Despite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance measurements. Here, we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high-sensitivity mass spectrometry. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. By individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and uncharacterized proteins. In an archived primary melanoma tissue, DVP identified spatially resolved proteome changes as normal melanocytes transition to fully invasive melanoma, revealing pathways that change in a spatial manner as cancer progresses, such as mRNA splicing dysregulation in metastatic vertical growth that coincides with reduced interferon signaling and antigen presentation. The ability of DVP to retain precise spatial proteomic information in the tissue context has implications for the molecular profiling of clinical samples.

Cutaneous T-cell lymphomas (CTCLs) are the most frequent primary skin lymphomas. Nevertheless, diagnosis of early disease has proven difficult because of a clinical and histologic resemblance to benign inflammatory skin diseases. To address whether microRNA (miRNA) profiling can discriminate CTCL from benign inflammation, we studied miRNA expression levels in 198 patients with CTCL, peripheral T-cell lymphoma (PTL), and benign skin diseases (psoriasis and dermatitis). Using microarrays, we show that the most induced (miR-326, miR-663b, and miR-711) and repressed (miR-203 and miR-205) miRNAs distinguish CTCL from benign skin diseases with > 90% accuracy in a training set of 90 samples and a test set of 58 blinded samples. These miRNAs also distinguish malignant and benign lesions in an independent set of 50 patients with PTL and skin inflammation and in experimental human xenograft mouse models of psoriasis and CTCL. Quantitative (q)RT-PCR analysis of 103 patients with CTCL and benign skin disorders validates differential expression of 4 of the 5 miRNAs and confirms previous reports on miR-155 in CTCL. A qRT-PCR–based classifier consisting of miR-155, miR-203, and miR-205 distinguishes CTCL from benign disorders with high specificity and sensitivity, and with a classification accuracy of 95%, indicating that miRNAs have a high diagnostic potential in CTCL.

Testicular germ cell cancers in young adult men derive from a precursor lesion called carcinoma in situ (CIS) of the testis. CIS cells were suggested to arise from primordial germ cells or gonocytes. However, direct studies on purified samples of CIS cells are lacking. To overcome this problem, we performed laser microdissection of CIS cells. Highly enriched cell populations were obtained and subjected to gene expression analysis. The expression profile of CIS cells was compared with microdissected gonocytes, oogonia, and cultured embryonic stem cells with and without genomic aberrations. Three samples of each tissue type were used for the analyses. Unique expression patterns for these developmentally very related cell types revealed that CIS cells were very similar to gonocytes because only five genes distinguished these two cell types. We did not find indications that CIS was derived from a meiotic cell, and the similarity to embryonic stem cells was modest compared with gonocytes. Thus, we provide new evidence that the molecular phenotype of CIS cells is similar to that of gonocytes. Our data are in line with the idea that CIS cells may be gonocytes that survived in the postnatal testis. We speculate that disturbed development of somatic cells in the fetal testis may play a role in allowing undifferentiated cells to survive in the postnatal testes. The further development of CIS into invasive germ cell tumors may depend on signals from their postpubertal niche of somatic cells, including hormones and growth factors from Leydig and Sertoli cells. [Cancer Res 2009;69(12):5241–50]

This paper reports that aggressive antibiotic treatment inhibits disease activity and lymphocyte proliferation in cutaneous T-cell lymphoma (CTCL). The study offers important evidence for a link between bacterial infection, activation of the immune system, and CTCL progression.

The pathogenesis of cutaneous T-cell lymphoma (CTCL) remains elusive. Recent discoveries indicate that the oncogenic microRNA miR-155 is overexpressed in affected skin from CTCL patients. Here, we address what drives the expression of miR-155 and investigate its role in the pathogenesis of CTCL. We show that malignant T cells constitutively express high levels of miR-155 and its host gene BIC (B cell integration cluster). Using ChIP-seq, we identify BIC as a target of transcription factor STAT5, which is aberrantly activated in malignant T cells and induced by IL-2/IL-15 in non-malignant T cells. Incubation with JAK inhibitor or siRNA-mediated knockdown of STAT5 decreases BIC/miR-155 expression, whereas IL-2 and IL-15 increase their expression in cell lines and primary cells. In contrast, knockdown of STAT3 has no effect, and BIC is not a transcriptional target of STAT3, indicating that regulation of BIC/miR-155 expression by STAT5 is highly specific. Malignant proliferation is significantly inhibited by an antisense-miR-155 as well as by knockdown of STAT5 and BIC. In conclusion, we provide the first evidence that STAT5 drives expression of oncogenic BIC/miR-155 in cancer. Moreover, our data indicate that the STAT5/BIC/miR-155 pathway promotes proliferation of malignant T cells, and therefore is a putative target for therapy in CTCL.