Multiomics analyses decipher intricate changes in the cellular and metabolic landscape of steatotic livers upon dietary restriction and sleeve gastrectomy DOI Creative Commons
Shuai Chen, Qinghe Zeng, Xiurong Cai

et al.

International Journal of Biological Sciences, Journal Year: 2024, Volume and Issue: 20(11), P. 4438 - 4457

Published: Jan. 1, 2024

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a chronic, progressive that encompasses spectrum of steatosis, steatohepatitis (or MASH), and fibrosis. Evidence suggests dietary restriction (DR) sleeve gastrectomy (SG) can lead to remission hepatic steatosis inflammation through weight loss, but it unclear whether these procedures induce distinct metabolic or immunological changes in MASLD livers. This study aims elucidate the intricate following DR, SG sham surgery rats fed high-fat diet as model obesity-related MASLD, comparison clinical cohort patients undergoing SG. Single-cell single-nuclei transcriptome analysis, spatial metabolomics, immunohistochemistry revealed landscape, while circulating biomarkers were measured serum samples. Artificial intelligence (AI)-assisted image analysis characterized distribution hepatocytes, myeloid cells lymphocytes. In experimental rats, improved body mass index, injury triglyceride levels. Both DR attenuated fibrosis rats. Metabolism-related genes (

Language: Английский

Advances in spatial transcriptomics and its applications in cancer research DOI Creative Commons
Huazhe Yang,

Yuanli Zuo,

Gang Li

et al.

Molecular Cancer, Journal Year: 2024, Volume and Issue: 23(1)

Published: June 20, 2024

Abstract Malignant tumors have increasing morbidity and high mortality, their occurrence development is a complicate process. The of sequencing technologies enabled us to gain better understanding the underlying genetic molecular mechanisms in tumors. In recent years, spatial transcriptomics been developed rapidly allow quantification illustration gene expression context tissues. Compared with traditional technologies, not only detect levels cells, but also inform location genes within tissues, cell composition biological interaction between cells. Here we summarize tools its application cancer research. We discuss limitations challenges current approaches, as well future prospects.

Language: Английский

Citations

23
Artificial intelligence in liver cancer — new tools for research and patient management DOI
Julien Caldéraro, Laura Žigutytė, Daniel Truhn

et al.

Nature Reviews Gastroenterology & Hepatology, Journal Year: 2024, Volume and Issue: 21(8), P. 585 - 599

Published: April 16, 2024

Language: Английский

Citations

12
Artificial intelligence applied to ‘omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment DOI Creative Commons
Soumita Ghosh, Xun Zhao,

Mouaid Alim

et al.

Gut, Journal Year: 2024, Volume and Issue: unknown, P. gutjnl - 331740

Published: Aug. 22, 2024

Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our progress towards personalised diagnosis, prognosis treatment strategies hepatology. This review provides a comprehensive overview of the current landscape AI methods used for analysis data liver diseases. We present an prevalence different levels across various diseases, as well categorise methodology studies. Specifically, we highlight predominance transcriptomic genomic profiling relatively sparse exploration other such proteome methylome, which represent untapped potential novel insights. Publicly available database initiatives The Cancer Genome Atlas International Consortium have paved way advancements diagnosis hepatocellular carcinoma. However, same availability large datasets remains limited Furthermore, application sophisticated to handle complexities multiomics requires substantial train validate models faces challenges achieving bias-free results with clinical utility. Strategies address paucity capitalise on opportunities discussed. Given global burden chronic it is imperative that multicentre collaborations be established generate large-scale early disease recognition intervention. Exploring advanced also necessary maximise these improve detection strategies.

Language: Английский

Citations

9
Lactate Drives Senescence-Resistant Lineages in Hepatocellular Carcinoma via Histone H2B Lactylation of NDRG1 DOI
Lu Li, Jinyun Dong,

Chunwei Xu

et al.

Cancer Letters, Journal Year: 2025, Volume and Issue: unknown, P. 217567 - 217567

Published: Feb. 1, 2025

Language: Английский

Citations

1
Mapping the landscape of biliary tract cancer in Europe: challenges and controversies DOI Creative Commons
Lorenza Rimassa, Shahid A. Khan, Bas Groot Koerkamp

et al.

The Lancet Regional Health - Europe, Journal Year: 2025, Volume and Issue: 50, P. 101171 - 101171

Published: Feb. 19, 2025

Biliary tract cancer (BTC) is becoming more common worldwide, with geographic differences in incidence and risk factors. In Europe, BTC may be associated primary sclerosing cholangitis, lithiasis, liver cirrhosis, but frequently observed as a sporadic disease. increasingly affects patients under 60 years, resulting significant social economic burden. Early diagnosis remains challenging due to vague symptoms 50% of BTC, lack specific biomarkers, late presentation poor prognosis. The identification at increased reliable biomarkers require collaborative efforts make faster progress. This Series paper highlights the disparities access diagnostic tools multidisciplinary care particularly economically disadvantaged regions, while identifying priority areas for improvement. Addressing these inequities requires harmonised guidelines, accelerated pathways curative treatments, improved awareness among healthcare professionals public. Multidisciplinary teams (MDTs) are crucial improving patient outcomes, yet inconsistencies exist their implementation not only between different countries, also centres within country. Collaboration standardisation treatment protocols across Europe essential effectively address management BTC.

Language: Английский

Citations

1
Focal liver lesion diagnosis with deep learning and multistage CT imaging DOI Creative Commons

Yi Wei,

Meiyi Yang, Meng ZHANG

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Aug. 15, 2024

Diagnosing liver lesions is crucial for treatment choices and patient outcomes. This study develops an automatic diagnosis system using multiphase enhanced computed tomography (CT). A total of 4039 patients from six data centers are enrolled to develop Liver Lesion Network (LiLNet). LiLNet identifies focal lesions, including hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), metastatic tumors (MET), nodular hyperplasia (FNH), hemangioma (HEM), cysts (CYST). Validated in four external clinically verified two hospitals, achieves accuracy (ACC) 94.7% area under the curve (AUC) 97.2% benign malignant tumors. For HCC, ICC, MET, ACC 88.7% with AUC 95.6%. FNH, HEM, CYST, 88.6% 95.9%. can aid clinical diagnosis, especially regions a shortage radiologists. The distinction critical accurate cancer. Here, authors LiLNet, deep learning-based identify as well tumours CT images high across multiple cohorts.

Language: Английский

Citations

7
Combined hepatocellular-cholangiocarcinoma: from genesis to molecular pathways and therapeutic strategies DOI Creative Commons
Simona Gurzu,

Rita Szodorai,

Ioan Jung

et al.

Journal of Cancer Research and Clinical Oncology, Journal Year: 2024, Volume and Issue: 150(5)

Published: May 23, 2024

Abstract Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most common primary liver cancers. Little is known about combined hepatocellular-cholangiocarcinoma (cHCC-ICC) variant proper therapeutic strategies. Out of over 1200 available studies cHCC-ICC, we selected representative ones that reflected updated information with application to individualized therapy. Based on literature data own experience, hypothesize two molecular groups cHCC-ICC can be identified. The proposed division might have a significant role. Most cases develop, like HCC, background cirrhosis hepatitis share characteristics HCC; thus, they named HCC-type strategies those for HCC. This review also highlights new carcinogenic perspective identifies, based second called ICC-type cHCC-ICC. Contrary these show tendency lymph node metastases ICC components in metastatic tissues. No guidelines been established yet such cases. Individualized therapy should be, however, oriented toward immunoprofile tumor cells, different used patients HCC- versus

Language: Английский

Citations

6
Deep learning for liver cancer histopathology image analysis: A comprehensive survey DOI
Haoyang Jiang, Yimin Yin, Jinghua Zhang

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 133, P. 108436 - 108436

Published: April 18, 2024

Language: Английский

Citations

4
Use of Artificial Intelligence for Liver Diseases: A Survey from the EASL Congress 2024 DOI Creative Commons
Laura Žigutytė, Thomas Sorz, Jan Clusmann

et al.

JHEP Reports, Journal Year: 2024, Volume and Issue: 6(12), P. 101209 - 101209

Published: Sept. 6, 2024

Language: Английский

Citations

4
Spatial‒temporal heterogeneities of liver cancer and the discovery of the invasive zone DOI Creative Commons
Jiayan Yan, Zhifeng Jiang, Shiyu Zhang

et al.

Clinical and Translational Medicine, Journal Year: 2025, Volume and Issue: 15(2)

Published: Feb. 1, 2025

Solid tumours are intricate and highly heterogeneous ecosystems, which grow in invade normal organs. Their progression is mediated by cancer cells' interaction with different cell types, such as immune cells, stromal cells endothelial the extracellular matrix. Owing to its high incidence, aggressive growth resistance local systemic treatments, liver has particularly mortality rates worldwide. In recent decades, spatial heterogeneity garnered significant attention an unfavourable biological characteristic of tumour microenvironment, prompting extensive research into role development. Advances omics have facilitated detailed analysis states cell‒cell interactions, allowing a thorough understanding temporal heterogeneities microenvironment informing development novel therapeutic approaches. This review illustrates latest discovery invasive zone, systematically introduced specific macroscopic heterogeneities, pathological cancer.

Language: Английский

Citations

0