This chapter comprehensively describes the methods involved in antibody conjugation, validation, staining procedures, and preliminary data collection on human and mouse pancreatic adenocarcinoma samples using IMC or MIBI. With the goal of facilitating use, these protocols are intended for these complex platforms, enabling their application not only in tissue-based tumor immunology studies, but also in broader tissue-based oncology and immunology research.
Specialized cell types' development and physiology are dictated by the interplay of complex signaling and transcriptional programs. Perturbations in these cellular programs lead to the emergence of human cancers from a multifaceted array of specialized cell types and developmental states. The intricate nature of these systems, along with their capacity to contribute to cancer growth, necessitates the development of immunotherapies and the pursuit of druggable targets. Pioneering single-cell multi-omics technologies, designed to analyze transcriptional states, have been coupled with cell-surface receptor expression. This chapter explains a computational framework, SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), that establishes a connection between transcription factors and the expression of proteins on the cell's surface. To model gene expression, SPaRTAN integrates CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to simulate how transcription factors and cell-surface receptors interact. Our presentation of the SPaRTAN pipeline uses CITE-seq data from peripheral blood mononuclear cells.
Mass spectrometry (MS) plays a critical role in biological research, adeptly probing a broad spectrum of biomolecules, including proteins, drugs, and metabolites, exceeding the capabilities of alternative genomic approaches. Unfortunately, combining measurements of different molecular classes for downstream analysis is complex, requiring input from specialists in different relevant fields. The intricate nature of this process acts as a critical impediment to the widespread implementation of MS-based multi-omic methodologies, despite the unparalleled biological and functional understanding that these data offer. compound 991 supplier To fulfill the existing gap in this area, our team developed Omics Notebook, an open-source platform designed to enable automated, reproducible, and customizable exploratory analysis, reporting, and integration of MS-based multi-omic data. This pipeline's deployment provides researchers with a framework to more quickly identify functional patterns across complex data types, concentrating on results that are both statistically significant and biologically compelling in their multi-omic profiling. This chapter describes a protocol, employing our publicly available tools, to analyze and integrate high-throughput proteomics and metabolomics data for the creation of reports aimed at propelling research, encouraging collaboration across institutions, and achieving wider data dissemination.
Intracellular signal transduction, gene transcription, and metabolism are but a few of the biological processes that are reliant upon protein-protein interactions (PPI) as their bedrock. Not only are PPI involved in the pathogenesis and development of various diseases, but also in cancer. Gene transfection and molecular detection technologies have shed light on the PPI phenomenon and its functions. Instead, during histopathological evaluation, while immunohistochemical analyses offer details regarding protein expression and their placement within the context of diseased tissues, visualizing protein-protein interfaces has presented a considerable hurdle. For the microscopic observation of protein-protein interactions (PPI) in formalin-fixed, paraffin-embedded tissues, cultured cells, and frozen tissues, an in situ proximity ligation assay (PLA) was developed. Cohort studies of PPI, facilitated by PLA applied to histopathological specimens, provide crucial data on the pathologic role of PPI. Our prior studies highlighted the dimerization pattern of estrogen receptors and the implications of HER2-binding proteins, using fixed formalin-preserved embedded breast cancer tissue. A process for the visualization of protein-protein interactions (PPIs) in pathological specimens using photolithographically produced arrays (PLAs) is laid out in this chapter.
In the clinical management of numerous cancers, nucleoside analogs (NAs) remain a reliable class of anticancer agents, administered either independently or in conjunction with other proven anticancer or pharmacological therapies. By the present date, nearly a dozen anticancer nucleic acids have received FDA approval, and numerous novel nucleic acid agents are undergoing preclinical and clinical research for potential future applications. medial temporal lobe A primary cause of resistance to therapy lies in the problematic delivery of NAs into tumor cells, arising from modifications in the expression of drug carrier proteins, such as solute carrier (SLC) transporters, within the tumor or the cells immediately surrounding it. High-throughput investigation of alterations in numerous chemosensitivity determinants in hundreds of patient tumor tissues is enabled by the combination of tissue microarray (TMA) and multiplexed immunohistochemistry (IHC), surpassing conventional IHC methods. We describe, in detail, the optimized procedure for multiplexed immunohistochemistry (IHC) on TMAs from pancreatic cancer patients treated with gemcitabine, a nucleoside analog chemotherapy. This chapter encompasses the steps for imaging tissue sections and quantifying relevant marker expressions, alongside a discussion of considerations in experimental design and execution.
Innate resistance and resistance to anticancer drugs that arises from treatment are recurring obstacles in cancer therapy. Gaining insight into the mechanisms of drug resistance is crucial for developing alternative therapeutic strategies. A strategy involves subjecting drug-sensitive and drug-resistant variants to single-cell RNA sequencing (scRNA-seq), followed by network analysis of the resulting scRNA-seq data to pinpoint pathways linked to drug resistance. This protocol outlines a computational analysis pipeline for investigating drug resistance, employing the integrative network analysis tool PANDA on scRNA-seq expression data. PANDA incorporates protein-protein interactions (PPI) and transcription factor (TF) binding motifs for comprehensive analysis.
The recent surge in spatial multi-omics technologies has brought about a revolutionary change in biomedical research. The DSP, commercialized by nanoString, has achieved a prominent position within spatial transcriptomics and proteomics, proving useful in disentangling complex biological inquiries. Our three-year engagement with DSP has yielded a practical protocol and key handling guide, brimming with actionable details, to empower the wider community to improve efficiency in their workflow.
Within the 3D-autologous culture method (3D-ACM), a patient's own body fluid or serum is integral in constructing both a 3D scaffold and the culture medium for patient-derived cancer samples. nocardia infections 3D-ACM facilitates the in vitro growth of tumor cells and/or tissues from a patient, creating a microenvironment remarkably similar to their in vivo state. In order to uphold the natural biological properties of the tumor, cultural preservation is the desired approach. This technique is used for two types of models: (1) cells separated from malignant ascites or pleural effusions, and (2) solid tissues from biopsies or surgically excised cancers. A thorough guide to the procedures for creating and utilizing these 3D-ACM models is presented.
A new and unique model, the mitochondrial-nuclear exchange mouse, enhances our comprehension of how mitochondrial genetics influence disease pathogenesis. This document presents the rationale for their development, the techniques employed in their creation, and a brief account of how MNX mice have been employed to elucidate the involvement of mitochondrial DNA in diverse diseases, with a focus on cancer metastasis. Polymorphisms in mitochondrial DNA, that vary between mouse strains, induce intrinsic and extrinsic effects on metastasis by modifying the epigenetic landscape of the nuclear genome, impacting reactive oxygen species, modulating the gut microbiota, and influencing the immunological reaction to cancer cells. Concerning cancer metastasis, the core topic of this report, MNX mice have been valuable in elucidating the involvement of mitochondria in the pathogenesis of other diseases.
Biological samples are subjected to RNA sequencing, a high-throughput method for quantifying mRNA. To determine the genetic basis of drug resistance, differential gene expression analysis is widely applied to compare drug-resistant and sensitive cancer cells. Our experimental and bioinformatic pipeline, from mRNA isolation from human cell lines to next-generation sequencing library preparation and subsequent bioinformatics analyses, is described in comprehensive detail.
The occurrence of DNA palindromes, a type of chromosomal alteration, is a frequent hallmark of tumorigenesis. These are characterized by nucleotide sequences that are identical to their reverse complement sequences. Such sequences are frequently a consequence of improper repair of DNA double-strand breaks, the fusion of telomeres, or the halt of replication forks, all representing adverse early events commonly linked to cancer. A protocol is presented for enriching palindromes from genomic DNA with limited quantities of DNA input and a bioinformatics method to quantify the enrichment and precisely locate newly formed palindromes in low-coverage whole-genome sequencing data.
Systems and integrative biology's comprehensive methodologies provide a means to analyze the complex and multiple layers of investigation inherent in cancer biology. The use of large-scale, high-dimensional omics data for in silico discoveries finds valuable support in integrating lower-dimensional data and outcomes from lower-throughput wet lab studies, fostering a more mechanistic comprehension of the control, execution, and operation of intricate biological systems.