China's π-HuB Bets Billions on Lifetime Proteome Prediction

China's Proteomic Navigator of the Human Body, π-HuB, expects investment running into billions of renminbi over three decades, according to a roadmap presented at World HUPO 2026 in Singapore, where 1,428 delegates from 45 countries gathered September 27 to October 1 under the theme "Proteomics Plus: Transforming Lives."

Fuchu He, PhD, chairman of the National Center for Protein Sciences in Beijing, opened the congress by setting out that ambition. Jing Yang, PhD, π-HuB's secretary-general and a researcher at Guangzhou National Laboratory, described an effort to profile organs, tissues, cell types and individuals, building a reference for how human biology changes across a lifetime.

The goal is to "predict the proteomic states of each person across their lifetime," Yang explained, accounting for the microbiome, immune system, environment and lifestyle. He was clear that reliable individual predictions remain a research goal, not a deliverable.

"We really want to collaborate with HUPO," Yang told GEN, describing discussions about extending cooperation beyond conferences into science and funding.

Can AI models guide experiments?

Tiannan Guo, PhD, a professor at Westlake University, connected spatial and perturbation proteomics with AI-based virtual cell modeling. His presentation covered proteomic work spanning 58 major tissue types, 251 more finely defined tissue types and 25 carcinoma types, plus a perturbation-based virtual cell model for triple-negative breast cancer with potential clinical benefits.

His framework brings together existing biological knowledge, cellular architecture and dynamic perturbation measurements: models guide experiments, and measurements refine the models. The Westlake AI Virtual Cell–Yeast (WAY) project divides the challenge into functions such as metabolism, membrane systems and stress responses, with task-specific AI agents working together. Contributors include researchers at ETH Zurich, Stanford University and the University of Toronto.

What does a cell actually endure?

Florian Rosenberger, PhD, a SciLifeLab fellow and assistant professor at Karolinska Institutet, studies mitochondrial disease with single-cell deep visual proteomics while preserving tissue context. "Life is all about being able to deal with the little fluctuations," he said, including "being able to deal with lunch without dying instantly."

His group isolates cells in different functional states and arranges them in pseudotime, reconstructing a possible progression rather than tracking one cell. He compared the patchwork of states to a Portuguese tile floor, and stressed the work is early. "What is the normal working range that a cell can have, and when does it tip over into disease?" he asked.

Fabian Coscia, PhD, head of the spatial proteomics group at the Max Delbrück Center in Berlin, showed that cancer cells can differ in treatment response, with rare populations carrying resistance-associated protein states before treatment begins. In Alzheimer's brain tissue, neurons with visible tau pathology and neighbors without it revealed intermediate states rather than clean separation. "You have an entire trajectory of states," Coscia said.

From tissue to accessible samples

Birgit Schilling, PhD, of the Buck Institute for Research on Aging, described spatial mass spectrometry applied to human osteoarthritis, finding localized bone changes that bulk analysis could obscure. "What I'm particularly excited about is that we took that to then bring that back to a biomarker fluid," she said, with follow-up work in synovial fluid.

Mitchell Lai, PhD, a senior lecturer at the National University of Singapore, tests Alzheimer's biomarkers in an Asian cohort with substantial cerebrovascular disease. Using NULISA technology, his assays recognize both a phosphorylation site and a brain-associated splice variant of tau. "Now we are more interested in prognostic biomarkers," he said, noting that longitudinal research requires comparable assays across samples collected years apart.

Jochen Schwenk, PhD, who chaired HUPO's Plasma Proteome Project for a decade, reported a substantial increase in biofluid studies of large cohorts, while cautioning against early conclusions without cross-checking similar studies. Gabriel Mazzucchelli, PhD, of the University of Liège, presented a sweat spectral library of roughly 4,000 proteins and an overnight collection patch that could allow repeated sampling without hospital visits.

What would a proteoform reference cost?

At the closed Day of the Research Initiatives, Neil Kelleher, PhD, of Northwestern University, proposed a reference set of intact protein forms across human cell types and body fluids, estimating 50–100 million distinct proteoforms. "It is a structural project more than a functional one," he said, estimating the effort at roughly 10 years and $300 million–$500 million annually.

Cecilia Lindskog, PhD, of Uppsala University, chairs HUPO's Human Protein Project and noted fewer than a third of human proteins have well-characterized, experimentally validated functions. "We want to determine the function of every human protein," she said, calling for shared standards, complementary methods and joint pilot studies.

Coscia added a caution: exploratory spatial proteomics remains largely a discovery technology, and some findings may reach the clinic through established methods such as immunohistochemistry. The test by next year's congress is whether these models perform on new data and whether candidate biomarkers hold up in larger, more diverse cohorts.