Evaluation of ex vivo drug combination optimization platform in recurrent high grade astrocytic glioma: An interventional, non-randomized, open-label trial protocol.

INTRODUCTION: High grade astrocytic glioma (HGG) is a lethal solid malignancy with high recurrence rates and limited survival. While several cytotoxic agents have demonstrated efficacy against HGG, drug sensitivity testing platforms to aid in therapy selection are lacking. Patient-derived organoids (PDOs) have been shown to faithfully preserve the biological characteristics of several cancer types including HGG, and coupled with the experimental-analytical hybrid platform Quadratic Phenotypic Optimization Platform (QPOP) which evaluates therapeutic sensitivity at a patient-specific level, may aid as a tool for personalized medical decisions to improve treatment outcomes for HGG patients. METHODS: This is an interventional, non-randomized, open-label study, which aims to enroll 10 patients who will receive QPOP-guided chemotherapy at the time of first HGG recurrence following progression on standard first-line therapy. At the initial presentation of HGG, tumor will be harvested for primary PDO generation during the first biopsy/surgery. At the point of tumor recurrence, patients will be enrolled onto the main study to receive systemic therapy as second-line treatment. Subjects who undergo surgery at the time of recurrence will have a second harvest of tissue for PDO generation. Established PDOs will be subject to QPOP analyses to determine their therapeutic sensitivities to specific panels of drugs. A QPOP-guided treatment selection algorithm will then be used to select the most appropriate drug combination. The primary endpoint of the study is six-month progression-free survival. The secondary endpoints include twelve-month overall survival, RANO criteria and toxicities. In our radiological biomarker sub-study, we plan to evaluate novel radiopharmaceutical-based neuroimaging in determining blood-brain barrier permeability and to assess in vivo drug effects on tumor vasculature over time. TRIAL REGISTRATION: This trial was registered on 8th September 2022 with ClinicalTrials.gov Identifier: NCT05532397.

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping.

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

Quantitative profiling of drug-associated proteomic alterations by combined 2-nitrobenzenesulfenyl chloride (NBS) isotope labeling and 2DE/MS identification.

The identification of drug-responsive biomarkers in complex protein mixtures is an important goal of quantitative proteomics. Here, we describe a novel approach for identifying such drug-induced protein alterations, which combines 2-nitrobenzenesulfenyl chloride (NBS) tryptophan labeling with two-dimensional gel electrophoresis (2DE)/mass spectrometry (MS). Lysates from drug-treated and control samples are labeled with light or heavy NBS moiety and separated on a common 2DE gel, and protein alterations are identified by MS through the differential intensity of paired NBS peptide peaks. Using NBS/2DE/MS, we profiled the proteomic alterations induced by tamoxifen (TAM) in the estrogen receptor (ER) positive MCF-7 breast cancer cell line. Of 88 protein spots that significantly changed upon TAM treatment, 44 spots representing 23 distinct protein species were successfully identified with NBS-paired peptides. Of these 23 TAM-altered proteins, 16 (70%) have not been previously associated with TAM or ER activity. We found the NBS labeling procedure to be both technically and biologically reproducible, and the NBS/2DE/MS alterations exhibited good concordance with conventional 2DE differential protein quantitation, with discrepancies largely due to the comigration of distinct proteins in the regular 2DE gels. To validate the NBS/2DE/MS results, we used immunoblotting to confirm GRP78, CK19, and PA2G4 as bona fide TAM-regulated proteins. Furthermore, we demonstrate that PA2G4 expression can serve as a novel prognostic factor for disease-free survival in two independent breast cancer patient cohorts. To our knowledge, this is the first report describing the proteomic changes in breast cancer cells induced by TAM, the most commonly used selective estrogen receptor modulator (SERM). Our results indicate that NBS/2DE/MS may represent a more reliable approach for cellular protein quantitation than conventional 2DE approaches.

Integrative genomic, transcriptional, and proteomic diversity in natural isolates of the human pathogen Burkholderia pseudomallei.

Natural isolates of pathogenic bacteria can exhibit a broad range of phenotypic traits. To investigate the molecular mechanisms contributing to such phenotypic variability, we compared the genomes, transcriptomes, and proteomes of two natural isolates of the gram-negative bacterium Burkholderia pseudomallei, the causative agent of the human disease melioidosis. Significant intrinsic genomic, transcriptional, and proteomic variations were observed between the two strains involving genes of diverse functions. We identified 16 strain-specific regions in the B. pseudomallei K96243 reference genome, and for eight regions their differential presence could be ascribed to either DNA acquisition or loss. A remarkable 43% of the transcriptional differences between the strains could be attributed to genes that were differentially present between K96243 and Bp15682, demonstrating the importance of lateral gene transfer or gene loss events in contributing to pathogen diversity at the gene expression level. Proteins expressed in a strain-specific manner were similarly correlated at the gene expression level, but up to 38% of the global proteomic variation between strains comprised proteins expressed in both strains but associated with strain-specific protein isoforms. Collectively, >65 hypothetical genes were transcriptionally or proteomically expressed, supporting their bona fide biological presence. Our results provide, for the first time, an integrated framework for classifying the repertoire of natural variations existing at distinct molecular levels for an important human pathogen.