Impact of multiplexing technologies on immuno-oncology research

During the last few decades, cancer research has made great strides forward with the development of cancer immunotherapy being hailed as a specific breakthrough for cancer treatment. Immunotherapy is based on enhancing the capability of immune cells to eliminate tumour cells. However, malignant cells can develop the ability to evade immune responses by avoiding immune recognition, expressing factors that modulate or suppress immune cells, or disrupting pathways involved in controlling T cell inhibition.

Tumour proliferation and progression is highly heterogeneous among both patients and types of cancer and there is a large variability in individual response to cancer therapy. This cancer heterogeneity and therapeutic variability necessitates the use of individual molecular profiling to help build a ‘personalized’ plan for therapy. Current research efforts in immuno-oncology focus on the identification of cancer biomarkers for diagnostic, prognostic and predictive purposes, the development of new targeted therapies that harness the immune mechanisms to fight against tumour cells and the development of personalized strategies for cancer treatment.

Tumour biomarkers are measurable molecules whose detection, quantification, or localization can be used diagnostically for assessing the risk of developing a specific condition, for early detection of cancer or for establishing a specific diagnosis. Biomarkers can also provide prognostic information by determining the aggressiveness of a specific tumour, may allow prediction as to how a patient will respond to treatment and are useful in monitoring treatment response over time. Moreover, cancer biomarkers can be used to better understand the signaling pathways of cellular processes, for the validation of clinical trials of new cancer drugs and to identify new potential therapeutic targets.

Cancer biomarkers

There are a great variety of biomarkers and they may be proteins, nucleic acids, antibodies or even metabolic or gene expression factors. Some examples of antibodies include the cancer antigen 125 (CA-125), angiogenic factors like the vascular endothelial growth factor (VEGF) or the human epidermal growth factor receptor 2 (HER2), cytokines like interferons, adipokines, interleukins (IL) and tumour necrosis factors (TNF), or immune checkpoint proteins such as the programmed cell death-ligand 1 (PD-L1) and the cytotoxic T-lymphocyte-associated protein 4 (CTLA-4). The elucidation of how cytokine-mediated inflammation and cancer are correlated or how immune checkpoints are used by cancer cells to avoid anti-tumor response are some of the current active areas of immune-oncology research.

Cytokines are proteins involved in a great number of biochemical pathways with a variety of pro- and anti-inflammatory effects. Among the proinflammatory cytokines there are interferon-γ (IFN-γ), IL-1, IL-12, IL-17, IL-18 or TNF-α, and the anti-inflammatory cytokines include IL-1 receptor antagonist, IL-4, IL-10, or IL-13. There are certain cytokines that have both pro- and anti-inflammatory effects. Moreover, cytokines are involved in adaptive immune response acting as immunomodulating agents. Abnormal cytokine profiles have been correlated with the onset of several types of cancer such as gastric and colorectal cancer, thus cytokine testing can be used to support diagnosis.

Immune checkpoint proteins are involved in maintaining T cell expansion during the immune response. Several tumour cells express high levels of PD-L1, that bind to programmed cell death-1 (PD-1) to block the activation and expansion of T cells and therefore attenuate the anti-tumour response. The level of expression of PD-L1 has been identified as a predictive biomarker of response to targeted therapies in several types of cancer, including lung cancer, breast cancer, head and neck cancer, melanoma and colorectal cancer.

Genetic mutations or alterations can also be used as predictive biomarkers as they can be associated with the risk of developing specific types of cancers. Some examples include mutations of the genes BRCA1 and BRCA2 and the overexpression of the gene HER2 that are associated with breast and ovarian cancer. BRAF mutations are highly associated with melanoma, mutations on genes KRAS or PIK3CA increase the risk of developing colorectal cancer and mutations on genes ALK, EGFR or KRAS are associated with lung cancer. The detection of these genetic alterations not only allow for the assessment of specific cancer risk, but also indicate which patients are more likely to benefit from a particular therapy.

Phenotyping immune response

Even though many proteins can be used as cancer biomarkers, the isolated detection of these proteins may not always be useful to differentiate tumour cells from non-tumour cells, or to predict patient outcomes. Multiplexed technologies are effective tools that allow the detection or quantification of these cancer biomarkers by the simultaneous identification of molecular alterations or specific proteins produced during the immune response. These technologies have boosted immune-oncology research by enabling the investigation of tumour cell immune evasion mechanisms, enhancing the discovery of biomarkers and their mechanisms of action and by predicting patient response to therapy.

Conventional immunostaining assays such as enzyme-linked immunosorbent assay (ELISA), flow cytometry or immunohistochemistry (IHC) are robust techniques to accurately measure protein levels on a liquid or tissue sample. However, these methods have the limitation of measuring a single marker per sample. Multiplexed immunoassay technologies are based on conventional immunoassays but with the advantage that they can quantify multiple proteins in a single sample.

Some of the methods used for multiplex immunoassay include physical isolation of captured antibodies on a solid surface, particle isolation of captured antibodies on dyed beads that may be read with flow cytometry or multiplex IHC or immunofluorescence (IF) that enable simultaneous dying of multiple markers on a tissue sample. These analyses can provide comprehensive information about cell composition and spatial distribution. There are also some technologies that allow for the simultaneous detection of RNA transcripts and proteins.

Moreover, multiplexed imaging technologies have also emerged. These techniques have enabled the identification and quantification of immune cell subsets and their spatial distribution, providing a comprehensive characterization of the tumor and helping to decipher the tumor microenvironment and its relation to the heterogeneity of drug treatments. Using the multiplex imaging profiles of responding and non-responding patients for the subsequent training of artificial intelligence algorithms is also useful to predict the response of new patients to a proposed therapy, enabling better planning of personalized treatment strategies and improving precision medicine.

Examples of applications of multiplex immunoassay

Multiplexing techniques facilitate the quantification of cancer biomarkers which is of paramount importance to both clinical immuno-oncology and in immune-oncology research. One of the applications of multiplexed immunoassays is to find new predictive biomarkers. Immune checkpoint inhibitors like anti-PD1/PD-L1 and anti-CTLA-4 have improved clinical responses and survival of patients with several types of advanced cancers. However, treatment response is not the same for all the patients and across all therapies. Therefore, there is an additional need for predictive biomarkers to better select patients and to facilitate treatment decisions.

The scrutiny of large immune cell subsets across multiple functions is required for the detection and identification of predictive biomarkers. In contrast to conventional immunoassays that only detect a limited number of markers, multiplexing techniques can be used to simultaneously study different cell lineages, cytokines, or activation markers. Thereby, in melanoma patients CD4+ and CD8+ memory T cell subsets have shown up as potential biomarker candidates for anti-CTLA-4 response while natural killer cell subsets have shown correlation with an anti-tumour clinical response to anti-PD1 therapy.

In prostate cancer, there are several multiplex biomarker tests for screening, diagnostic, and prognostic purposes. These tests assess several molecular markers such as levels of prostate specific antigen (PSA), presence of TMPRSS2-ERG fusions, or expression of PCA3, KLK3, HOXC6, TDRD1, and DLX1 genes. The results of the different arrays of biomarkers provide screening information that allow selection of which patients should be referred for biopsy, diagnostic information on which suspected prostate cancer patients should be re-biopsied after a negative initial biopsy, or prognostic information that allows the stratification of patients according to their prostate cancer risk and the selection of those that need to be treated after a positive biopsy or after a surgery.

Another application of these techniques is to better understand mechanisms of clinical response to immunotherapies in cancer. For example, in head and neck squamous cell carcinoma, multiplexed immunoassay was used to assess whether chemo-radiotherapy impacted tumor vasculature and antitumour immunity by altering levels of several antiangiogenic factors including VEGF, placental growth factor (PLGF) and angiopoietins-1 and 2 (Ang 1 and Ang2). It was found that chemoradiation decreased VEGF and Ang1 levels and increased Ang2 and PLGF, suggesting the existence of compensatory angiogenic pathways that are activated through a reduction in VEGF levels and illuminating potential mechanisms of impact of chemoradiation on systemic antitumour immunity.

Pathologists have also benefited from multiplexed IHC as it is a potent tool to simultaneously detect multiple protein biomarkers on a single tissue sample thereby enabling the precise characterization of different cells and their interactions with, for example, the tumour microenvironment. In non-small cell lung cancer (NSCLC), multiplexed IHC and IF techniques have improved the molecular and immune profiling of these tumours.

The expression of PD1 and the intratumoral infiltration of CD8+T cells are potential predictive biomarkers of clinical response to immunotherapy. Multiplex IHC and IF have been associated with an improved prediction of response to anti-PD1/PD-L1 therapies over PD-L1 IHC, tumour mutational burden or gene expression profiling alone. Moreover, multiparametric analysis allows better characterization of more complex cell phenotypes, such as a subpopulations of resident memory T cells (CD8+T), defined by several biomarkers including CD103, CD49a or CD69, and whose close contact with epithelial tumour cells suggests involvement in immunosurveillance. Patients with NSCLC that have high levels of intratumoral infiltration with CD8+T cells or a high effector CD8+T cell/regulatory T cell ratio, show better clinical outcomes. Multiplex IF has also revealed that patients with EGFR-mutated NSCLC may not respond to immunotherapy, since they only slightly express PD-L1 and do not show CD8+T cell infiltration. Other predictive biomarkers of response to anti-PD1/PD-L1 could be an increase of T cells with low proliferation and activation status, defined by low levels of Ki67 and Granzyme negative, considering that these markers have been correlated with better overall survival in NSCLC patients treated with immunotherapy.

Early detection of ovarian cancer is essential to improve patient survival. Multiplexed platforms have been used to identify candidate biomarkers that, in combination with CA-125 and HE4, may improve sensitivity and specificity for early-stage serous ovarian cancer detection. A multiplex approach was used to simultaneously test 92 proteins. The different protein expression data allowed separation of non-tumour samples from early- or late-stage serous ovarian cancer samples, using different clustering methods, and identification of candidate serum biomarkers for ovarian cancer such as MK, KLK6, hK11, CXCL13, FR-alpha, IL-6, TNFSF14, FADD, PRSS8, and FUR. Moreover, the information from multiple proteins was used to develop a classifier to discern between early-stage serous ovarian cancer and healthy women. The multi-protein classifier combined 12 proteins (CA125, CD40.L, CD69, CXCL9, CXCL13, EGFR, EpCAM, PARK7, SELE, LAP.TGF-β1, TF, and VEGFR2) and was found to have better sensitivity and specificity than CA-125 alone.

These are only some examples of the applications of multiplexed immunoassays in oncology. The continuing development of multiplexing technologies and new prognostic and predictive assays has resulted in a marked increase in publications, during the last few years, of immuno- oncology research using these multiplexing assays. This rapidly evolving field of research is leading to a better understanding of the tumor microenvironment, with the identification and quantification of the different immune cell subsets involved in tumor development, their spatial distribution, and the identification of biomarkers associated with the immune response. Some of the potential outcomes include improved diagnostic precision, better personalized medicine, new treatment strategies and the development of new targeted therapies which will ultimately lead to improved diagnostics and better precision medicine.


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