Introduction

Cancer ranks as a leading cause of death and a huge obstacle to rising life expectancy, hence a major public health problem worldwide. According to the data from GLOBOCAN, 19.3 million new cancer cases and almost 10.0 million cancer deaths occurred in 2020 (Siegel et al. 2020a). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020 (Sung et al. 2021). Conventional methods, mainly referring to medical imageology, such as computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, endoscope, etc., rely on the phenotypic features of the tumor and thus are not powerful to the cancer detection at early stage (Roointan et al. 2019). It has been demonstrated by the union international center of cancer that one-third of cancers are preventable. If cancers are spotted early there is a high chance of survival.

Cancer involves multi-stage process and its pathogenesis and evolution are closely related to a complicated series of genetic and epigenetic alterations, which leads to the tumor transformation and ultimate malignancy (Huang et al. 2018a). Cancer’s onset and progression often associated with some specific molecular alteration, the correlated molecules which are identified as biomarkers (Sveen et al. 2020). The cancer-associated biomarkers are capable of indicating specific cancer states, since their presence and absence and even the concentration change in normal cell often indicate the cancer evolution. As a result, biomarkers play an important role in early diagnosis, assessing the patient's state, and develo** an appropriate therapy strategy. Traditional biochemical strategies based on polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) suffer from time and reagents consuming and discontinuous monitoring (Rusling et al. 2010). The demand for fast, real-time, and cost-effective biomarker tests is on the rise (Chen et al. 2020).

Optical biosensors have recently attracted researchers' attention due to their exceptional performance. They are label-free, quick, sensitive, robust and dependable (Khansili et al. 2018; Chen and Wang 2020). Biological signal is probed and then transformed to an optical signal including optical absorption, fluorescence, refractive index (RI), et al. Amongst which, optical sensor based on the RI detection is named optical RI sensor. Optical RI sensor makes use of evanescent wave to sense the RI change within a whole sample (bulk sensing) or a small volume very close to the sensor surface (surface sensing) (Chiavaioli et al. 2017). For bulk sensing, evanescent wave with its entire extent of penetration depth interacts with the surrounding volume. The optical RI sensor is only deemed as an optical refractometer. While for surface sensing, only the portion of the evanescent wave probed the RI and thickness of a biolayer which was previously immobilized on the sensing surface. In this case, optical RI sensor is used as an optical biosensor. When it comes to cancer biomarker detection, optical RI sensor served as optical biosensor because detection specificity and affinity are undoubtedly considered in the test.

The recognition element and the signal transducer underlie the RI-based cancer biomarker detection theory (Fig. 1). On one hand, recognition element which normally associated with the transducer enables to identify and capture the biomarker in complex clinical sample with high affinity and specificity. On the other hand, RI variation induced by biomarkers is extremely sensitive, which enables biomarkers to be spotted at very low levels (Kozma et al. 2014; Chocarro Ruiz 2019).

Fig. 1
figure 1

Sketch of the RI-based optical biosensor, whose primary components were molecular recognition unit and optical RI transducer

Among different configurations of optical RI transducer, SPR technology which is the earliest commercially available product is the most effective tool for the in vitro assay, especially for medical diagnosis (Sanders et al. 2014). For a traditional SPR technology, photonic energy is confined on the gold film surface leading to the intensified light-matter interaction. Nevertheless, it is still challenge to determine the biomarker in clinical sample due to a very low concentration. Recent decades, the advance of nanotechnology benefits SPR technique a lot (Mao et al. 2021; Ye et al. 2018; Li et al. 2017). Nanomaterials with the unique chemical and physical properties, have positive effects on both the recognition and transducing processes and ultimately improve the sensing performance. AuNPs and 2D functional nanomaterials are widely adopted in assistance with SPR for detecting a cancer biomarker. AuNPs features localized SPR (LSPR) effect which is confined on the surface of AuNPs (Saha et al. 2012). The LSPR coupling with the propagating SPR (PSPR) results in an intensified electromagnetic field. Moreover, AuNPs promote biomarkers secretion from cancer cells and hence strengthens the initial weak biological signal (Giljohann et al. 2020).

There have been exploited some 2D functional nanomaterials so far, such as the graphene and its derivatives (Stebunov et al. 2015; Chiu et al. 2017a; Chiu and Huang 2014), molybdenum disulfide (MoS2) and its derivatives (Zhang et al. 2015; Chiu et al. 2017b; Chiu and Lin 2018), black phosphorus (BP) (Nangare and Patil 2021; Pandey et al. 2021), antimonene (Pumera and Sofer 2017; Lu et al.

Availability of data and materials

Not applicable.

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Funding

National Science Foundation of Shaanxi Province (2022JQ-707). National Natural Science Foundation of China (12204367), Fundamental Research Funds for the Central Universities (XJS211203).

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Chen Chen conceived, designed, and wrote the manuscript; Kaifei Wang collected literatures of section II (Cancer biomarker) and he also discussed the manuscript; Lei Luo discussed the outlook of the SPR biosensor and edited the manuscript. All authors read and approved the final manuscript.

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Correspondence to Chen Chen.

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Chen, C., Wang, K. & Luo, L. AuNPs and 2D functional nanomaterial-assisted SPR development for the cancer detection: a critical review. Cancer Nano 13, 29 (2022). https://doi.org/10.1186/s12645-022-00138-7

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