Abstract Background Traditional genomic profiling and mutation analysis of single cells like Circulating Tumor Cells (CTCs) fails to capture post-translational and functional alterations of proteins, often leading to limited treatment efficacy. To overcome this gap, we developed a miniaturized ‘protein analysis on the single cell level’ workflow—baptized ZeptoCTC. It integrates established technologies for single-cell isolation with sensitive Reverse Phase Protein Array (RPPA) analysis, thus enabling the comprehensive assessment of multiple protein expression and activation in individual CTCs. Methods The ZeptoCTC workflow involves several critical steps. Firstly, individual cells are labeled and isolated. This is followed by cell lysis and the printing of true single cell lysate preparations onto a ZeptoChip using a modified micromanipulator, CellCelector™. The printed lysates then undergo fluorescence immunoassay RPPA protein detection using a ZeptoReader. Finally, signal quantification is carried out with Image J software, ensuring precise measurement of multiple protein levels. Results The efficacy of ZeptoCTC was demonstrated through various applications. Initially, it was used for measuring EpCAM protein expression, a standard marker for CTC detection, revealing higher levels in single MCF-7 over MDA-MB-231 tumor cells. Furthermore, in Capivasertib (Akt-inhibitor)-treated MCF-7 single cells, ZeptoCTC detected a 2-fold increase in the pAkt/Akt ratio compared to control cells, and confirmed co-performed bulk-cell western blot analysis results. Notably, when applied to individual CTCs from metastasized breast cancer patients, ZeptoCTC revealed significant differences in protein activation levels, particularly in measured pAkt and pErk levels, compared to patient-matched WBCs. Moreover, it successfully differentiated between CTCs from patients with different Akt1 genotypes, highlighting its potential to determine the activation status of druggable cancer driving proteins for individual and targeted treatment decision making. Conclusions The ZeptoCTC workflow represents a valuable tool in single cell cancer research, crucial for personalized medicine. It permits detailed analysis of key proteins and their activation status of targeted, cancer-driven signaling pathways in single cell samples, aiding in understanding tumor response, progression, and treatment efficacy beyond bulk analysis. The method significantly advances clinical investigations in cancer, improving treatment precision and effectiveness. The workflow will be applicable to protein analysis on other types of single cells like relevant in stem cell, neuropathology and hemopoietic cell research.

In a Plac8-YFP-transfected S2-007 cell, a region of interest (ROI) covering a Plac8-positive membrane area (white rectangle) was photobleached using high-power laser intensities. Recovery of fluorescence in the ROI was recorded and quantified over time. Fluorescence recovery was complete within 100 s. Scale bar: 10 µm.

Nocodazole treatment and flow cytometry.

List of differentially expressed transcripts.

Circulating Tumor Cells (CTCs) are commonly analyzed through genomic profiling, which does not capture posttranslational and functional alterations of encoded proteins. To address this limitation, we developed ZeptoCTC, a single-cell protein analysis workflow that combines established technologies for single-cell isolation and sensitive Reverse Phase Protein Array (RPPA) analysis to assess multiple protein expression and activation in individual CTCs. The workflow involves single cell labeling, isolation, lysis, and printing of the true single cell lysates onto a ZeptoChip using a modified micromanipulator CellCelector TM . Subsequently, the printed lysates undergo fluorescence immunoassay RPPA protein detection using a ZeptoReader followed by signal quantification with Image J software. ZeptoCTC was successfully optimized, beginning with the measurement of EpCAM protein expression—a standard marker for CTC detection. As expected, mean fluorescence signals for EpCAM levels were significantly higher in single MCF-7 cells compared to MDA-MB-231 cells. Next, Capivasertib-treated MCF-7 cells exhibited an approximately 2-fold increase in the pAkt/Akt ratio compared to non-treated control cells. This finding was consistent with a co-performed western blot analysis of pooled MCF-7 cells. Application of ZeptoCTC to the analysis of single CTCs derived from a metastasized breast cancer (MBC) patient indicated a significantly higher level of pAkt, accompanied by a corresponding increase in pErk level when compared to patient-matched WBC. Finally, the current workflow successfully indicated the detectable pAkt and Akt signal difference in CTCs from two MBC patients: one with an Akt1 wild-type genotype, and the other harboring approximately 80% Akt1(E17K) mutated CTCs. The mutated CTCs revealed clearly elevated pAkt levels (1.8-fold), along with an even more strongly elevated total Akt (3.4-fold) when compared to the respective signals measured in wild-type CTCs. In conclusion, ZeptoCTC is a highly sensitive method for measuring the expression and phosphorylation of treatment-relevant proteins in key cancer-driving signaling pathways from true single cell samples.

S2-007 cells were transfected with Plac8-CFP (left panel) or YFP (right panel). ROIs (white outlines) in individual cells were repeatedly photobleached using high-power laser intensities and fluorescent signals recorded in regular intervals for 20 min of total duration.

S2-007 cells were co-transfected with Plac8-CFP (left panels/green pseudocolor in overlay) and YFP (middle panels/red pseudocolor in overlay). At the 60 s time point, cells were treated with digitonin, and at the 400 s time point trypsin was added. Scale bars: 10 µm.

Plac8 knockdown does not affect Akt/ phospho-Akt and c-Myc levels.

S2-007 cells were transfected with Plac8-YFP and TIRF images of an individual cell recorded over a timeframe of 9 min.

Quantification of Plac8 signal intensities.

Differentialy expressed transcripts.

3D rendering of stacked images of a Plac8- and PrP-positive intracellular vesicle.

Summary of assays and effects from RPPA analyses.

Results of Pathway Enrichment Analysis.

In light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems representing patient tumor heterogeneity, while enabling parallel drug testing and identification of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease, we developed a 3D preclinical tumor model comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) to identify individual treatment vulnerabilities and validate chemo-, immuno- and targeted therapy efficacies. Enzymatic digestion of primary ovarian cancer tissue and cultivation in defined serum-free media allowed rapid and efficient recovery of PDM, while preserving histopathological features of corresponding patient tumor tissue. Reverse-phase protein array (RPPA)-analyses of >110 total and phospho-proteins enabled the identification of patient-specific sensitivities to standard, platinum-based therapy and thereby the prediction of potential treatment-responders. Co-cultures of PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitor treatment demonstrated patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach. Combining protein pathway analysis and drug efficacy testing of PDM enables drug mode-of-action analyses and therapeutic sensitivity prediction within a clinically relevant time frame after surgery. Follow-up studies in larger cohorts are currently under way to further evaluate the applicability of this platform to support clinical decision making.

Precision oncology is defined as the individualized treatment of a patient´s tumor based on molecular, cellular and functional analyses of tumor tissue specimen (National Center for Tumor Diseases Heidelberg. Precision oncology, 2020). To date, mostly genomic analyses of tumor biopsy tissue are used to identify aberrations present in the patient’s tumor and in result matching drug treatments addressing these alterations. Based on such analyses and considering available clinical and histopathological data, oncologists discuss and select tailored therapies in molecular tumor boards established at clinical centers. A prominent example of a precision therapeutic is Imatinib, which was approved amongst others for the treatment of chronic myeloid leukemia (CML) and gastrointestinal stromal tumors (GIST) harboring activating BCR-ABL gene fusion and c-KIT mutations, respectively. Another early example of precision oncology is the use of tyrosine kinase inhibitors (e.g. Gefitinib, Erlotinib) for treatment of non-small-cell lung cancer (NSCLC) harboring activating mutations in the epidermal growth factor receptor (EGFR). More recently, tissue-agnostic, targeted treatment approaches for tumors harboring TRK gene fusions received clinical approval. Promising results of this novel approach to tumor therapy have led to significant changes and restructuring in the treatment of tumor patients at clinical centers worldwide in recent years. Necessary infrastructures with molecular genomic core facilities and molecular tumor boards have been established and centers for personalized medicine for patient treatment have been founded in many places. Here, we provide an overview on the status of practical implementation of precision oncology at clinical centers with a focus on existing challenges of this approach as well as future opportunities with regard to the integration of additional technologies with emphasis on protein profiling technologies and patient-derived cellular model systems.

Abstract In the era of personalized medicine, the ability of pre-selecting individualized therapeutic options and pre-defining their suitability in advance of clinical treatment might facilitate decision making in breast cancer treatment and hence, improve patient outcome. In order to preclinically validate anti-cancer drug efficacy, it is crucial to design a model system that reveals the influence of cellular interactions of the tumor microenvironment and cellular heterogeneity on drug response. Within the PRIMO (Personalized Medicine for tailored cancer therapies) project, such a 3D preclinical model system comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) isolated from fresh primary breast cancer tissue using limited digestion and subsequent culture in defined media in the absence of serum is established. Herein, the heterogeneous cellular composition of isolated PDM is analyzed by FFPE immunohistochemistry and compared to corresponding primary tumor tissue. The composition of autologous TILs influencing individual treatment responses is characterized by multi-color flow cytometry detecting different cell populations, such as tumor-specific CD8+ or regulatory CD4+ T-cells. By using the DigiWest technology, a proprietary high throughput immune assay screening tool, in-depth protein profiling of up to 200 analytes from low amounts of PDM material is performed. The generated protein profiles of PDM are compared to their corresponding primary tumor tissue as well as the pathological receptor grading. Furthermore, differences in activation of key signal transduction pathways are detected and related to treatment responses to small molecules, chemotherapeutics as well as immunotherapeutic agents within PDM and PDM-TIL co-cultures assessed by a functional viability assay in a microplate format. To expand this preclinical model system, we established PDM-co-cultures adding further immune cell types including natural killer (NK) cells or dendritic cells (DC). In summary, immunohistochemical analyses combined with protein profiling of breast cancer PDM enables drug-mode-of-action analyses, biomarker identification together with personalized therapeutic sensitivity prediction. The platform presented here expands the preclinical repertoire of relevant test systems for efficacy testing of drugs and investigational compounds, pre-identified by protein pathways as well as genetic profiling in personalized medicine of breast cancer. Citation Format: Nicole Anderle, Felix Ruoff, Simge Yuez, André Koch, Andreas Hartkopf, Sara Brucker, Michael Pawlak, Markus Templin, Christian Schmees. A fast and effective 3D preclinical assay system comprised of patient derived breast cancer microtumors combined with DigiWest protein signaling pathway analyses for therapeutic response prediction (Project PRIMO) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS17-42.

An amendment to this paper has been published and can be accessed via the original article.

Background: Progesterone Receptor Membrane Component 1 (PGRMC1) is expressed in many cancer cells, where it is associated with detrimental patient outcomes. It contains phosphorylated tyrosines which evolutionarily preceded deuterostome gastrulation and tissue differentiation mechanisms. Results: We demonstrate that manipulating PGRMC1 phosphorylation status in MIA PaCa-2 (MP) cells imposes broad pleiotropic effects. Relative to parental cells over-expressing hemagglutinin-tagged wild-type (WT) PGRMC1-HA, cells expressing a PGRMC1-HA-S57A/S181A double mutant (DM) exhibited reduced levels of proteins involved in energy metabolism and mitochondrial function, and altered glucose metabolism suggesting modulation of the Warburg effect. This was associated with increased PI3K/Akt activity, altered cell shape, actin cytoskeleton, motility, and mitochondrial properties. An S57A/Y180F/S181A triple mutant (TM) indicated the involvement of Y180 in PI3K/Akt activation. Mutation of Y180F strongly attenuated subcutaneous xenograft tumor growth in NOD-SCID gamma mice. Elsewhere we demonstrate altered metabolism, mutation incidence, and epigenetic status in these cells. Conclusions: Altogether, these results indicate that mutational manipulation of PGRMC1 phosphorylation status exerts broad pleiotropic effects relevant to cancer and other cell biology.