ReviewFrontiers in immunology2018
Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology.
Review in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed, 66 citations in OpenAlex.
- Adaptor proteins regulating tumor-associated macrophage polarization during cancer progression.Oncoscience · 2026Review
- Single-Cell Sequencing Data Revealed Mechanisms of Interactions Between Tumor Cells and Cancer-Associated Fibroblasts in Metastatic Colorectal Cancer.BioMed research international · 2026Article
- Plantaricin BM-1 enhances anti-colorectal cancer effects by inhibiting CD8+ cytotoxic T cell apoptosis via the ERK/AP1/Bim signaling pathway.Frontiers in immunology · 2026Article
- Using single cell sequencing to investigate tumor microenvironment differences in left and right colon cancer and prognosis-related core genes.Discover oncology · 2025Article
- From inflammation to invasion: neutrophils in cervical cancer pathogenesis.Annals of medicine and surgery (2012) · 2025Review
- Comprehensive biomarker profiles in hematological malignancies: improving diagnosis, prognosis, and treatment.Biomarkers in medicine · 2025Review
- Multi-omics integration and machine learning-driven construction of an immunogenic cell death prognostic model for colon cancer and functional validation of FCGR2A.Frontiers in pharmacology · 2025Article
- Cancer stem cells and tumor-associated macrophages as mates in tumor progression: mechanisms of crosstalk and advanced bioinformatic tools to dissect their phenotypes and interaction.Frontiers in immunology · 2025Review
- Personalized analysis of human cancer multi-omics for precision oncology.Computational and structural biotechnology journal · 2024Review
- Application of Single-Cell Sequencing Technology in Research on Colorectal Cancer.Journal of personalized medicine · 2024Review
- Harnessing the potential of CAR-T cell therapy: progress, challenges, and future directions in hematological and solid tumor treatments.Journal of translational medicine · 2023Review
- Single-Cell Analysis in Immuno-Oncology.International journal of molecular sciences · 2023Review
- A Method for Rapid, Quantitative Evaluation of Particle Sorting in Microfluidics Using Basic Cytometry Equipment.Micromachines · 2023Article
- Pan-cancer classification of single cells in the tumour microenvironment.Nature communications · 2023Article
- Will gazing into the single-cell multiome illuminate cardiovascular drug development?Nature cardiovascular research · 2023Article
- Advances in Microfluidics for Single Red Blood Cell Analysis.Biosensors · 2023Review
- A Novel Attention-Mechanism Based Cox Survival Model by Exploiting Pan-Cancer Empirical Genomic Information.Cells · 2022Article
- The Architecture of a Precision Oncology Platform.Advances in experimental medicine and biology · 2022Review
- Deciphering colorectal cancer immune microenvironment transcriptional landscape on single cell resolution - A role for immunotherapy.Frontiers in immunology · 2022Review
- Capturing tumour heterogeneity in pre- and post-chemotherapy colorectal cancer ascites-derived cells using single-cell RNA-sequencing.Bioscience reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a heterogeneous and complex disease. Tumors are formed by cancer cells and a myriad of non-cancerous cell types that together with the extracellular matrix form the tumor microenvironment. These cancer-associated cells and components contribute to shape the progression of cancer and are deeply involved in patient outcome. The immune system is an essential part of the tumor microenvironment, and induction of cancer immunotolerance is a necessary step involved in tumor formation and growth. Immune mechanisms are intimately associated with cancer progression, invasion, and metastasis; as well as to tumor dormancy and modulation of sensitivity to drug therapy. Transcriptome analyses have been extensively used to understand the heterogeneity of tumors, classifying tumors into molecular subtypes and establishing signatures that predict response to therapy and patient outcomes. However, the classification of the tumor cell diversity and specially the identification of rare populations has been limited in these transcriptomic analyses of bulk tumor cell populations. Massively-parallel single-cell RNAseq analysis has emerged as a powerful method to unravel heterogeneity and to study rare cell populations in cancer, through unsupervised sampling and modeling of transcriptional states in single cells. In this context, the study of the role of the immune system in cancer would benefit from single cell approaches, as it will enable the characterization and/or discovery of the cell types and pathways involved in cancer immunotolerance otherwise missed in bulk transcriptomic information. Thus, the analysis of gene expression patterns at single cell resolution holds the potential to provide key information to develop precise and personalized cancer treatment including immunotherapy. This review is focused on the latest single-cell RNAseq methodologies able to agnostically study thousands of tumor cells as well as targeted single-cell RNAseq to study rare populations within tumors. In particular, we will discuss methods to study the immune system in cancer. We will also discuss the current challenges to the study of cancer at the single cell level and the potential solutions to the current approaches.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.