Nanjing Gulou Hospital Licenses Hepatocellular Carcinoma Molecular Subtyping Gene Panel Technology for Up to RMB 2.6 Million
Recently, Nanjing Drum Tower Hospital released a public notice on the conversion of scientific and technological achievements. The hospital plans to transfer these achievements through negotiated pricing.“Molecular Subtyping Gene Panels for Hepatocellular Carcinoma: Diagnostic Products and Applications”Relevant patents are licensed to industry partners. The total licensing fees shall not exceed RMB2.6 million yuan, specifically including an upfront fee of RMB 100,000, milestone bonuses of RMB 300,000, and sales royalties capped at RMB 2.2 million. The inventor of this patented technology is from Nanjing Drum Tower HospitalProfessor Yu Decai and his teamIt is understood that the project was provided with full-process technology transfer services by the team of technology managers from the Nanjing Institute of Translational Medicine (Nanjing Cuizhi Medical).
Yu Decai:Ph.D. in Surgery from Nanjing University, currently serving as the Administrative Director and Chief Physician of the Department of Hepatobiliary Surgery and Liver Transplantation at Nanjing Drum Tower Hospital, as well as Professor and Doctoral Supervisor at Nanjing University. He obtained his bachelor’s, master’s, and doctoral degrees in Surgery from the Medical School of Nanjing University in 2008, and earned a Master’s degree in Clinical Research from the Medical University of South Carolina in the United States in 2012. He has undertaken advanced training in hepatobiliary surgery and liver transplantation techniques at Queen Mary Hospital in Hong Kong, the Medical University of South Carolina in the United States, and Asan Medical Center in South Korea. Since 2002, he has successively served as a Resident Physician, Attending Physician, and Associate Chief Physician at Nanjing Drum Tower Hospital, and was promoted to Chief Physician and Professor in 2019. He has presided over five projects funded by the National Natural Science Foundation of China, and his research achievements have received two provincial/ministerial-level science and technology progress awards, including the First Prize of the Jiangsu Provincial Science and Technology Award. He has published more than 100 papers in journals such as Hepatology and Gut, and served as the editor-in-chief for two monographs, including Laparoscopic Liver Resection: The Glissonian Pedicle Approach. He proposedConcept of Anatomical Liver Resection via the Laennec Approach, specializing in laparoscopic liver resection and liver transplantation, and conducting research on molecular subtyping of fatty acid metabolism in hepatocellular carcinoma.Selected as a Tier II Talent under Jiangsu Province’s “333 Project” and as a High-Level Talent under Jiangsu Province’s “Six Major Talent Peaks.”
The assignee of this patent is an innovative biotechnology company focused on oncology diagnostics and precision medicine. Its business layout centers on “R&D of molecular diagnostic reagents for tumors, clinical testing services, and support for personalized treatment plans,” dedicated to translating cutting-edge scientific achievements into clinically applicable diagnostic products, thereby filling market gaps in the fields of precise tumor subtyping and efficacy prediction.
The patent provides gene panels for molecular subtyping of hepatocellular carcinoma, along with diagnostic products and applications. By detecting gene expression, serum metabolites, or protein abundance, patients are classified into F1–F3 subtypes, enabling rapid subtyping and prediction of therapeutic efficacy.
Hepatocellular carcinoma (HCC), as a high-incidence and high-risk malignant tumor in China, has long faced challenges in its treatment“High heterogeneity leads to significant variations in treatment efficacy, while the lack of subtype guidance hinders precise decision-making”This core challenge. Although treatment modalities such as surgical resection, transarterial chemoembolization (TACE), targeted therapy (sorafenib), immunotherapy (anti-PD-1/PD-L1), and the “T + A” combination regimen have been continuously optimized and upgraded, significantly improving prognosis for some patients, the overall 5-year survival rate for liver cancer patients remains only around 20%. There is an urgent clinical need to break through the bottlenecks in diagnosis and treatment.
From the perspective of treatment regimen selection, the current diagnosis and treatment of liver cancer are mainly based onClinical Staging Systems (e.g., BCLC Staging). However, patients at the same stage exhibit significant differences in their response to treatment and prognosis.
For example, some patients with advanced hepatocellular carcinoma rapidly develop resistance to sorafenib, while others derive long-term benefit from it; similarly, among patients undergoing transarterial chemoembolization (TACE), some experience significant tumor shrinkage, whereas others exhibit disease progression.
The core reason is that traditional staging relies solely on macroscopic indicators such as tumor size, number, and liver function, failing to reflect the deep-seated molecular characteristics of the tumor. This leads to a "one-size-fits-all" treatment approach that struggles to maximize therapeutic efficacy, and may even increase the risk of ineffective treatment and the medical burden due to a mismatch between the treatment regimen and the patient’s individual characteristics.
Molecular subtyping of tumors should have become the key to solving this problem; however, existing technologies still suffer from multiple limitations, making it difficult to implement them in clinical practice.
First, most molecular subtyping studies of liver cancer rely on clustering based on tumor-wide gene expression patterns, with classifiers encompassing a large number of non-specific genes and pathways.This not only results in structural complexity and increased difficulty in interpretation, but also lacks support from clear biological mechanisms, leading to low reproducibility across different research teams or testing platforms and preventing the establishment of unified standards.
Secondly, most existing classifications focus on the association between tumor biological behavior and prognosis, while overlooking their guiding value in the selection of treatment regimens.For instance, it can only determine whether the patient’s prognosis is favorable or unfavorable, but fails to clarify their sensitivity to specific therapies such as sorafenib and PD-1 inhibitors, thereby limiting its clinical significance.
More critically,Existing molecular subtyping techniques suffer from the drawbacks of “high operational barriers and limited applicability.”Most protocols rely on tumor tissue samples, which must be obtained through invasive liver needle biopsy or surgical resection. This not only causes pain and carries risks of complications such as bleeding and infection for patients, but also makes it difficult to apply to patients with advanced-stage disease who are ineligible for surgery or face high risks from needle biopsy. Although a few techniques have attempted to perform subtyping using blood samples, they suffer from issues such as insufficient detection accuracy and low specificity of metabolite/protein biomarkers, failing to precisely distinguish different molecular subtypes. As a result, these methods have garnered academic interest but seen limited clinical adoption.
Furthermore,Existing diagnostic products still face the problem of "disconnection between subtyping and therapeutic efficacy prediction."Some liver cancer detection kits can only measure traditional tumor markers such as AFP, failing to provide subtype information or inform physicians which treatment approach is more suitable for patients with a specific subtype. This situation, in which molecular subtyping is possible but does not guide therapy, limits the practical utility of molecular subtyping technologies and fails to meet the core needs of precision diagnosis and treatment of liver cancer.
In clinical practice, the molecular subtyping of liver cancer faces pain points such as “complex classification, reliance on invasive sampling, and inability to guide treatment,” which has driven the team to pursue technological innovation. The patented technology being translated in this instance, “Gene Panel for Molecular Subtyping of Hepatocellular Carcinoma and Diagnostic Product,” uses“Classification Logic Centered on Fatty Acid Metabolism (FAM)” and “Dual-Track Diagnosis via Tissue and Liquid Biopsies”Develop a comprehensive solution that achieves breakthroughs across all dimensions—including classification criteria, testing scenarios, and efficacy prediction—thereby overcoming the limitations of traditional liver cancer diagnosis and treatment, which rely heavily on clinical staging.
This technology has pioneered disruptive innovation in subtyping logic—breaking through the complex paradigm of traditional whole-genome clustering, and pioneeringConstructed a “42-gene fatty acid degradation pathway” classification systemTraditional molecular subtyping largely relies on differentially expressed genes between tumor and normal tissues, which encompass numerous non-specific pathways. This not only complicates interpretation but also results in low reproducibility across different platforms. In contrast, our team focused on the well-defined biological mechanism of fatty acid metabolism and identified 42 key genes, including ACAA1, ACAA2, and ACADL. By detecting the mRNA or protein expression levels of these genes in tumor tissues and applying consensus clustering, patients can be precisely stratified into three subtypes: F1, F2, and F3. These subtypes exhibit significant differences in fatty acid metabolic activity:The F1 subtype exhibits the lowest activity, followed by the F2 subtype, while the F3 subtype shows the highest activity.
This classification logic, based on well-defined pathways, not only ensures the stability of the classification results (demonstrating reproducibility across multiple datasets such as TCGA and ICGC) but also directly correlates with tumor biological characteristics, thereby laying the foundation for subsequent therapeutic efficacy prediction.
AtDiagnostic Product DesignIn terms of aspects, this technological innovation has created"Tissue Testing + Liquid Biopsy"multi-scenario solutions to meet diverse clinical needs.
First, a PCR chip kit has been developed for patients whose tumor tissues can be obtained via surgery or needle biopsy. Leveraging real-time quantitative PCR (qPCR) technology, this kit detects the expression levels of 42 genes at the transcriptional level. Compatible with any real-time qPCR instrument, the kit enables simultaneous testing of two samples. It requires no complex pre-processing, features a streamlined experimental workflow, and delivers rapid results, making it ideally suited for routine testing in hospital clinical laboratories. Furthermore, it eliminates the reliance on large-scale equipment associated with traditional whole-genome testing, thereby lowering the adoption threshold for healthcare institutions.
Secondly, two types of liquid biopsy kits were innovatively developed for advanced-stage patients from whom tumor tissue cannot be obtained, or for populations requiring non-invasive monitoring.
One type of kit achieves subtyping by detecting the abundance of 20 specific metabolites in peripheral blood serum (e.g., Proline betaine corresponding to the F1 subtype, and Notoginsenoside T2 corresponding to the F3 subtype), combined with single-sample gene set enrichment analysis (ssGSEA) scores. Another type of kit completes subtyping by measuring the abundance of 20 proteins in serum, such as EZR and AFP.
Both types of test kits require no invasive procedures, onlySmall volume of serum samplesThe detection can be completed. Experimental validation has demonstrated that the metabolite-based subtyping accuracy reaches92.7%, the accuracy rate of protein-based subtyping reached95.1%, and the testing process does not require specialized pathological analysis. This significantly expands the eligible population for molecular subtyping, particularly offering the possibility of precise subtyping for elderly patients and those with advanced-stage disease who cannot tolerate biopsy.
The most core breakthrough of this technology lies in“Deep integration of subtyping with efficacy prediction” to achieve the clinical value of “subtyping as treatment guidance.”Extensive clinical data and animal model validation have now clarified the sensitivity of each subtype to different treatment regimens:F1 and F2 subtypes are sensitive to sorafenib and “T+A” (atezolizumab plus bevacizumab) therapy, whereas the F3 subtype is sensitive to transarterial chemoembolization (TACE); the F1 subtype exhibits the most favorable response to anti-PD-1/PD-L1 immunotherapy.
This clear association between “subtype and therapeutic efficacy” has fundamentally transformed the blind approach of traditional “stage-based regimen selection.” For instance, among patients with advanced hepatocellular carcinoma, those classified as subtype F1 may be prioritized for PD-1 inhibitor therapy, whereas those with subtype F3 are better suited for transarterial chemoembolization (TACE). This advancement opens new avenues for personalized diagnosis and treatment tailored to each individual patient.
Furthermore, this technology also possesses“Balancing High Accuracy with Practicality”advantages. On one hand, the subtyping results have been validated through multicenter studies: they consistently distinguish subtypes and accurately predict prognosis (with F1 subtype having the worst prognosis and F3 subtype having the best) in a cohort of 41 patients at Nanjing Drum Tower Hospital, public datasets such as TCGA, and patient-derived xenograft (PDX) models. On the other hand, the diagnostic products are user-friendly: the PCR chip kit requires no complex sample processing, and the testing workflow of the liquid biopsy kit is standardized. General laboratory personnel can perform the tests after brief training, eliminating the reliance on specialized bioinformatics analysis teams required by traditional molecular subtyping, thereby facilitating promotion and application in primary care hospitals.
In the field of precision diagnosis and treatment for hepatocellular carcinoma (HCC), centered on the core need for “molecular subtyping-guided individualized therapy,” multiple companies have deployed strategies along diverse technological pathways, forming a competitive landscape characterized by “upgrading traditional biomarker testing plus exploring innovative subtyping technologies.”
Currently, similar products on the market primarily focus on tumor marker detection and the development of multi-omics subtyping tools. With varying R&D progress and product positioning across different companies, these efforts are collectively advancing liver cancer diagnosis and treatment from “clinical staging” to “molecular precision subtyping.”
From the perspective of traditional tumor marker testing,Roche DiagnosticsAs a leading foreign-funded enterprise, its core products“Alpha-fetoprotein (AFP) Assay Kit (Electrochemiluminescence Method)”Widely adopted in clinical practice, this product aids in the diagnosis of liver cancer by detecting serum AFP concentrations. It has obtained dual certification from the NMPA and CE, offering advantages of high sensitivity (limit of detection: 0.5 ng/mL) and a wide linear range (0–1210 ng/mL). Currently, it is in a mature stage of market promotion with high penetration.
In the field of multi-omics typing tools，Burning Rock BiotechAs a representative enterprise of precision oncology medicine in China, providing“Multi-Gene NGS Testing Service for Liver Cancer (LDT Model)”, this product is based on NGS technology and can detect mutations in 20 liver cancer driver genes, including TP53 and CTNNB1, while simultaneously achieving molecular subtyping of tumors by combining methylation site analysis.
In recent years, non-invasive detection approaches have also garnered significant attention. Some research institutions and third-party platforms are exploring the use of technologies such as liquid chromatography–mass spectrometry (LC-MS) to analyze changes in the abundance of specific metabolites (e.g., glycerophospholipids and sphingolipids) in serum, thereby constructing liver cancer subtyping models. While these methods offer potential advantages, including convenient sampling and high patient compliance, they remain in the research or early validation stage due to limitations related to metabolite stability, standardization of detection platforms, and the accumulation of clinical validation data. Further prospective studies are needed to confirm the association between subtyping results and responses to different treatment regimens.