NEW YORK – Members of the Human Tumor Atlas Network (HTAN) have shared a set of new studies outlining the 3D features found in several cancer types and their microenvironments, providing a look at the molecular, cellular, and structural insights gained across more than 20 tumor origin sites since the HTAN effort kicked off in 2018.
In a paper published in Nature on Wednesday, for example, investigators at Washington University in St. Louis, Princeton University, and elsewhere presented findings from a spatial transcriptomic, single-nucleus RNA sequencing, and "co-detection by indexing" (CODEX) analysis of tumor samples from individuals with breast cancer, colorectal carcinoma, pancreatic ductal adenocarcinoma, renal cell carcinoma, uterine corpus endometrial carcinoma, or cholangiocarcinoma.
Based on Visium-based spatial transcriptomic data for 131 samples representing 78 cancer cases — together with snRNA-seq data for four dozen samples and 22 matched CODEX samples — the team unearthed cell clusters dubbed tumor microregions and subclonal structures found in specific cancer types and in metastatic cases.
These included subclones marked by specific mutation features or copy number variation (CNV) patterns, along with spatial interactions involving T cells, macrophages, or other immune cells interacting with the tumors, the researchers explained. With the help of machine learning, they were also able to distinguish between parts of the tumors with enhanced or decreased immune function or with markers linked to "immune exhaustion."
"Overall, this spatial omics approach provides deeper insights into clonal evolution and the microregional distinctions across six different solid tumor types, paving the way to continued advances in understanding the mechanisms of therapeutic resistance in cancer," co-senior and co-corresponding author Li Ding, a genetics researcher with Washington University's McDonnell Genome Institute and its Siteman Cancer Center, and her colleagues reported, adding that subclonal evolution appears to be a "major driver of therapeutic resistance."
For another Nature paper, an international team led by investigators at Vanderbilt University turned to multiomic analyses, single-cell genomics, and single-cell CRISPR editing to retrace tumor development and clonal dynamics in more than 400 sporadic human polyps and in mouse intestinal tumor models.
"Our multimodal framework, which pairs natural genetic changes in humans with induced genetic changes in the mouse, illuminates the complexities of cellular origins and temporal transitions, and their relevance in early tumorigenesis," Vanderbilt University researchers Ken Lau and Robert Coffey, the study's co-senior and co-corresponding authors, and their colleagues wrote.
Among other findings, members of that team saw signs that some 15 percent to 30 percent of precancerous colon lesions appeared to involve multiple progenitor cell types, rather than individual colon cells.
Meanwhile, in another Nature study, researchers with the Chinese Academy of Sciences, the University of Macau, Sun Yat-Sen University, and other centers in China took a closer look at the progression from precancerous lesions to colorectal cancer, using substitution mutation-aided lineage tracing, single-cell RNA-seq, exome sequencing, whole-genome sequencing, and other approaches.
"[O]ur data suggest that colorectal precancer is often founded by many different lineages and highlight their cooperative interactions in the earliest stages of cancer formation," the authors reported, noting that their analyses on genomic and clinical data "support a model of polyclonal-to-monoclonal transition, with monoclonal lesions representing a more advanced stage."
Within a set of nine other papers published in Nature, Nature Medicine, Nature Methods, Nature Cancer, and Communications Biology, HTAN investigators also explored familial adenomatous polyposis tumorigenesis or polyclonal tumor features within colorectal cancer cases involving mutant forms of the APC gene, single-cell mapping methods, and spatial genomic or chromatin accessibility features in breast cancer and metastatic breast cancer.