[China Tech] Unraveling Drug Resistance & Prognostic Codes for the 'King of Cancers'

China Tech is a column dedicated to the innovations reshaping China – and, inevitably, the world. From cutting-edge AI labs and next-generation robotics to apps that redefine daily life, we explore the breakthroughs that emerge from the country's relentless drive for technological dominance. Some are game-changers, others cautionary tales, but all offer a glimpse into the future as it's being built, at breakneck speed, in China.

Local scientists have identified treatment resistance drivers and prognostic indicators for pancreatic cancer, the "king of cancers."

The first cell-type-resolution platform for pancreatic cancer prognostic assessment and therapeutic target discovery, ctPANDA, is now available to researchers worldwide.

About 90 percent of pancreatic cancer cases are pancreatic ductal adenocarcinoma (PDAC), which has high aggressiveness, low survival rates, few actionable therapeutic targets, and therapy resistance, leaving patients with few salvage alternatives.

Experts spent five years building ctPANDA by breaching bulk tumor sequencing constraints under Dr Yu Xianjun, president of Fudan University Shanghai Cancer Center.

New research tools on the open-access public platform let scientists worldwide find promising treatment targets and prognostic signatures for this deadly disease.

Cancer Cell, a leading oncology magazine, released significant findings on Thursday.

According to official figures, the global 5-year survival rate for PDAC is only 13 percent. Patients who undergo curative surgical resection have a median survival rate of 20 months.

A major obstacle to improving survival rates is the lack of effective therapeutic targets. Most patients eventually experience disease progression due to chemotherapy resistance and a limited availability of alternative targeted therapies.

For decades, researchers have relied on bulk tissue sequencing to analyze tumor gene expression, treating malignancies as a black box and overlooking the intratumoral heterogeneity.

"A tumor is far more than a solid mass; it functions as a complex cellular ecosystem made up of cancer cells, immune cells, stromal cells, and dozens of other cell subsets," said Yu Xianjun.

Bulk sequencing obscures molecular characteristics across different cell populations, concealing genes that are crucial for patient survival and therapy responsiveness, which complicates the identification of targets for PDAC.

To address this unmet clinical need, the research team developed a gene expression-survival atlas that includes 23 cell types. This atlas was created using high-precision single-nucleus RNA sequencing data along with long-term clinical follow-up information from 152 PDAC patients.

The researchers created ctPANDA, the first cell-type-specific PDAC prediction and target mining platform, using this high-resolution atlas.

For instance, researchers can ask whether genes overexpressed in cancer cells have a poor prognosis or which immune-cell-enriched genes indicate prolonged patient survival. With our whole dataset, the platform automatically finds matches.

Yu said the free public resource will speed pancreatic cancer drug development and precision medicine upgrades, boosting translational research between fundamental science and clinical practice worldwide.

Traditional techniques miss cell-specific prognostic indicators and therapeutic possibilities, but the ctPANDA platform reveals disease-driving and treatment-responsive genes.

The platform was used to discover PDAC's initial "dual-role genes." Overexpression of CD44 in cancer cells promotes tumor growth and a poor prognosis, yet high CD44 levels in T immunological cells improve anti-tumor immunity and prolong longevity.

The discovery warns medication developers not to harm immune cells while eliminating cancer cells.

The researchers removed pan-cellular target PLOD2, which is upregulated across multiple cell subsets and predicts poor patient outcomes, to target persistent chemotherapy resistance.

Targeted PLOD2 inhibition showed strong anti-tumor activity in functional validations.

Using spatial transcriptomics, local researchers found a triple-complex of three harmful cell types that causes neoadjuvant therapy resistance, providing a new approach to PDAC treatment failure.

The launch of ctPANDA marks a milestone shift in pancreatic cancer and broader solid tumor research toward single-cell resolution, representing a major leap forward in our understanding of tumor biology within the precision medicine era.