Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I–IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming RAS/RAF mutations in predicting sensitivity to the EGFR inhibitor cetuximab.

Exosomes have been implicated in numerous biological processes, and they may serve as important disease markers. Surface proteins on exosomes carry information about their tissues of origin. Because of the heterogeneity of exosomes it is desirable to investigate them individually, but this has so far remained impractical. Here, we demonstrate a proximity-dependent barcoding assay to profile surface proteins of individual exosomes using antibody-DNA conjugates and next-generation sequencing. We first validate the method using artificial streptavidin-oligonucleotide complexes, followed by analysis of the variable composition of surface proteins on individual exosomes, derived from human body fluids or cell culture media. Exosomes from different sources are characterized by the presence of specific combinations of surface proteins and their abundance, allowing exosomes to be separately quantified in mixed samples to serve as markers for tissue-specific engagement in disease.

Significant advances have been made in methods to analyze genomes and transcriptomes of single cells, but to fully define cell states, proteins must also be accessed as central actors defining a cell's phenotype. Methods currently used to analyze endogenous protein expression in single cells are limited in specificity, throughput, or multiplex capability. Here, we present an approach to simultaneously and specifically interrogate large sets of protein and RNA targets in lysates from individual cells, enabling investigations of cell functions and responses. We applied our method to investigate the effects of BMP4, an experimental therapeutic agent, on early-passage glioblastoma cell cultures. We uncovered significant heterogeneity in responses to treatment at levels of RNA and protein, with a subset of cells reacting in a distinct manner to BMP4. Moreover, we found overall poor correlation between protein and RNA at the level of single cells, with proteins more accurately defining responses to treatment.

We present a scalable, integrated strategy for coupled protein and RNA detection from single cells. Our approach leverages the DNA polymerase activity of reverse transcriptase to simultaneously perform proximity extension assays and complementary DNA synthesis in the same reaction. Using the Fluidigm C1™ system, we profile the transcriptomic and proteomic response of a human breast adenocarcinoma cell line to a chemical perturbation, benchmarking against in situ hybridizations and immunofluorescence staining, as well as recombinant proteins, ERCC Spike-Ins, and population lysate dilutions. Through supervised and unsupervised analyses, we demonstrate synergies enabled by simultaneous measurement of single-cell protein and RNA abundances. Collectively, our generalizable approach highlights the potential for molecular metadata to inform highly-multiplexed single-cell analyses.

Detection of proteins released in the bloodstream from tissues damaged by disease can promote early detection of pathological conditions, differential diagnostics, and follow-up of therapy. Despite these prospects and a plethora of candidate biomarkers, efforts in recent years to establish new protein diagnostic assays have met with limited success. One important limiting factor has been the challenge of detecting proteins present at trace levels in complex bodily fluids. To achieve robust, sensitive, and specific detection, we have developed a microparticle-based solid-phase proximity ligation assay, dependent on simultaneous recognition of target proteins by three antibody molecules for added specificity. After capture on a microparticle, solid-phase pairs of proximity probes are added followed by washes, enabling detection and identification of rare protein molecules in blood while consuming small amounts of sample. We demonstrate that single polyclonal antibody preparations raised against target proteins of interest can be readily used to establish assays where detection depends on target recognition by three individual antibody molecules, recognizing separate epitopes. The assay was compared with state-of-the-art sandwich ELISAs for detection of vascular endothelial growth factor, interleukin-8 and interleukin-6, and it was found to be superior both with regard to dynamic range and minimal numbers of molecules detected. Furthermore, the assays exhibited excellent performance in undiluted plasma and serum as well as in whole blood, producing comparable results for nine different antigens. We thus show that solid-phase proximity ligation assay is suitable for validation of a variety of protein biomarkers over broad dynamic ranges in clinical samples.

Cancer diagnostics based on the detection of protein biomarkers in blood has promising potential for early detection and continuous monitoring of disease. However, the currently available protein biomarkers and assay formats largely fail to live up to expectations, mainly due to insufficient diagnostic specificity. Here, we discuss what kinds of plasma proteins might prove useful as biomarkers of malignant processes in specific organs. We consider the need to search for biomarkers deep down in the lowest reaches of the proteome, below current detection levels. In this regard, we comment on the poor molecular detection sensitivity of current protein assays compared to nucleic acid detection reactions, and we discuss requirements for achieving detection of vanishingly small amounts of proteins, to ensure detection of early stages of malignant growth through liquid biopsy.