Unraveling mitotic protein networks by 3D multiplexed epitope drug screening.

Three-dimensional protein localization intricately determines the functional coordination of cellular processes. The complex spatial context of protein landscape has been assessed by multiplexed immunofluorescent staining or mass spectrometry, applied to 2D cell culture with limited physiological relevance or tissue sections. Here, we present 3D SPECS, an automated technology for 3D Spatial characterization of Protein Expression Changes by microscopic Screening. This workflow comprises iterative antibody staining, high-content 3D imaging, and machine learning for detection of mitoses. This is followed by mapping of spatial protein localization into a spherical, cellular coordinate system, a basis for model-based prediction of spatially resolved affinities of proteins. As a proof-of-concept, we mapped twelve epitopes in 3D-cultured spheroids and investigated the network effects of twelve mitotic cancer drugs. Our approach reveals novel insights into spindle fragility and chromatin stress, and predicts unknown interactions between proteins in specific mitotic pathways. 3D SPECS's ability to map potential drug targets by multiplexed immunofluorescence in 3D cell culture combined with our automated high-content assay will inspire future functional protein expression and drug assays.

PPFIA1 and CCND1 are frequently coamplified in breast cancer.

Recently, amplification of PPFIA1, encoding a member of the liprin family located about 600 kb telomeric to CCND1 on chromosome band 11q13, was described in squamous cell carcinoma of head and neck. Because 11q13 amplification is frequent in breast cancer, and PPFIA1 has been suggested to contribute to mammary gland development, we hypothesized that PPFIA1 might also be involved in the 11q13 amplicon in breast cancer and contribute to breast cancer development. A tissue microarray containing more than 2000 human breast cancers was analyzed for gene copy numbers of PPFIA1 and CCND1 by means of fluorescence in situ hybridization. PPFIA1 amplification was found in 248/1583 (15.4%) of breast cancers. Coamplification with CCND1 was found in all (248/248, 100%) PPFIA1-amplified cancers. CCND1 amplification without PPFIA1 coamplification was found in additional 117 (4.7%) tumors. Amplification of both PPFIA1 and CCND1 were significantly associated with high-grade phenotype (P = 0.0002) but were unrelated to tumor stage (P = 0.7066) or nodal stage (P = 0.5807). No difference in patient prognosis was found between 248 CCND1/PPFIA1 coamplified tumors and 117 tumors with CCND1 amplification alone (P = 0.6419). These data show that PPFIA1 amplification occurs frequently in breast cancer. The higher incidence of CCND1 amplification when compared with PPFIA1, the lack of prognostic relevance of coamplifications, and the fact that PPFIA1 amplification was found exclusively in CCND1-amplified cancers suggest that PPFIA1 gene copy number changes represent concurrent events of CCND1 amplification rather than specific biological incidents.

Pheno-seq - linking visual features and gene expression in 3D cell culture systems.

Patient-derived 3D cell culture systems are currently advancing cancer research since they potentiate the molecular analysis of tissue-like properties and drug response under well-defined conditions. However, our understanding of the relationship between the heterogeneity of morphological phenotypes and the underlying transcriptome is still limited. To address this issue, we here introduce "pheno-seq" to directly link visual features of 3D cell culture systems with profiling their transcriptome. As prototypic applications breast and colorectal cancer (CRC) spheroids were analyzed by pheno-seq. We identified characteristic gene expression signatures of epithelial-to-mesenchymal transition that are associated with invasive growth behavior of clonal breast cancer spheroids. Furthermore, we linked long-term proliferative capacity in a patient-derived model of CRC to a lowly abundant PROX1-positive cancer stem cell subtype. We anticipate that the ability to integrate transcriptome analysis and morphological patho-phenotypes of cancer cells will provide novel insight on the molecular origins of intratumor heterogeneity.