In the last half decade, we have witnessed an exponential increase in the sample sizes of multiplex proteomics studies, with population biobanks in Iceland, Finland, Qatar, and the United Kingdom increasingly implementing proteomic profiling across their cohorts. In this talk, we will illustrate how the rapidly expanding field population proteomics has emerged from, and has been partly driven by, the successes and setbacks of population genetics. We will review present-day examples of how population proteomics is being leveraged to accelerate precision medicine, placing particular emphasis on high-impact applications of the UK Biobank Pharma Proteomics Project (UKB-PPP) dataset. Finally, we will discuss the  future of population proteomics – from more systematic integration into the drug development process to clinical translation

Most patients treated with immune checkpoint blockade (ICB) do not have durable treatment responses, stressing a critical need to identify early non-invasive biomarkers of response. Circulating biomarkers provide easy access for serial monitoring and can provide insight on the mechanisms of response to ICB. We performed plasma proteomics (~3000 proteins) from 250 metastatic melanoma patients before and on ICB treatment and performed analysis to identify response- and time point-associated peripheral protein biomarkers. We next generated patient-matched peripheral blood lymphocyte (PBL) surface proteomic data to measure their proportions in circulation. We further obtained 13 patient-matched tumor samples and performed single-cell RNA-sequencing (scRNA-seq). We fit linear mixed effects (LME) models to predict plasma protein abundances, using the sample time point, response status and interaction term between time point and response as covariates, with patient ID as a random effect to account for patient-level differences in protein abundance. We identified 397 proteins with a significant time point, response, or interaction effect, or some combination of these effects. For proteins with positive time point effects (upregulated post-ICB), gene ontology analysis suggested these proteins were associated with inflammatory pathways involving the activation of effector immune functions. LME models fitted on the PBL proportions data and an analysis of immune-related plasma proteins supported that post-ICB samples may be defined by increased immune activity, including T cell infiltration. Moreover, expression of genes corresponding to these post-ICB proteins in the tumor scRNA-seq data tended to be favored by immune subsets, namely those involved in immune cell recruitment and tumor reactivity, such as CXCL10+ macrophages and CXCL13+ T cells, respectively. On the other hand, expression genes corresponding to plasma proteins upregulated in non-responders in the TME tended to be favored by suppressive myeloid subsets such as SPP1+ macrophages as well as malignant cells, suggesting the potential of immunosuppressive and pro-tumor biological processes to be involved in ICB resistance. Inference of cell-cell interactions in the TME further showed the involvement of these non-responder genes in potentially immunosuppressive and pro-tumor processes. Effforts to examine absolute levels of key secreted proteins using the T48 panel are ongoing. Together, these data represent one of the deepest peripheral biomarker studies using paired samples in melanoma patients treated with anti-PD1 therapy.

Numerous studies have shown that the composition of the fecal microbiota is a factor impacting the response to immunotherapy-type anticancer drugs. This is particularly true during dysbiosis induced after taking antibiotics. This finding opened the door to the possibility of using gut microbiota-centered interventions to improve the likelihood of patient response to immunotherapies. One of the gut microbiota-centered therapy is fecal microbiota transplantation (FMT), already used in the treatment of certain intestinal pathologies. Understanding how FMT impacts intestinal and anti-tumor immunity is the challenge of tomorrow to improve the care of patients living with cancer. The use of the Olink Cytokine Panel in our FMT models makes it possible to highlight a variation in the immune tone of the transplant recipient.

The standard of care for Multiple Sclerosis (MS) patients relies heavily on assessments that are subjective, qualitative, and inadequate. To address unmet needs across the entire MS ecosystem (patients, physicians, pharma and payors), Octave Bioscience developed, validated and commercially launched the Multiple Sclerosis Disease Activity (MSDA) Test. The MSDA test quantitatively reports a patient’s level of disease activity using an algorithm incorporating 18 protein biomarkers that are measured in a blood sample. The development of the MSDA test involved biomarker discovery efforts for which over 1400 proteins were screened in several deeply phenotyped studies and associated with clinical and radiographic endpoints of disease activity. An iterative process that balanced statistical, analytical, and biological factors was then used to select proteins for inclusion into a custom assay panel that was developed using the Olink platform. Prior to clinical launch, the MSDA Test was analytically and clinically validated, and it is currently in use in nearly 100 clinics across the United States as well as being utilized in multiple retrospective and prospective clinical trials.  

To facilitate translational research on diabetic kidney disease, we developed the Joslin Kidney Panel (JKP), a panel of 21 circulating proteins strongly associated with risk of kidney function decline and progression to ESKD. Using a custom-made OLINK multiplex platform of assays with excellent specificity, precision, and accuracy, we quantified 21 JKP proteins in four independent study groups. In the Type 1 diabetes individuals from Joslin (n=59), FinnDiane (n=389) and Steno (n=283), JKP proteins predicted progression to ESKD during 10-year follow-up. Many of these proteins had prognostic performance equal to or better than clinical markers. An optimal model to predict risk of ESKD, which included clinical markers and 8 JKP proteins, was developed for the FinnDiane cohort and validated in the Steno cohort, and had better discrimination than the clinical model alone. By measuring baseline serum concentrations of the JKP proteins in a subgroup of 500 Type 2 diabetes individuals from the ACCORD trial, we identified 3 proteins that predicted amelioration of fast kidney function decline during 6 years of follow-up in those receiving treatment with fenofibrate. In conclusion, 21 JKP proteins measured on the Joslin OLINK platform provided a precision medicine-based approach to identify those at risk of ESKD and those responding to specific reno-protective therapy.

As people age, their immune function gradually declines, coinciding with increased cancer rates. However, the precise reasons behind age-related dysfunction of CD8+ T cells in cancer remain unclear. Our study reveals that tumor growth accelerates in older tumor-bearing mice due to diminished infiltration and function of CD8+ T cells. Even when young, tumor antigen-specific CD8+ T cells are transferred into aged hosts, they fail to combat tumors effectively. This failure is related to the rapid onset of CD8+ T cell dysfunction triggered by cell-extrinsic signals from the aged tumor microenvironment. Given that aging is typified by a persistent, low-level inflammation termed inflammaging across various tissues, we wonder whether a specific type of pro-inflammatory cytokine or chemokine is the potential cell-extrinsic signal in the aged tumors that causes CD8+ T cell dysfunction. We then utilize the Olink Target 48 Mouse Cytokine platform to explore the interplay of cytokines and chemokines within both the aging hosts generally and the aged tumors locally. In summary, our research delves into the cell-extrinsic signals (e.g., pro-inflammatory cytokine or chemokine) influencing CD8+ T cell response in aged tumors and proposes potential therapeutic approaches to enhance CD8+ T cell control of cancer.  Learning Objectives  •Understand the potential mechanism of how the aged tumor microenvironment limits CD8+ T cell control of cancer. •Discover proper therapeutic approaches to reinvigorate CD8+ T cell effector function in aged tumors. •