dowsett, M.; Sestak, I.; Lopez-Knowles, E.; Sidhu, K.; Dunbier, A.K.; Cowens, J.W.; Ferree, S.; Storhoff, J.; Schaper, C.; Cuzick, J. Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J. Clin. Oncol. 2013, 31, 2783–2790.
  25. Gnant, M.; Filipits, M.; Greil, R.; Stoeger, H.; Rudas, M.; Bago-Horvath, Z.; Mlineritsch, B.; Kwasny, W.; Knauer, M.; Singer, C.; et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: Using the PAM50 Risk of Recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann. Oncol. 2014, 25, 339–345.
  26. Veracyte. Prosigna Breast Cancer Assay. 2022. Available online: https://www.prosigna.com/ (accessed on 26 October 2022).
  27. Lænkholm, A.V.; Jensen, M.B.; Eriksen, J.O.; Rasmussen, B.B.; Knoop, A.S.; Buckingham, W.; Ferree, S.; Schaper, C.; Nielsen, T.O.; Haffner, T.; et al. PAM50 Risk of Recurrence Score Predicts 10-Year Distant Recurrence in a Comprehensive Danish Cohort of Postmenopausal Women Allocated to 5 Years of Endocrine Therapy for Hormone Receptor-Positive Early Breast Cancer. J. Clin. Oncol. 2018, 36, 735–740.
  28. Soliman, H.; Shah, V.; Srkalovic, G.; Mahtani, R.; Levine, E.; Mavromatis, B.; Srinivasiah, J.; Kassar, M.; Gabordi, R.; Qamar, R.; et al. MammaPrint guides treatment decisions in breast Cancer: Results of the IMPACt trial. BMC Cancer 2020, 20, 81.
  29. van de Vijver, M.J.; He, Y.D.; van’t Veer, L.J.; Dai, H.; Hart, A.A.; Voskuil, D.W.; Schreiber, G.J.; Peterse, J.L.; Roberts, C.; Marton, M.J.; et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 2002, 347, 1999–2009.
  30. Cardoso, F.; van’t Veer, L.J.; Bogaerts, J.; Slaets, L.; Viale, G.; Delaloge, S.; Pierga, J.Y.; Brain, E.; Causeret, S.; DeLorenzi, M.; et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N. Engl. J. Med. 2016, 375, 717–729.
  31. Andre, F.; Ismaila, N.; Allison, K.H.; Barlow, W.E.; Collyar, D.E.; Damodaran, S.; Henry, N.L.; Jhaveri, K.; Kalinsky, K.; Kuderer, N.M.; et al. Biomarkers for Adjuvant Endocrine and Chemotherapy in Early-Stage Breast Cancer: ASCO Guideline Update. J. Clin. Oncol. 2022, 40, 1816–1837.
  32. Beumer, I.; Witteveen, A.; Delahaye, L.; Wehkamp, D.; Snel, M.; Dreezen, C.; Zheng, J.; Floore, A.; Brink, G.; Chan, B.; et al. Equivalence of MammaPrint array types in clinical trials and diagnostics. Breast Cancer Res. Treat. 2016, 156, 279–287.
  33. Krijgsman, O.; Roepman, P.; Zwart, W.; Carroll, J.S.; Tian, S.; de Snoo, F.A.; Bender, R.A.; Bernards, R.; Glas, A.M. A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response. Breast Cancer Res. Treat. 2012, 133, 37–47.
  34. Syed, Y.Y. Oncotype DX Breast Recurrence Score®: A Review of its Use in Early-Stage Breast Cancer. Mol. Diagn Ther. 2020, 24, 621–632.
  35. Kalinsky, K.; Barlow, W.E.; Gralow, J.R.; Meric-Bernstam, F.; Albain, K.S.; Hayes, D.F.; Lin, N.U.; Perez, E.A.; Goldstein, L.J.; Chia, S.K.L.; et al. 21-Gene Assay to Inform Chemotherapy Benefit in Node-Positive Breast Cancer. N. Engl. J. Med. 2021, 385, 2336–2347.
  36. Genomic Health. What is the Oncotype DX® Test, and What Makes it Unique? 2022. Available online: https://www.oncotypeiq.com/en-CA/breast-cancer/healthcare-professionals/oncotype-dx-breast-recurrence-score/about-the-test# (accessed on 7 November 2022).
  37. Trosman, J.R.; Van Bebber, S.L.; Phillips, K.A. Coverage policy development for personalized medicine: Private payer perspectives on developing policy for the 21-gene assay. J. Oncol. Pract. 2010, 6, 238–242.
  38. Sparano, J.A.; Gray, R.J.; Makower, D.F.; Pritchard, K.I.; Albain, K.S.; Hayes, D.F.; Geyer, C.E., Jr.; Dees, E.C.; Perez, E.A.; Olson, J.A., Jr.; et al. Prospective Validation of a 21-Gene Expression Assay in Breast Cancer. N. Engl. J. Med. 2015, 373, 2005–2014.
  39. Sparano, J.A.; Gray, R.J.; Makower, D.F.; Pritchard, K.I.; Albain, K.S.; Hayes, D.F.; Geyer, C.E., Jr.; Dees, E.C.; Goetz, M.P.; Olson, J.A., Jr.; et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N. Engl. J. Med. 2018, 379, 111–121.
  40. Sparano, J.A.; Gray, R.J.; Ravdin, P.M.; Makower, D.F.; Pritchard, K.I.; Albain, K.S.; Hayes, D.F.; Geyer, C.E., Jr.; Dees, E.C.; Goetz, M.P.; et al. Clinical and Genomic Risk to Guide the Use of Adjuvant Therapy for Breast Cancer. N. Engl. J. Med. 2019, 380, 2395–2405.
  41. Sparano, J.A.; Gray, R.J.; Makower, D.F.; Albain, K.S.; Saphner, T.J.; Badve, S.S.; Wagner, L.I.; Kaklamani, V.G.; Keane, M.M.; Gomez, H.L.; et al. Clinical Outcomes in Early Breast Cancer with a High 21-Gene Recurrence Score of 26 to 100 Assigned to Adjuvant Chemotherapy Plus Endocrine Therapy: A Secondary Analysis of the TAILORx Randomized Clinical Trial. JAMA Oncol. 2020, 6, 367–374.
  42. Sestak, I.; Zhang, Y.; Sgroi, D.; Schnabel, C.A.; Cuzick, J.M.; Dowsett, M. Residual risk assessment with the Breast Cancer Index (BCI) for prediction of late distant recurrence (DR) in patients from the TransATAC study. J. Clin. Oncol. 2018, 36 (Suppl. S15), 529.
  43. Habel, L.A.; Sakoda, L.C.; Achacoso, N.; Ma, X.J.; Erlander, M.G.; Sgroi, D.C.; Fehrenbacher, L.; Greenberg, D.; Quesenberry, C.P., Jr. HOXB13:IL17BR and molecular grade index and risk of breast cancer death among patients with lymph node-negative invasive disease. Breast Cancer Res. 2013, 15, R24.
  44. Sgroi, D.C.; Sestak, I.; Cuzick, J.; Zhang, Y.; Schnabel, C.A.; Schroeder, B.; Erlander, M.G.; Dunbier, A.; Sidhu, K.; Lopez-Knowles, E.; et al. Prediction of late distant recurrence in patients with oestrogen-receptor-positive breast cancer: A prospective comparison of the breast-cancer index (BCI) assay, 21-gene recurrence score, and IHC4 in the TransATAC study population. Lancet Oncol. 2013, 14, 1067–1076.
  45. Müller, B.M.; Keil, E.; Lehmann, A.; Winzer, K.J.; Richter-Ehrenstein, C.; Prinzler, J.; Bangemann, N.; Reles, A.; Stadie, S.; Schoenegg, W.; et al. The EndoPredict Gene-Expression Assay in Clinical Practice—Performance and Impact on Clinical Decisions. PLoS ONE 2013, 8, e68252.
  46. Myriad Genetics. EndoPredict: One Test—Three Clinical Answers for Breast Cancer Patients. 2022. Available online: https://endopredict.eu/ (accessed on 27 November 2022).
  47. Filipits, M.; Rudas, M.; Jakesz, R.; Dubsky, P.; Fitzal, F.; Singer, C.F.; Dietze, O.; Greil, R.; Jelen, A.; Sevelda, P.; et al. A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors. Clin. Cancer Res. 2011, 17, 6012–6020.
  48. Sestak, I.; Martín, M.; Dubsky, P.; Kronenwett, R.; Rojo, F.; Cuzick, J.; Filipits, M.; Ruiz, A.; Gradishar, W.; Soliman, H.; et al. Prediction of chemotherapy benefit by EndoPredict in patients with breast cancer who received adjuvant endocrine therapy plus chemotherapy or endocrine therapy alone. Breast Cancer Res. Treat. 2019, 176, 377–386.
  49. Filipits, M.; Dubsky, P.; Rudas, M.; Greil, R.; Balic, M.; Bago-Horvath, Z.; Singer, C.F.; Hlauschek, D.; Brown, K.; Bernhisel, R.; et al. Prediction of Distant Recurrence Using EndoPredict Among Women with ER+, HER2- Node-Positive and Node-Negative Breast Cancer Treated with Endocrine Therapy Only. Clin. Cancer Res. 2019, 25, 3865–3872.
  50. Buus, R.; Sestak, I.; Kronenwett, R.; Denkert, C.; Dubsky, P.; Krappmann, K.; Scheer, M.; Petry, C.; Cuzick, J.; Dowsett, M. Comparison of EndoPredict and EPclin With Oncotype DX Recurrence Score for Prediction of Risk of Distant Recurrence After Endocrine Therapy. J. Natl. Cancer Inst. 2016, 108, djw149.
  51. Constantinidou, A.; Marcou, Y.; Simmons, T.; Bernhisel, R.; Hughes, E.; Meek, S.; Kakouri, E.I.; Georgiou, G.; Zouvani, I.; Savvidou, G.; et al. Clinical validation of EndoPredict in premenopausal women with estrogen receptor-positive (ER+), human epidermal growth factor receptor 2-negative (HER2-) primary breast cancer. J. Clin. Oncol. 2021, 39 (Suppl. S15), 537.
  52. Veridex. GeneSearch Breast Lymph Node (BLN) Test Kit, FDA Report/PMA P060017. 2022. Available online: https://fda.report/PMA/P060017/6/P060017B.pdf (accessed on 7 November 2022).
  53. Janssen Diagnostics. GeneSearch™ Breast Lymph Node (BLN) Assay Post Approval Study. ClinicalTrials.gov Identifier: NCT00595296; 2016. Available online: https://www.clinicaltrials.gov/ct2/show/record/NCT00595296?view=record (accessed on 2 November 2022).
  54. U.S. Food & Drug Administration. Premarket Approval, PMA Number P060017, Genesearch Breast Lymph Node (Bln) Assay. 2022. Available online: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPMA/pma.cfm?start_search=1&PMANumber=P060017 (accessed on 2 November 2022).
  55. Cutress, R.; Agrawal, A.; Etherington, A.; Gabriel, F.G.; Jeffrey, M.; Lai, L.; Wise, M.; Cree, I.; Yiangou, C. Intra-operative assessment of axillary sentinel lymph nodes (SLN) using an RT-PCR based assay for Mammaglobin (MG) and Cytokeratin 19 (CK19). EJSO 2008, 34, 1159–1160.
  56. Mansel, R.E.; Goyal, A.; Douglas-Jones, A.; Woods, V.; Goyal, S.; Monypenny, I.; Sweetland, H.; Newcombe, R.G.; Jasani, B. Detection of breast cancer metastasis in sentinel lymph nodes using intra-operative real time GeneSearch BLN Assay in the operating room: Results of the Cardiff study. Breast Cancer Res. Treat. 2009, 115, 595–600.
  57. Agendia. The Molecular Profile to Define and Defeat Her Unique Cancer. 2022. Available online: https://agendia.com/mammaprint/ (accessed on 27 November 2022).
  58. Mittempergher, L.; Delahaye, L.J.M.J.; Witteveen, A.T.; Spangler, J.B.; Hassenmahomed, F.; Mee, S.; Mahmoudi, S.; Chen, J.; Bao, S.; Snel, M.H.J.; et al. MammaPrint and BluePrint Molecular Diagnostics Using Targeted RNA Next-Generation Sequencing Technology. J. Mol. Diagn. 2019, 21, 808–823.
  59. Bou Zerdan, M.; Ibrahim, M.; Nakib, C.E.; Hajjar, R.; Assi, H.I. Genomic Assays in Node Positive Breast Cancer Patients: A Review. Front. Oncol. 2021, 10, 609100.
  60. Biotheranostics, I. Breast Cancer Index. 2022. Available online: www.breastcancerindex.com (accessed on 27 November 2022).
  61. Myriad Genetic Laboratories. Myriad EndoPredict Technical Specifications. 2021. Available online: https://myriad-library.s3.amazonaws.com/technical-specifications/EndoPredict-Technical-Specifications.pdf (accessed on 2 November 2022).
  62. Sun, L.; Legood, R.; Sadique, Z.; Dos-Santos-Silva, I.; Yang, L. Cost-effectiveness of risk-based breast cancer screening programme, China. Bull. World Health Organ. 2018, 96, 568–577.
  63. Nøst, T.H.; Holden, M.; Dønnem, T.; Bøvelstad, H.; Rylander, C.; Lund, E.; Sandanger, T.M. Transcriptomic signals in blood prior to lung cancer focusing on time to diagnosis and metastasis. Sci. Rep. 2021, 11, 7406.
  64. Holsbø, E.; Olsen, K.S. Metastatic Breast Cancer and Pre-Diagnostic Blood Gene Expression Profiles-The Norwegian Women and Cancer (NOWAC) Post-Genome Cohort. Front. Oncol. 2020, 10, 575461.
  65. Holden, M.; Holden, L.; Olsen, K.S.; Lund, E. Local in Time Statistics for detecting weak gene expression signals in blood—Illustrated for prediction of metastases in breast cancer in the NOWAC Post-genome Cohort. Adv. Genom. Genet. 2017, 7, 11–28.
  66. Chen, S.; Liu, M.; Liang, B.; Ge, S.; Peng, J.; Huang, H.; Xu, Y.; Tang, X.; Deng, L. Identification of human peripheral blood monocyte gene markers for early screening of solid tumors. PLoS ONE 2020, 15, e0230905.
  67. Han, M.; Liew, C.T.; Zhang, H.W.; Chao, S.; Zheng, R.; Yip, K.T.; Song, Z.Y.; Li, H.M.; Geng, X.P.; Zhu, L.X.; et al. Novel blood-based, five-gene biomarker set for the detection of colorectal cancer. Clin. Cancer Res. 2008, 14, 455–460.
  68. Siegel, R.L.; Miller, K.D.; Fuchs, H.E.; Jemal, A. Cancer Statistics, 2021. CA Cancer J. Clin. 2021, 71, 7–33.
  69. Thigpen, D.; Kappler, A.; Brem, R. The Role of Ultrasound in Screening Dense Breasts-A Review of the Literature and Practical Solutions for Implementation. Diagnostics 2018, 8, 20.
  70. Weedon-Fekjaer, H.; Lindqvist, B.H.; Vatten, L.J.; Aalen, O.O.; Tretli, S. Breast cancer tumor growth estimated through mammography screening data. Breast Cancer Res. 2008, 10, R41.
  71. DeSantis, C.E.; Ma, J.; Gaudet, M.M.; Newman, L.A.; Miller, K.D.; Goding Sauer, A.; Jemal, A.; Siegel, R.L. Breast cancer statistics, 2019. CA Cancer J. Clin. 2019, 69, 438–451.
  72. de Fraipont, F.; Gazzeri, S.; Cho, W.C.; Eymin, B. Circular RNAs and RNA Splice Variants as Biomarkers for Prognosis and Therapeutic Response in the Liquid Biopsies of Lung Cancer Patients. Front. Genet. 2019, 10, 390.
  73. Markou, A.; Tzanikou, E.; Lianidou, E. The potential of liquid biopsy in the management of cancer patients. Semin. Cancer Biol. 2022, 84, 69–79.
  74. Duffy, M.J. Chapter 13—Circulating cancer biomarkers: Current status and future prospects. In Clinical Aspects and Laboratory Determination, Cancer Biomarkers; Ramanathan, L.V., Fleisher, M., Duffy, M.J., Eds.; Elsevier: Amsterdam, The Netherlands, 2022; pp. 409–443.
  75. Adashek, J.J.; Janku, F.; Kurzrock, R. Signed in Blood: Circulating Tumor DNA in Cancer Diagnosis, Treatment and Screening. Cancers 2021, 13, 3600.
  76. Li, J.; Guan, X.; Fan, Z.; Ching, L.M.; Li, Y.; Wang, X.; Cao, W.M.; Liu, D.X. Non-Invasive Biomarkers for Early Detection of Breast Cancer. Cancers 2020, 12, 2767.
  77. Jurj, A.; Zanoaga, O.; Braicu, C.; Lazar, V.; Tomuleasa, C.; Irimie, A.; Berindan-Neagoe, I. A Comprehensive Picture of Extracellular Vesicles and Their Contents. Molecular Transfer to Cancer Cells. Cancers 2020, 12, 298.
  78. Liyanage, U.K.; Moore, T.T.; Joo, H.G.; Tanaka, Y.; Herrmann, V.; Doherty, G.; Drebin, J.A.; Strasberg, S.M.; Eberlein, T.J.; Goedegebuure, P.S.; et al. Prevalence of regulatory T cells is increased in peripheral blood and tumor microenvironment of patients with pancreas or breast adenocarcinoma. J. Immunol. 2002, 169, 2756–2761.
  79. Liew, C.C.; Ma, J.; Tang, H.C.; Zheng, R.; Dempsey, A.A. The peripheral blood transcriptome dynamically reflects system wide biology: A potential diagnostic tool. J. Lab. Clin. Med. 2006, 147, 126–132.
  80. Twine, N.C.; Stover, J.A.; Marshall, B.; Dukart, G.; Hidalgo, M.; Stadler, W.; Logan, T.; Dutcher, J.; Hudes, G.; Dorner, A.J.; et al. Disease-associated expression profiles in peripheral blood mononuclear cells from patients with advanced renal cell carcinoma. Cancer Res. 2003, 63, 6069–6075.
  81. Stoiber, D.; Assinger, A. Platelet-Leukocyte Interplay in Cancer Development and Progression. Cells 2020, 9, 855.
  82. Ward, M.P.; EKane, L.; ANorris, L.; Mohamed, B.M.; Kelly, T.; Bates, M.; Clarke, A.; Brady, N.; Martin, C.M.; Brooks, R.D.; et al. Platelets, immune cells and the coagulation cascade; friend or foe of the circulating tumour cell? Mol. Cancer 2021, 20, 59.
  83. Sharma, P.; Sahni, N.S.; Tibshirani, R.; Skaane, P.; Urdal, P.; Berghagen, H.; Jensen, M.; Kristiansen, L.; Moen, C.; Sharma, P.; et al. Early detection of breast cancer based on gene-expression patterns in peripheral blood cells. Breast Cancer Res. 2005, 7, R634–R644.
  84. Aarøe, J.; Lindahl, T.; Dumeaux, V.; Saebø, S.; Tobin, D.; Hagen, N.; Skaane, P.; Lönneborg, A.; Sharma, P.; Børresen-Dale, A.L. Gene expression profiling of peripheral blood cells for early detection of breast cancer. Breast Cancer Res. 2010, 12, R7.
  85. Čelešnik, H.S. Triple-Negative Breast Cancer and other Breast Cancer. In: Encyclopedia. Available online: https://encyclopedia.pub/entry/21678 (accessed on 27 November 2022).
  86. Thompson, D.; Easton, D. The genetic epidemiology of breast cancer genes. J. Mammary Gland. Biol. Neoplasia 2004, 9, 221–236.
  87. Loke, S.Y.; Lee, A.S.G. The future of blood-based biomarkers for the early detection of breast cancer. Eur. J. Cancer 2018, 92, 54–68.
  88. Seale, K.N.; Tkaczuk, K.H.R. Circulating Biomarkers in Breast Cancer. Clin. Breast Cancer 2022, 22, e319–e331.
  89. Ambry Genetics. +RNAinsight, Expanded RNA Analysis for Better Variant Classification. 2021. Available online: https://www.ambrygen.com/file/material/view/1663/RNA_Flyer_FNL%20091521.pdf (accessed on 8 November 2022).
  90. Syantra. Syantra DX|Breast Cancer FAQs. 2022. Available online: https://ss-usa.s3.amazonaws.com/c/308494115/media/1619629a43fbddb7823212636145172/4115~collateral_FAQs_c.pdf (accessed on 8 November 2022).
  91. Syantra. 2022. Available online: https://www.syantra.com/ (accessed on 8 November 2022).
  92. StageZero. Aristotle®. 2022. Available online: https://www.stagezerolifesciences.com/aristotle-test.html (accessed on 8 November 2022).
  93. Tobin, D.; Karlsson, M.; Hagen, N.; Børresen-Dale, A.; Mydland, E.; Bårdsen, K.; Jensen, M. Use of the blood based, 96-assay set for breast cancer detection. Poster. EJC Suppl. 2010, 8, 164.
  94. Tobin, D.; Bårdsen, K.; Kauczynska, M.; Kumar, Y.; Shroff, C.; Punia, D.; Srinivasan, V.; Børresen Dale, A.; Sharma, P.; Hollingsworth, A. Performance of a blood-based gene-expression test, BCtect, for early breast cancer detection. J. Clin. Oncol. 2009, 27 (Suppl. S15), 11012.
  95. Mackay, J.; Szecsei, C.M. Genetic counselling for hereditary predisposition to ovarian and breast cancer. Ann. Oncol. 2010, 21 (Suppl. S7), vii334–vii338.
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