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 large-scale 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.

Keywords: AI; Cancer Moonshot; Human Tumor Atlas; cancer transitions; data integration; data visualization; metastasis; pre-cancer; resistance; single-cell genomics; spatial genomics; spatial imaging; tumor.

Figure 1.. Crucial Transitions in Cancer

HTAN aims to generate 3D atlases of three critical transitions in cancer: tumor initiation (from pre-cancerous lesions to local malignancy), expansion (from local malignancy to metastasis), and progression to a therapy-resistant state through intrinsic (purple) or acquired (yellow) resistance mechanisms. These transitions involve complex interactions between pre-malignant, malignant, and/or non-malignant cells within the tumor ecosystem.

Figure 2.. HTAN Is Complementary to Previous Large-Scale Cancer Genomics Initiatives and Ongoing Atlas Efforts

HTAN will illuminate aspects of malignancy that could not be fully addressed by previous large-scale cancer genomics programs and is complementary to ongoing atlas building efforts across healthy and disease tissues.

Figure 3.. Building 3D Human Tumor Atlases

HTAN centers will measure data modalities at multiple scales of resolution, from molecular to ultrastructural to cellular to histological to anatomical (when possible), and will collect relevant clinical information from patients with tumors under study. These modalities will be used for profiling samples according to the capabilities of each HTAN center. Most centers will use both molecular and spatial profiling methods to generate data. Data that pass HTAN-defined basic processing and quality control will be utilized for interrogating cell-type composition, cell-cell interactions, and spatial structures (left panels). Atlases will then be constructed through the integration of these data modalities measured across time (right panel).

Figure 4.. Key Tumors Studied by the Consortium

HTAN centers will generate 3D atlases of human tumors spanning different tissue types across adult and pediatric tumors from patients with pre-cancer, primary tumors, and metastases, as well as resistant tumors before and after treatment. Projected ranges for the number of samples to be profiled over the 5-year HTAN period are depicted for each center and tumor type. In some cases, multiple samples will be profiled from the same patient. HTAN includes the following centers: Children’s Hospital of Philadelphia (CHOP), Dana-Farber Cancer Institute (DFCI), Oregon Health & Science University (OHSU), Washington University in St. Louis (WUSTL), Duke University School of Medicine, Pre-Cancer Atlas Pilot Project (PCAPP), Human Tumor Pilot Project (HTAPP), Vanderbilt University Medical Center (VUMC), Stanford University, Boston University (BU), Memorial Sloan Kettering Cancer Center (MSCKK), and Harvard Medical School (HMS).

Figure 5.. What We Can Learn from the Atlases and How to Query Them

(A and B) HTAN centers will combine clinical outcome and measurement data to (A) capture shared and unique characteristics and features across tumors—or subsets of tumors—and (B) associate them with “structural” features such as genes, molecules, cells, cellular interactions and structures, and histology. (C) By identifying features that correlate with clinical transitions and disease states, responses to treatment, and/or structural and molecular traits, tumor atlases will facilitate clinical and structural predictions according to query datasets.

Figure 6.. HTAN Will Have a Profound Impact on Cancer Biology and Medicine

The translational promise of a tumor cell atlas ranges from basic understanding of disease mechanisms, diagnosis, prognosis, treatment monitoring, drug development, biomarker discovery, and patient stratification and will ultimately facilitate an era of precision medicine.