Epigenetic loss of heterogeneity from low to high grade localized prostate tumours

A risk-reward examination of sample multiplexing reagents for single cell RNA-Seq

Single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for understanding cellular heterogeneity and function. However the choice of sample multiplexing reagents can impact data quality and experimental outcomes. In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, across diverse sample types such as human peripheral blood mononuclear cells (PBMCs), mouse embryonic brain and patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We compared multiple demultiplexing algorithms which differed in performance depending on data quality. We find that minor improvements to laboratory workflows such as titration and rapid processing are critical to optimal performance. We also compared the performance of fixed scRNA-Seq kits and highlight the advantages of the Parse Biosciences kit for fragile samples. Highly multiplexed scRNA-Seq experiments require more sequencing resources, therefore we evaluated CRISPR-based destruction of non-informative genes to enhance sequencing value. Our comprehensive analysis provides insights into the selection of appropriate sample multiplexing reagents and protocols for scRNA-Seq experiments, facilitating more accurate and cost-effective studies.

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.

Integrative multi-omics and drug-response characterization of patient-derived prostate cancer primary cells

Prostate cancer (PCa) is the second most prevalent malignancy in males across the world. A greater knowledge of the relationship between protein abundance and drug responses would benefit precision treatment for PCa. Herein, we establish 35 Chinese PCa primary cell models to capture specific characteristics among PCa patients, including gene mutations, mRNA/protein/surface protein distributions, and pharmaceutical responses. The multi-omics analyses identify Anterior Gradient 2 (AGR2) as a pre-operative prognostic biomarker in PCa. Through the drug library screening, we describe crizotinib as a selective compound for malignant PCa primary cells. We further perform the pharmacoproteome analysis and identify 14,372 significant protein-drug correlations. Surprisingly, the diminished AGR2 enhances the inhibition activity of crizotinib via ALK/c-MET-AKT axis activation which is validated by PC3 and xenograft model. Our integrated multi-omics approach yields a comprehensive understanding of PCa biomarkers and pharmacological responses, allowing for more precise diagnosis and therapies.

Supervised learning of high-confidence phenotypic subpopulations from single-cell data

Accurately identifying phenotype-relevant cell subsets from heterogeneous cell populations is crucial for delineating the underlying mechanisms driving biological or clinical phenotypes. Here, by deploying a learning with rejection strategy, we developed a novel supervised learning framework called PENCIL to identify subpopulations associated with categorical or continuous phenotypes from single-cell data. By embedding a feature selection function into this flexible framework, for the first time, we were able to select informative features and identify cell subpopulations simultaneously, which enables the accurate identification of phenotypic subpopulations otherwise missed by methods incapable of concurrent gene selection. Furthermore, the regression mode of PENCIL presents a novel ability for supervised phenotypic trajectory learning of subpopulations from single-cell data. We conducted comprehensive simulations to evaluate PENCIĽs versatility in simultaneous gene selection, subpopulation identification and phenotypic trajectory prediction. PENCIL is fast and scalable to analyze 1 million cells within 1 hour. Using the classification mode, PENCIL detected T-cell subpopulations associated with melanoma immunotherapy outcomes. Moreover, when applied to scRNA-seq of a mantle cell lymphoma patient with drug treatment across multiple time points, the regression mode of PENCIL revealed a transcriptional treatment response trajectory. Collectively, our work introduces a scalable and flexible infrastructure to accurately identify phenotype-associated subpopulations from single-cell data.

An Overview of the Molecular Cues and Their Intracellular Signaling Shared by Cancer and the Nervous System: From Neurotransmitters to Synaptic Proteins, Anatomy of an All-Inclusive Cooperation

We propose an overview of the molecular cues and their intracellular signaling involved in the crosstalk between cancer and the nervous system. While "cancer neuroscience" as a field is still in its infancy, the relation between cancer and the nervous system has been known for a long time, and a huge body of experimental data provides evidence that tumor-nervous system connections are widespread. They encompass different mechanisms at different tumor progression steps, are multifaceted, and display some intriguing analogies with the nervous system's physiological processes. Overall, we can say that many of the paradigmatic "hallmarks of cancer" depicted by Weinberg and Hanahan are affected by the nervous system in a variety of manners.

The most effective but largely ignored target for prostate cancer early detection and intervention

Over the past two decades, the global efforts for the early detection and intervention of prostate cancer seem to have made significant progresses in the basic researches, but the clinic outcomes have been disappointing: (1) prostate cancer is still the most common non-cutaneous cancer in Europe in men, (2) the age-standardized prostate cancer rate has increased in nearly all Asian and African countries, (3) the proportion of advanced cancers at the diagnosis has increased to 8.2% from 3.9% in the USA, (4) the worldwide use of PSA testing and digital rectal examination have failed to reduce the prostate cancer mortality, and (5) there is still no effective preventive method to significantly reduce the development, invasion, and metastasis of prostate cancer… Together, these facts strongly suggest that the global efforts during the past appear to be not in a correlated target with markedly inconsistent basic research and clinic outcomes. The most likely cause for the inconsistence appears due to the fact that basic scientific studies are traditionally conducted on the cell lines and animal models, where it is impossible to completely reflect or replicate the in vivo status. Thus, we would like to propose the human prostate basal cell layer (PBCL) as “the most effective target for the early detection and intervention of prostate cancer”. Our proposal is based on the morphologic, immunohistochemical and molecular evidence from our recent studies of normal and cancerous human prostate tissues with detailed clinic follow-up data. We believe that the human tissue-derived basic research data may provide a more realistic roadmap to guide the clinic practice and to avoid the potential misleading from in vitro and animal studies.

The Role of Perineural Invasion in Prostate Cancer and Its Prognostic Significance

Simple Summary

Prostate cancer is one of the most frequently diagnosed cancers in men worldwide. Perineural invasion (PNI), the movement of cancer cells along nerves, is a commonly observed approach to tumor spread and is important in both research and clinical practice of prostate cancer. However, despite many studies reporting on molecules and pathways involved in PNI, understanding its clinical relevance remains insufficient. In this review, we aim to summarize the current knowledge of mechanisms and prognostic significance of PNI in prostate cancer, which may provide new perspectives for future studies and improved treatment.

Abstract

Perineural invasion (PNI) is a common indication of tumor metastasis that can be detected in multiple malignancies, including prostate cancer. In the development of PNI, tumor cells closely interact with the nerve components in the tumor microenvironment and create the perineural niche, which provides a supportive surrounding for their survival and invasion and benefits the nerve cells. Various transcription factors, cytokines, chemokines, and their related signaling pathways have been reported to be important in the progress of PNI. Nevertheless, the current understanding of the molecular mechanism of PNI is still very limited. Clinically, PNI is commonly associated with adverse clinicopathological parameters and poor outcomes for prostate cancer patients. However, whether PNI could act as an independent prognostic predictor remains controversial among studies due to inconsistent research aim and endpoint, sample type, statistical methods, and, most importantly, the definition and inclusion criteria. In this review, we provide a summary and comparison of the prognostic significance of PNI in prostate cancer based on existing literature and propose that a more standardized description of PNI would be helpful for a better understanding of its clinical relevance.

Patterns of indolence in prostate cancer (Review)

Although prostate cancer is a major cause of cancer-related mortality worldwide, most patients will have a relatively indolent clinical course. Contrary to most other types of cancer, even the diagnosis of locally advanced or metastatic disease is not always lethal. The present review aimed to summarize what is known regarding the underlying mechanisms related to the indolent course of subsets of prostate cancer, at various stages. The data suggested that no specific gene alteration by itself was responsible for carcinogenesis or disease aggressiveness. However, pathway analysis identified genetic aberrations in multiple critical pathways that tend to accumulate over the course of the disease. The progression from indolence into aggressive disease is associated with a complex interplay in which genetic and epigenetic factors are involved. The effect of the immune tumor microenvironment is also very important. Emerging evidence has suggested that the upregulation of pathways related to cellular aging and senescence can identify patients with indolent disease. In addition, a number of tumors enter a long-lasting quiescent state. Further research will determine whether halting tumor evolution is a feasible option, and whether the life of patients can be markedly prolonged by inducing tumor senescence or long-term dormancy.