The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution

Abstract

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous largescale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.Cancer forms and progresses through a series of critical transitions-from pre-malignant to malignant states, from locally contained to metastatic disease, and from treatment-responsive to treatment-resistant tumors (Figure 1). Although specifics differ across tumor types and patients, all transitions involve complex dynamic interactions between diverse pre-malignant, malignant, and non-malignant cells (e.g., stroma cells and immune cells), often organized in specific patterns within the tumor

Sensei: How many samples to tell evolution in single-cell studies?

“…We expect that Sensei, with rich information we summarized from various datasets including normal/tumor, primary/metastasis/recurrent tumor, and pre-/post-treatment data, will meet the demand of many projects that are being planned, such as those in the Human Tumor Atlas Network [53] Pre-Cancer Atlas [48,50], and clinical trials. Similar single-cell studies are on the rise at present.…”

Single-cell genomics to understand disease pathogenesis

“…In the near future, the number of studies integrating single-cell genomics with deep phenotyping [102] or assessing/predicting drug responses with single-cell genomics will increase [103][104][105]. After confirming the conservation of the myeloid subsets in human and mouse colorectal cancer, Zhang et al used single-cell RNA-seq to show that anti-CSF1R treatment preferentially depletes macrophages with an inflammatory signature, but spares macrophage populations that express pro-angiogenic/ tumorigenic genes, and that CD40 agonist treatment preferentially activates a specific dendritic cell population and expands Th1-like and CD8 + memory T cells [106].…”

The issues with tissues: the wide range of cell fate separation enables the evolution of multicellularity and cancer

“…How the unlocking of developmentally defined differentiation programmes is explored and explained matters for our understanding of where cancer arises along the cellular differentiation pathway. Understanding the qualities of cancer's cell type of origin would improve our abilities to predict and restrain the evolutionary success of cancer [1,[38][39][40][41].…”