Cancer progression and the invisible phase of metastatic colonization

Nature reviews. Cancer, Journal Year: 2020, Volume and Issue: 20(11), P. 681 - 694

Published: Oct. 6, 2020

Language: Английский

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Single‐cell RNA sequencing in cancer research

Journal of Experimental & Clinical Cancer Research, Journal Year: 2021, Volume and Issue: 40(1)

Published: March 1, 2021

Abstract Single-cell RNA sequencing (scRNA-seq), a technology that analyzes transcriptomes of complex tissues at single-cell levels, can identify differential gene expression and epigenetic factors caused by mutations in unicellular genomes, as well new cell-specific markers cell types. scRNA-seq plays an important role various aspects tumor research. It reveals the heterogeneity cells monitors progress development, thereby preventing further cellular deterioration. Furthermore, transcriptome analysis immune tissue be used to classify cells, their escape mechanisms drug resistance mechanisms, develop effective clinical targeted therapies combined with immunotherapy. Moreover, this method enables study intercellular communication interaction non-malignant reveal carcinogenesis. provides technical means for development research is expected make significant breakthroughs field. This review focuses on principles scRNA-seq, emphasis application heterogeneity, pathogenesis, treatment.

Language: Английский

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Independent Drug Action in Combination Therapy: Implications for Precision Oncology

Cancer Discovery, Journal Year: 2022, Volume and Issue: 12(3), P. 606 - 624

Published: Jan. 4, 2022

Combination therapies are superior to monotherapy for many cancers. This advantage was historically ascribed the ability of combinations address tumor heterogeneity, but synergistic interaction is now a common explanation as well design criterion new combinations. We review evidence that independent drug action, described in 1961, explains efficacy practice-changing combination therapies: it provides populations patients with heterogeneous sensitivities multiple chances benefit from at least one drug. Understanding response heterogeneity could reveal predictive or pharmacodynamic biomarkers more precise use existing drugs and realize benefits additivity synergy.Significance:. The model action represents an effective means predict magnitude likely be observed clinical trials therapies. "bet-hedging" strategy implicit suggests individual often only subset—sometimes one—of combination. Personalized, targeted therapy, consisting agents active particular patient, will increase, perhaps substantially, therapeutic benefit. Precision approaches this type require better understanding variability biomarkers, which entail preclinical research on diverse panels cancer models rather than studying synergy unusually sensitive models.

Language: Английский

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Pharmacogenomics: Driving Personalized Medicine

Pharmacological Reviews, Journal Year: 2023, Volume and Issue: 75(4), P. 789 - 814

Published: March 16, 2023

Abstract

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool improve outcomes prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, metagenomics). This review summarizes basic principles relevant translation assessing pharmacogenomics' central role converging diverse elements of personalized medicine. We discuss genetic variations pharmacogenes (drug-metabolizing enzymes, drug transporters, receptors), their clinical relevance biomarkers, legacy decades research pharmacogenetics. All types including proteins, nucleic acids, viruses, cells, genes, irradiation, can benefit from genomics, expanding across Food Drug Administration approvals therapeutics involving biomarkers increase rapidly, demonstrating growing impact pharmacogenomics. A beacon for therapeutic approaches, molecularly targeted cancer therapies highlight trends discovery applications. To account human complexity, multicomponent biomarker panels genetic, personal, environmental factors guide diagnosis increasingly artificial intelligence cope extreme data complexities. However, application encounters substantial hurdles, such unknown validity ethnic groups, underlying bias care, real-world validation. address science technologies germane medicine, integrated economic, ethical, regulatory issues, providing insights current status future direction care.

Significance Statement

aims optimize care individual patients use predictive Pharmacogenomics drives guides development therapeutics. addresses large-scale repositories accelerating medical advances. The is discussed, along hurdles impeding broad implementation, context ethics, economics, affairs.

Language: Английский

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Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Journal of Hematology & Oncology, Journal Year: 2022, Volume and Issue: 15(1)

Published: May 12, 2022

Abstract Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS widely in diagnosis treatment of various diseases, including cancer. Over years, has gradually become effective clinical tool for exploration tumor metastasis mechanisms development strategies. Currently, not only analyze metastasis-related malignant biological characteristics, such as heterogeneity, drug resistance, microenvironment, but also construct maps predicting monitoring dynamics metastasis. identify therapeutic targets related it provides insights into distribution subsets gene expression differences between primary metastatic tumors. Additionally, techniques combination with artificial intelligence (AI) are liquid biopsy circulating cells (CTCs), thereby providing novel strategy treating In this review, we summarize potential applications field discuss prospects limitations provide theoretical basis finding

Language: Английский

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Single-cell RNA sequencing and immune microenvironment analysis reveal PLOD2-driven malignant transformation in cervical cancer

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 15

Published: Jan. 7, 2025

Cervical cancer is the fourth most common in women globally, and main cause of disease has been found to be ongoing HPV infection. remains primary cancer-related death despite major improvements screening treatment approaches, especially low- middle-income nations. Therefore, it crucial investigate tumor microenvironment advanced cervical order identify possible targets. In better understand malignant epithelial cells (EPCs), this study used bulk RNA-seq data from UCSC conjunction with single-cell RNA sequencing ArrayExpress database. After putting quality control procedures into place, cell type identification clustering analysis using Seurat software were carried out. To clarify functional pathways, enrichment differential gene expression The CIBERSORT ESTIMATE R packages evaluate immune characteristics, univariate multivariate Cox regression analyses extract prognostic features. Furthermore, assessments drug sensitivity Eight types identified, EPCs showing high proliferative stemness Five EPC subpopulations defined, C1 NNMT+ CAEPCs driving differentiation. A NNMT Risk Score (NCRS) model was developed, revealing a correlation between elevated NCRS scores adverse patient outcomes characterized by evasion. vitro experiments validated that PLOD2 significantly enhances proliferation, migration, invasion cells. This investigation delineated eight five cancer, establishing as therapeutic target. demonstrated its capability, indicating higher are associated poorer clinical outcomes. validation highlights potential, underscoring critical need for integrating immunotherapy targeted strategies enhance diagnostic approaches cancer.

Language: Английский

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Integrative inference of subclonal tumour evolution from single-cell and bulk sequencing data

Nature Communications, Journal Year: 2019, Volume and Issue: 10(1)

Published: June 21, 2019

Abstract Understanding the clonal architecture and evolutionary history of a tumour poses one key challenges to overcome treatment failure due resistant cell populations. Previously, studies on subclonal evolution have been primarily based bulk sequencing in some recent cases single-cell data. Either data type alone has shortcomings with regard this task, but methods integrating both types lacking. Here, we present B-SCITE, first computational approach that infers phylogenies from combined Using comprehensive set simulated data, show B-SCITE systematically outperforms existing respect tree reconstruction accuracy subclone identification. provides high-fidelity reconstructions even modest number single cells where allele frequencies are affected by copy changes. On real generated mutation histories high concordance expert trees.

Language: Английский

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Cancer Diagnosis Using a Liquid Biopsy: Challenges and Expectations

Diagnostics, Journal Year: 2018, Volume and Issue: 8(2), P. 31 - 31

Published: May 9, 2018

The field of cancer diagnostics has recently been impacted by new and exciting developments in the area liquid biopsy. A biopsy is a minimally invasive alternative to surgical biopsies solid tissues, typically achieved through withdrawal blood sample or other body fluids, allowing interrogation tumor-derived material including circulating tumor cells (CTCs) DNA (ctDNA) fragments that are present at given time point. In this short review, we discuss few studies summarize state-of-the-art from diagnostic perspective, speculate on current challenges expectations implementing testing for diagnosis monitoring clinical setting.

Language: Английский

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Plant Systems Biology at the Single-Cell Level

Trends in Plant Science, Journal Year: 2017, Volume and Issue: 22(11), P. 949 - 960

Published: Sept. 30, 2017

Language: Английский

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Single-cell mutation identification via phylogenetic inference

Nature Communications, Journal Year: 2018, Volume and Issue: 9(1)

Published: Nov. 28, 2018

Reconstructing the evolution of tumors is a key aspect towards identification appropriate cancer therapies. The task challenging because evolve as heterogeneous cell populations. Single-cell sequencing holds promise resolving heterogeneity tumors; however, it has its own challenges including elevated error rates, allelic drop-out, and uneven coverage. Here, we develop new approach to mutation detection in individual tumor cells by leveraging evolutionary relationship among cells. Our method, called SCIΦ, jointly calls mutations estimates phylogeny these Employing Markov Chain Monte Carlo scheme enables us reliably call each single even experiments with high drop-out rates missing data. We show that SCIΦ outperforms existing methods on simulated data applied different real-world datasets, namely whole exome breast well panel acute lymphoblastic leukemia dataset.

Language: Английский

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