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Novel Perspectives in Hepato-Biliary and Pancreatic Cancer

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 2383

Special Issue Editors


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Guest Editor
UBBMed Department, Babeș-Bolyai University, 400349 Cluj-Napoca, Romania
Interests: HCC; ERCP; tumor ablation; prognosis; molecular markers

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Guest Editor
1. Regional Institute of Gastroenterology and Hepatology “Octavian Fodor”, 400162 Cluj-Napoca, Romania
2. Department of General Surgery, University of Medicine and Pharmacy “Iuliu Hațieganu”, 400347 Cluj-Napoca, Romania
Interests: surgery; liver resection; DPC

Special Issue Information

Dear Colleagues,

Pancreatic and hepatobiliary tumors continue to rank among the deadliest cancers worldwide. Due to a low response rate to treatment, these tumors continue to have a high death rate, a poor prognosis and survival rate, and an overall poor patient outcome. The multimodal strategy currently used in treatment includes systemic therapy, radiation therapy, and surgery. The treatment of hepatobiliary pancreatic cancer is under investigation in a variety of fields.

The use of immunotherapy in hepatobiliary pancreatic tumors is crucial and presents a rapidly developing field of study in cancer treatment. The most recent developments in checkpoint inhibitors, CAR-T cell therapy, and cancer vaccines are among the immunotherapy areas used to treat hepatobiliary and pancreatic malignancies; their clinical effectiveness and potential to increase survival rates are being examined. Targeted therapy, which emphasizes molecularly targeted medicines and precision medicine techniques based on genetic profiling, is another option. These tactics have the ability to customize care for specific patients, improving therapeutic results and reducing side effects.

In recent years, increasingly more patients have become eligible for combination therapies, which combine immunotherapy and targeted therapy with more conventional forms of treatment. Such combinations' synergistic effects have demonstrated promise in overcoming resistance and improving the effectiveness of treatment. Additionally, advancements in robotics and less invasive surgical methods are enhancing surgical results and shortening patient recovery periods. With the advancement of methods like image-guided radiation therapy (IGRT) and stereotactic body radiotherapy (SBRT), radiation treatment continues to evolve. These developments provide patients with hepatobiliary pancreatic tumors fresh hope by increasing the accuracy and efficacy of radiation therapy. Furthermore, enhancing prognoses requires the discovery of novel biomarkers for early detection and therapy monitoring.

Preoperative biliary drainage represents another important pillar and has a direct impact on the perioperative prognosis of patients with obstructive jaundice and significantly compromised liver function due to hepato-bilio-pancreatic malignancies. The development of a variety of preoperative biliary methods, from endoscopic stenting to percutaneous drainage methods and even surgical diversion, constitutes another field of interest.

To enhance the current knowledge and highlight new trends in hepato-billiary and pancreatic cancer management, this Special Issue aims to gather the most recent studies and clinical insights on these cutting-edge approaches. Original research, reviews, systemic reviews, and mini-reviews are all welcome.

Dr. Tudor Mocan
Dr. Emil-Ioan Moiș
Guest Editors

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Keywords

  • HCC
  • cholangiocarcinoma
  • surgery
  • biliary drainage
  • pancreatic cancer
  • combination therapies

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Published Papers (2 papers)

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Research

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18 pages, 538 KB  
Article
BALAD-2 Emerges as the Most Accurate Prognostic Model in Hepatocellular Carcinoma: Results from a Biobank-Based Cohort Study
by Coskun Ozer Demirtas, Fatih Eren, Demet Yilmaz Karadag, Yasemin Kaldirim Armutcuoglu, Tugba Tolu, Javid Huseyinov, Ugur Ciftci, Tuba Yilmaz, Sehnaz Akin, Feyza Dilber and Osman Cavit Ozdogan
Cancers 2025, 17(21), 3457; https://doi.org/10.3390/cancers17213457 - 28 Oct 2025
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Abstract
Background/Objectives: Accurate prognostication of hepatocellular carcinoma (HCC) remains essential for treatment selection and risk stratification. This study aimed to compare the prognostic performance of individual serum biomarkers and composite scoring models, including GALAD, BALAD, BALAD-2, GAAP, ASAP, the Doylestown algorithm, and aMAP, [...] Read more.
Background/Objectives: Accurate prognostication of hepatocellular carcinoma (HCC) remains essential for treatment selection and risk stratification. This study aimed to compare the prognostic performance of individual serum biomarkers and composite scoring models, including GALAD, BALAD, BALAD-2, GAAP, ASAP, the Doylestown algorithm, and aMAP, using data from a biobank-based HCC cohort. Methods: This study enrolled 186 patients with confirmed HCC diagnosed between 2019 and 2024. Serum biomarkers (AFP, AFP-L3%, DCP) and composite models were evaluated for their association with overall survival (OS). Prognostic performance was assessed using time-dependent area under the receiver operating characteristic curve (AUROC) at 1-, 2-, 3-, and 5-year intervals and Harrel’s concordance index (c-index). Subgroup analyses were performed based on treatment intent and liver disease etiology. Results: All three biomarkers and composite models were independently associated with OS in multivariate analyses (all p < 0.05). Among all models, BALAD-2 demonstrated the best overall performance (c-index: 0.737), with the highest AUROCs at 1 year (0.827), 2 years (0.846), 3 years (0.781), and 5 years (0.716). BALAD-2 consistently showed superior discrimination in patients treated with curative or noncurative therapies and in the viral etiology subgroup. In the non-viral etiology subgroup, BALAD-2 remained among the top performers, although the GAAP, ASAP, and Doylestown algorithms showed slightly higher metrics. Conclusions: BALAD-2 demonstrated consistent and robust prognostic performance compared with other biomarker-based and clinical models across different patient subgroups, particularly among those receiving curative therapy and viral etiologies. These findings support its integration into clinical risk stratification and decision-making for HCC management. Full article
(This article belongs to the Special Issue Novel Perspectives in Hepato-Biliary and Pancreatic Cancer)
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Review

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25 pages, 776 KB  
Review
Turning the Tide—Artificial Intelligence in the Evolving Landscape of Liver Cancer
by Cristiana Grapă, Tudor Mocan, Lavinia Patricia Mocan, Andrei Motofelea, Raluca Stănciulescu, Rareș Crăciun, Andrei Vârciu, Zeno Spârchez and Teodora Mocan
Cancers 2025, 17(18), 3003; https://doi.org/10.3390/cancers17183003 - 14 Sep 2025
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Abstract
Background/Objectives: Liver cancer is an exceedingly heterogeneous malignancy with high mortality rates, and despite extensive research, there have been no significant improvements in treatment outcomes. In the process of navigating the complex landscape of liver cancer, AI has arisen as the “knight in [...] Read more.
Background/Objectives: Liver cancer is an exceedingly heterogeneous malignancy with high mortality rates, and despite extensive research, there have been no significant improvements in treatment outcomes. In the process of navigating the complex landscape of liver cancer, AI has arisen as the “knight in shining armour”, sparking hope and offering invaluable insight into early detection, diagnosis, staging, treatment selection, and post-treatment surveillance. By integrating imaging, clinical, pathological, and molecular data, AI emerges as a transformative tool that offers unique opportunities to enhance patient care. Methods: A comprehensive literature search of PubMed and Scopus, was conducted using the terms “artificial intelligence,” “machine learning,” “deep learning,” “radiomics,” and “liver cancer.” Eligible studies included peer-reviewed original research applying AI to detection, diagnosis, prognosis, treatment planning, or surveillance of liver cancer. Key findings are organized along the clinical continuum. Results: Imaging-based AI models for tumor detection were the most advanced, with several achieving diagnostic accuracy above 90% in retrospective studies. Applications for treatment decision-making are emerging, but most remain at proof-of-concept stages. Generally, few of these innovations have progressed to large-scale clinical trials or received regulatory approval, slowing their integration into clinical practice. Conclusions: This narrative review highlights AI’s potential to transform liver cancer management and addresses the ethical, regulatory, and logistical barriers to its clinical adoption, serving as a call to action for integrating AI into practice to improve patient outcomes. Full article
(This article belongs to the Special Issue Novel Perspectives in Hepato-Biliary and Pancreatic Cancer)
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