Opening the “Black Box” of Liver Cancer Metastasis to the Lungs: Fudan Team’s Findings Published in Science

Metastasis of hepatocellular carcinoma (hereinafter referred to as "liver cancer") is a long-term unresolved clinical problem. About 25%-56% of patients develop extrahepatic metastasis, and the lung, as the most commonly involved distant target organ, accounts for 28%-55% of extrahepatic metastasis. The vast majority of disseminated tumor cells (Disseminated Tumor Cells, After DTC) enters the pulmonary circulation, it is quickly recognized and cleared by the innate immune system. Only a handful of dormant cells survive, gradually forming micro-metastasis, and eventually evolve into fatal macro-metastasis. However, the micro-metastasis stage is almost impossible to capture in clinical practice. How disseminated cells evade immune surveillance early and how they co-evolve with the lung microenvironment, and its complete spatiotemporal dynamic mechanism has always been a "black box" in the field of tumor metastasis.

In the early morning of July 31, Beijing time, a multidisciplinary team led by academicians Fan Jia, academician Zhou Jian, and deputy chief physician Sun Yunfan from Zhongshan Hospital, Fudan University, and researchers from the National Key Laboratory of Genome Multidimensional Analysis Technology, BGI Research Institute Wu Liang, Xu Xun, and Shanghai Dunhui Medical Dr. Peng Haixiang, and Professor Cang Yong from ShanghaiTech University published an online publication in Science entitled "Spatiotemporal Multi-Omics Uncover Tumor Ecosystem Dynamics" During Metastatic Colonization” research paper. This study integrated high-precision multi-omics technology to construct a spatio-temporal map of mouse liver cancer lung metastasis covering 9 consecutive time points. It completely restored the entire process of tumor cells from dissemination, dormancy, recovery and proliferation to macro-metastasis for the first time. It pioneered the division of metastasis and colonization into four temporal stages, and systematically clarified the co-evolution rules of tumor cells and the lung microenvironment in the spatio-temporal dimension.

Article published online (web version)

Article abstract (Graphical Abstract)

Scientific issues transition from "one-way linear regulation" to "system collaborative evolution"

Traditional metastasis research is deeply rooted in "reductionist" thinking and is accustomed to looking for a single driver gene or linear signaling pathway to construct a causal chain of "A molecule → B phenotype". However, this study revealed a more complex picture of metastasis: the fate of metastatic tumor cells is not determined unidirectionally by their internal genome, but is repeatedly shaped in a continuous "dialogue" with the lung microenvironment. Specifically, alveolar epithelial cells can actively "educate" DTCs into a dormant state, while tumor cells can also reversely reshape the immune microenvironment, actively build an immune "desert" niche, and recruit CX3CR1⁺ macrophages during the transition stage from micro-metastasis to macro-metastasis, which further recruit immunosuppressive cells and provide favorable "soil" for the growth of metastases. This two-way domestication and co-evolution of "you are part of me, and I am part of you" breaks the traditional framework of "tumor actively attacks and the microenvironment passively responds", and redefines metastatic colonization as a multi-cell participation, precise timing ecological evolution event, rather than a linear cascade reaction driven by a single gene.

Upgrading the research strategy from "static snapshot" to "space-time continuum"

If the above paradigm shift changes our understanding of "what metastasis is," another contribution of this study is to establish new strategies for "how to study metastasis." Previous work was mostly based on sampling of a few discrete time points in in vitro systems or in vivo, which is like using a few "snapshots" to restore a long movie, and a large amount of spatial neighborhood information and evolutionary transition states are lost. This study is the first to incorporate continuous time series and spatial microenvironment neighborhood as independent core variables into a systematic analysis framework - no longer satisfied with describing "what molecules are there at a certain time", but quantitatively tracking "when, where, and in what order they occur." This cognitive dimensionality upgrade from "two-dimensional classification" to "spatial-temporal continuum" enables researchers to no longer just ask "which target is important", but can also ask "at which stage and which spatial location intervention is most effective", pushing tumor metastasis research from the "fixed-frame analysis" of molecular biology to the "dynamic deduction" of spatio-temporal ecology.

Treatment concepts are updated, and the "timing" and "target" of metastasis prevention and treatment are equally important

Based on the above dynamic laws of space and time, the research team further proposed a new treatment concept with direct clinical guidance. Through lineage tracing, it was found that high expression of phosphoglycerate dehydrogenase (PHGDH) (PHGDHhigh) is a "transient adaptation" of DTC rather than an "intrinsic characteristic" - the vast majority of DTCs that eventually form macrometastasis have experienced the PHGDHhigh state, but once the metastasis grows, PHGDH expression is down-regulated. This profoundly suggests that anti-metastasis treatment must seize the "adaptive window period" of DTC. The study introduced a "dynamic intervention window" to verify: that is, targeting DTC epigenetic regulation (H3K27me3) in the micro-metastasis stage to reverse the "desert" niche, or clearing macrophages in the micro-macro-metastasis transition period can significantly inhibit the occurrence of metastasis, while intervention at other stages has little effect - the timing of intervention is as important as the intervention target. This discovery upgrades the clinical treatment strategy from "finding the target" to a two-dimensional decision-making of "target + timing".

In summary, this study incorporates time series and spatial interactions into a systematic analysis framework, and is no longer limited to the static two-dimensional framework of "genotype-phenotype". Instead, it uses time series and spatial interactions as independent variables to systematically reveal the phase transition rules of "bidirectional co-evolution" of tumor cells and microenvironment in continuous time and space; through dynamic intervention windows The verification proves that the timing of intervention is as important as the target of intervention, and reconstructs cancer metastasis from a "molecular biology problem" to a "spatiotemporal ecology and system dynamics problem" - this "discovery" paradigm driven by an independent big science platform marks the cognitive upgrade from "additive" single-gene stories to "topological" system dynamic laws. This study establishes PHGDH and CX3CR1⁺ macrophages as precise intervention targets for tumor micrometastases, provides a new strategy for establishing staged anti-metastasis treatment, fills the research gap in clinical intervention of latent micrometastases, and provides a new theoretical basis and clinical translation direction for anti-metastasis diagnosis and treatment of malignant tumors and stratified management and control of recurrence and metastasis risk.

The co-corresponding authors are Academicians Fan Jia and Zhou Jian and Associate Chief Physician Sun Yunfan of Zhongshan Hospital, Fudan University; researchers Wu Liang and Xu Xun of the State Key Laboratory of Genome Multidimensional Analysis Technology and BGI Life Sciences Research Institute; Dr. Peng Haixiang of Dunhui Medical; and Professor Cang Yong of ShanghaiTech University. The co-first authors are Associate Chief Physician Sun Yunfan, Dr. Zhang Zefan, Dr. Chen Junbing and Chief Physician Guo Wei of Zhongshan Hospital, Fudan University; Associate Researcher Zhong Yu, Dr. Liu Shang and Dr. Wang Chunqing of the Southwest BGI Life Sciences Research Institute; and Dr. Liu Yang of ShanghaiTech University.

Original URL: https://www.science.org/doi/10.1126/science.adz7928