Abstract'Molecular signatures' are the qualitative and quantitative patterns of groups of biomolecules (e.g., mRNA, proteins, peptides, or metabolites) in a cell, tissue, biological fluid, or an entire organism. To apply this concept to biomarker discovery, the measurements should ideally be noninvasive and performed in a single read-out. We have therefore developed a peptidomics platform that couples magnetics-based, automated solid-phase extraction of small peptides with a high-resolution MALDI-TOF mass spectrometric readout (Villanueva, J.; Philip, J.; Entenberg, D.; Chaparro, C. A.; Tanwar, M. K.; Holland, E. C.; Tempst, P. Anal. Chem. 2004Chem. , 76, 1560Chem. -1570. Since hundreds of peptides can be detected in microliter volumes of serum, it allows to search for disease signatures, for instance in the presence of cancer. We have now evaluated, optimized, and standardized a number of clinical and analytical chemistry variables that are major sources of bias; ranging from blood collection and clotting, to serum storage and handling, automated peptide extraction, crystallization, spectral acquisition, and signal processing. In addition, proper alignment of spectra and user-friendly visualization tools are essential for meaningful, certifiable data mining. We introduce a minimal entropy algorithm, 'Entropycal', that simplifies alignment and subsequent statistical analysis and increases the percentage of the highly distinguishing spectral information being retained after feature selection of the datasets. Using the improved analytical platform and tools, and a commercial statistics program, we found that sera from thyroid cancer patients can be distinguished from healthy controls based on an array of 98 discriminant peptides. With adequate technological and computational methods in place, and using rigorously standardized conditions, potential sources of patient related bias (e.g., gender, age, genetics, environmental, dietary, and other factors) may now be addressed.

We present the design and describe the operation of a scanning probe microscope which simultaneously provides the attractive mode force and near-field optical images of objects. In this technique, the force signal is used to track the topography, thus allowing the optical signal primarily to show variations in transmissivity. A number of results are presented on the application of the technique to imaging different samples.

Recently, surface-enhanced Raman scattering nanoprobes have shown tremendous potential in oncological imaging owing to the high sensitivity and specificity of their fingerprint-like spectra. As current Raman scanners rely on a slow, point-by-point spectrum acquisition, there is an unmet need for faster imaging to cover a clinically relevant area in real-time. Herein, we report the rational design and optimization of fluorescence-Raman bimodal nanoparticles (FRNPs) that synergistically combine the specificity of Raman spectroscopy with the versatility and speed of fluorescence imaging. DNA-enabled molecular engineering allows the rational design of FRNPs with a detection limit as low as 5 × 10 −15 M. FRNPs selectively accumulate in tumor tissue mouse cancer models and enable real-time fluorescence imaging for tumor detection, resection, and subsequent Raman-based verification of clean margins. Furthermore, FRNPs enable highly efficient image-guided photothermal ablation of tumors, widening the scope of the NPs into the therapeutic realm.

Regulatory T cells (Tregs) suppress antitumor immunity by inhibiting the killing of tumor cells by antigen-specific CD8+ T cells. To better understand the mechanisms involved, we used ex vivo three-dimensional (3D) collagen-fibrin gel cultures of dissociated B16 melanoma tumors. This system recapitulated the in vivo suppression of antimelanoma immunity, rendering the dissociated tumor cells resistant to killing by cocultured activated, antigen-specific T cells. Immunosuppression was not observed when tumors excised from Treg-depleted mice were cultured in this system. Experiments with neutralizing antibodies showed that blocking transforming growth factor–β (TGF-β) also prevented immunosuppression. Immunosuppression depended on cell-cell contact or cellular proximity because soluble factors from the collagen-fibrin gel cultures did not inhibit tumor cell killing by T cells. Moreover, intravital, two-photon microscopy showed that tumor-specific Pmel-1 effector T cells physically interacted with tumor-resident Tregs in mice. Tregs isolated from B16 tumors alone were sufficient to suppress CD8+ T cell–mediated killing, which depended on surface-bound TGF-β on the Tregs. Immunosuppression of CD8+ T cells correlated with a decrease in the abundance of the cytolytic protein granzyme B and an increase in the cell surface amount of the immune checkpoint receptor PD-1. These findings suggest that contact between Tregs and antitumor T cells in the tumor microenvironment inhibits antimelanoma immunity in a TGF-β–dependent manner and highlight potential ways to inhibit intratumoral Tregs therapeutically.