Meningioma brain tumor detection and classification using hybrid CNN method and RIDGELET transform.

The detection of meningioma tumors is the most crucial task compared with other tumors because of their lower pixel intensity. Modern medical platforms require a fully automated system for meningioma detection. Hence, this study proposes a novel and highly efficient hybrid Convolutional neural network (HCNN) classifier to distinguish meningioma brain images from non-meningioma brain images. The HCNN classification technique consists of the Ridgelet transform, feature computations, classifier module, and segmentation algorithm. Pixel stability during the decomposition process was improved by the Ridgelet transform, and the features were computed from the coefficient of the Ridgelet. These features were classified using the HCNN classification approach, and tumor pixels were detected using the segmentation algorithm. The experimental results were analyzed for meningioma tumor images by applying the proposed method to the BRATS 2019 and Nanfang dataset. The proposed HCNN-based meningioma detection system achieved 99.31% sensitivity, 99.37% specificity, and 99.24% segmentation accuracy for the BRATS 2019 dataset. The proposed HCNN technique achieved99.35% sensitivity, 99.22% specificity, and 99.04% segmentation accuracy on brain Magnetic Resonance Imaging (MRI) in the Nanfang dataset. The proposed system obtains 99.81% classification accuracy, 99.2% sensitivity, 99.7% specificity and 99.8% segmentation accuracy on BRATS 2022 dataset. The experimental results of the proposed HCNN algorithm were compared with those of the state-of-the-art meningioma detection algorithms in this study.

Implementation of deep learning in liver pathology optimizes diagnosis of benign lesions and adenocarcinoma metastasis.

INTRODUCTION: Differentiation of histologically similar structures in the liver, including anatomical structures, benign bile duct lesions, or common types of liver metastases, can be challenging with conventional histological tissue sections alone. Accurate histopathological classification is paramount for the diagnosis and adequate treatment of the disease. Deep learning algorithms have been proposed for objective and consistent assessment of digital histopathological images. MATERIALS AND METHODS: In the present study, we trained and evaluated deep learning algorithms based on the EfficientNetV2 and ResNetRS architectures to discriminate between different histopathological classes. For the required dataset, specialized surgical pathologists annotated seven different histological classes, including different non-neoplastic anatomical structures, benign bile duct lesions, and liver metastases from colorectal and pancreatic adenocarcinoma in a large patient cohort. Annotation resulted in a total of 204.159 image patches, followed by discrimination analysis using our deep learning models. Model performance was evaluated on validation and test data using confusion matrices. RESULTS: Evaluation of the test set based on tiles and cases revealed overall highly satisfactory prediction capability of our algorithm for the different histological classes, resulting in a tile accuracy of 89% (38 413/43 059) and case accuracy of 94% (198/211). Importantly, the separation of metastasis versus benign lesions was certainly confident on case level, confirming the classification model performed with high diagnostic accuracy. Moreover, the whole curated raw data set is made publically available. CONCLUSIONS: Deep learning is a promising approach in surgical liver pathology supporting decision making in personalized medicine.

Tumor biology and immune infiltration define primary liver cancer subsets linked to overall survival after immunotherapy.

Primary liver cancer is a rising cause of cancer deaths in the US. Although immunotherapy with immune checkpoint inhibitors induces a potent response in a subset of patients, response rates vary among individuals. Predicting which patients will respond to immune checkpoint inhibitors is of great interest in the field. In a retrospective arm of the National Cancer Institute Cancers of the Liver: Accelerating Research of Immunotherapy by a Transdisciplinary Network (NCI-CLARITY) study, we use archived formalin-fixed, paraffin-embedded samples to profile the transcriptome and genomic alterations among 86 hepatocellular carcinoma and cholangiocarcinoma patients prior to and following immune checkpoint inhibitor treatment. Using supervised and unsupervised approaches, we identify stable molecular subtypes linked to overall survival and distinguished by two axes of aggressive tumor biology and microenvironmental features. Moreover, molecular responses to immune checkpoint inhibitor treatment differ between subtypes. Thus, patients with heterogeneous liver cancer may be stratified by molecular status indicative of treatment response to immune checkpoint inhibitors.

Stiff matrix induces exosome secretion to promote tumour growth.

Tissue fibrosis and extracellular matrix (ECM) stiffening promote tumour progression. The mechanisms by which ECM regulates its contacting cells have been extensively studied. However, how stiffness influences intercellular communications in the microenvironment for tumour progression remains unknown. Here we report that stiff ECM stimulates the release of exosomes from cancer cells. We delineate a molecular pathway that links stiff ECM to activation of Akt, which in turn promotes GTP loading to Rab8 that drives exosome secretion. We further show that exosomes generated from cells grown on stiff ECM effectively promote tumour growth. Proteomic analysis revealed that the Notch signalling pathway is activated in cells treated with exosomes derived from tumour cells grown on stiff ECM, consistent with our gene expression analysis of liver tissues from patients. Our study reveals a molecular mechanism that regulates exosome secretion and provides insight into how mechanical properties of the ECM control the tumour microenvironment for tumour growth.

Lung_PAYNet: a pyramidal attention based deep learning network for lung nodule segmentation.

Accurate and reliable lung nodule segmentation in computed tomography (CT) images is required for early diagnosis of lung cancer. Some of the difficulties in detecting lung nodules include the various types and shapes of lung nodules, lung nodules near other lung structures, and similar visual aspects. This study proposes a new model named Lung_PAYNet, a pyramidal attention-based architecture, for improved lung nodule segmentation in low-dose CT images. In this architecture, the encoder and decoder are designed using an inverted residual block and swish activation function. It also employs a feature pyramid attention network between the encoder and decoder to extract exact dense features for pixel classification. The proposed architecture was compared to the existing UNet architecture, and the proposed methodology yielded significant results. The proposed model was comprehensively trained and validated using the LIDC-IDRI dataset available in the public domain. The experimental results revealed that the Lung_PAYNet delivered remarkable segmentation with a Dice similarity coefficient of 95.7%, mIOU of 91.75%, sensitivity of 92.57%, and precision of 96.75%.

Use of Autoreactive Antibodies in Blood of Patients with Pancreatic Intraductal Papillary Mucinous Neoplasms (IPMN) for Grade Distinction and Detection of Malignancy.

(1) Background: A reliable non-invasive distinction between low- and high-risk pancreatic intraductal papillary mucinous neoplasms (IPMN) is needed to effectively detect IPMN with malignant potential. This would improve preventative care and reduce the risk of developing pancreatic cancer and overtreatment. The present study aimed at exploring the presence of autoreactive antibodies in the blood of patients with IPMN of various grades of dysplasia. (2) Methods: A single-center cohort was studied composed of 378 serum samples from patients with low-grade IPMN (n = 91), high-grade IPMN (n = 66), IPMN with associated invasive cancer (n = 30), pancreatic ductal adenocarcinoma (PDAC) stages T1 (n = 24) and T2 (n = 113), and healthy controls (n = 54). A 249 full-length recombinant human protein microarray was used for profiling the serum samples. (3) Results: 14 proteins were identified as potential biomarkers for grade distinction in IPMN, yielding high specificity but mediocre sensitivity. (4) Conclusions: The identified autoantibodies are potential biomarkers that may assist in the detection of malignancy in IPMN patients.

Reduced Rates of Post-Transplant Recurrent Hepatocellular Carcinoma in Non-Alcoholic Steatohepatitis: A Propensity Score Matched Analysis.

Non-alcoholic steatohepatitis (NASH)-related hepatocellular carcinoma (HCC) has become the second leading cause of HCC-related liver transplantation in the United States. This study investigated post-transplant recurrence and survival for patients transplanted for NASH-related HCC compared to non-NASH HCC etiologies. Retrospective review of the United Network for Organ Sharing (UNOS) Organ Procurement and Transplantation Network (OPTN) database identified 7,461 patients with HCC-1,405 with underlying NASH and 6,086 with non-NASH underlying diseases. After propensity score matching (PSM) to account for patient- and tumor-related confounders 1,175 remained in each group. Primary outcomes assessed were recurrence rate and recurrence-free survival. Recurrent malignancy at 5 years post-transplant was lower in NASH compared to non-NASH patients (5.80 vs. 9.41%, p = 0.01). Recurrence-free survival, however, was similar at 5 years between groups. Patients with NASH-related HCC were less likely to have post-transplant recurrence than their non-NASH counterparts, although recurrence-free survival was similar at 5 years.

The role of RNA binding proteins in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of overall cancer deaths worldwide with limited therapeutic options. Due to the heterogeneity of HCC pathogenesis, the molecular mechanisms underlying HCC development are not fully understood. Emerging evidence indicates that RNA-binding proteins (RBPs) play a vital role throughout hepatocarcinogenesis. Thus, a deeper understanding of how RBPs contribute to HCC progression will provide new tools for early diagnosis and prognosis of this devastating disease. In this review, we summarize the tumor suppressive and oncogenic roles of RBPs and their roles in hepatocarcinogenesis. The diagnostic and therapeutic potential of RBPs in HCC, including their limitations, are also discussed.

Single-cell biology uncovers apoptotic cell death and its spatial organization as a potential modifier of tumor diversity in HCC.

BACKGROUND AND AIMS: HCC is a highly aggressive and heterogeneous cancer type with limited treatment options. Identifying drivers of tumor heterogeneity may lead to better therapeutic options and favorable patient outcomes. We investigated whether apoptotic cell death and its spatial architecture is linked to tumor molecular heterogeneity using single-cell in situ hybridization analysis. APPROACH AND RESULTS: We analyzed 254 tumor samples from two HCC cohorts using tissue microarrays. We developed a mathematical model to quantify cellular diversity among HCC samples using two tumor markers, cyclin-dependent kinase inhibitor 3 and protein regulator of cytokinesis 1 as surrogates for heterogeneity and caspase 3 (CASP3) as an apoptotic cell death marker. We further explored the impact of potential dying-cell hubs on tumor cell diversity and patient outcome by density contour mapping and spatial proximity analysis. We also developed a selectively controlled in vitro model of cell death using CRISPR/CRISPR-associated 9 to determine therapy response and growth under hypoxic conditions. We found that increasing levels of CASP3+ tumor cells are associated with higher tumor diversity. Interestingly, we discovered regions of densely populated CASP3+ , which we refer to as CASP3+ cell islands, in which the nearby cellular heterogeneity was found to be the greatest compared to cells farther away from these islands and that this phenomenon was associated with survival. Additionally, cell culture experiments revealed that higher levels of cell death, accompanied by increased CASP3 expression, led to greater therapy resistance and growth under hypoxia. CONCLUSIONS: These results are consistent with the hypothesis that increased apoptotic cell death may lead to greater tumor heterogeneity and thus worse patient outcomes.

Evaluating Outcomes Related to Donor and Recipient Metabolic Environment: Macrosteatotic Allografts and Nonalcoholic Steatohepatitis.

The increasing prevalence of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) affects both recipient and donor populations in liver transplantation. Presently, it is unclear whether transplantation of macrosteatotic allografts is affected by the metabolic milieu of liver transplant recipients. This study investigates fatty liver disease at the intersection of donor and recipient. A retrospective review of the Organ Procurement and Transplantation database identified 5167 NASH and 26,289 non-NASH transplant recipients who received transplants from January 1, 2004, to June 12, 2020. A total of 12,569 donors had allografts with no macrosteatosis (<5%), 16,140 had mild macrosteatosis (5%-29%), and 2747 had moderate to severe macrosteatosis (≥30%). Comparing recipients with NASH to propensity score-matched (PSM) recipients without NASH demonstrated noninferior graft and patient survival up to 10 years in patients with NASH. Similar trends were observed in subgroup analyses of transplants within each strata of allograft macrosteatosis. Assessing allograft macrosteatosis specifically in the NASH population demonstrated that allografts with ≥30% macrosteatosis were associated with reduced early graft survival (30 days, 93.32% versus 96.54% [P = 0.02]; 1 year, 84.53% versus 88.99% [P = 0.05]) compared with PSM grafts with <30% macrosteatosis. Long-term graft survival at 5 and 10 years, however, was similar. The use of carefully selected macrosteatotic allografts can be successful in both recipients with NASH and recipients without NASH. The metabolic environment of patients with NASH does not appear to adversely affect outcomes with regard to the allograft when controlled for numerous confounders. It is, however, important to remain cognizant of the potential for high-risk macrosteatotic allografts to negatively affect outcomes.

Noninvasive risk stratification of intraductal papillary mucinous neoplasia with malignant potential by serum apolipoprotein-A2-isoforms.

Intraductal papillary mucinous neoplasms (IPMNs) are premalignant lesions of pancreatic cancer. An accurate serum biomarker, which allows earlier identification of asymptomatic individuals with high-risk for developing cancer, is of urgent need. Apolipoprotein A2-isoforms (apoA2-i) have previously been identified as biomarkers in pancreatic cancer. This study investigates a potential clinical application of the serum apoA2-i for risk stratification of IPMN and associated cancer. The concentrations of apoA2-i were retrospectively determined in 523 patient sera specimen, composed of 305 IPMNs with preinvasive lesions with different grades of dysplasia and invasive cancer, 140 pancreatic ductal adenocarcinoma, 78 with other cystic lesions and healthy controls cohorts, using an apoA2-i enzyme-linked immunosorbent assay kit. The diagnostic performance of serum apoA2-i was assessed and compared to routine clinical marker CA 19-9. ApoA2-i levels were significantly reduced in all IPMN samples regardless of stage compared to healthy controls. Receiver operating characteristic curve analysis of IPMNs with high-grade dysplasia and IPMN with associated carcinoma revealed the area under curve (AUC) of 0.91 and >0.94, respectively. The respective sensitivities were 70% and 83% with a specificity of 95%, and significantly higher than the gold standard biomarker CA 19-9. AUC values of apoA2-i for detecting IPMN-associated carcinoma of colloid and ductal subtypes were 0.990 and 0.885, respectively. ApoA2-i has the potential to early detect the risk of malignancy of patients with IPMN. The serological apoA2-i test in combination with imaging modalities could help improve the diagnosis of IPMN malignancy. Further validation in larger and independent international cohort studies is needed.

Tumor metabolism and associated serum metabolites define prognostic subtypes of Asian hepatocellular carcinoma.

Treatment effectiveness in hepatocellular carcinoma (HCC) depends on early detection and precision-medicine-based patient stratification for targeted therapies. However, the lack of robust biomarkers, particularly a non-invasive diagnostic tool, precludes significant improvement of clinical outcomes for HCC patients. Serum metabolites are one of the best non-invasive means for determining patient prognosis, as they are stable end-products of biochemical processes in human body. In this study, we aimed to identify prognostic serum metabolites in HCC. To determine serum metabolites that were relevant and representative of the tissue status, we performed a two-step correlation analysis to first determine associations between metabolic genes and tissue metabolites, and second, between tissue metabolites and serum metabolites among 49 HCC patients, which were then validated in 408 additional Asian HCC patients with mixed etiologies. We found that certain metabolic genes, tissue metabolites and serum metabolites can independently stratify HCC patients into prognostic subgroups, which are consistent across these different data types and our previous findings. The metabolic subtypes are associated with ß-oxidation process in fatty acid metabolism, where patients with worse survival outcome have dysregulated fatty acid metabolism. These serum metabolites may be used as non-invasive biomarkers to define prognostic tumor molecular subtypes for HCC.

Attachment of human adenovirus onto household paints.

Attachment of human adenovirus 40 (HAdV40) onto surfaces coated with three compositionally different household paints was evaluated experimentally and interpreted based on measured physicochemical properties of the paints. Polar, dispersive and electrostatic interactions between HAdV40 and the paints were predicted using the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) model. Quartz crystal microbalance (QCM-D) was used to quantify virus attachment to paints from 1 mM and 150 mM NaCl solutions, with the latter having the ionic strength of a typical respiratory fluid. Acrylic latex water-based, alkyd water-based, and alkyd oil-based paints were all determined to be highly hydrophobic (ΔGsws < - 48 mJ/m2). XDLVO modeling and preliminary QCM-D tests evaluated virus-paint interactions within and outside pH windows of favorable virus-paint electrostatic interactions. Hydrophobic and electrostatic interactions governed virus attachment while van der Waals interactions played a relatively minor role. In higher ionic strength solutions, the extent of virus attachment correlated with the free energy of virus-paint interfacial interaction, [Formula: see text] : more negative energies corresponded to higher values of the areal mass density of attached viruses. Hydrophobicity was the dominant factor in determining virus adhesion from high ionic strength solutions where electrostatic interactions were screened out. The hydrophobicity of paints, while desirable for minimizing moisture intrusion, also facilitates attachment of colloids such as viruses. The results call for new approaches to the materials design of indoor paints with enhanced resistance to virus adhesion. Paints so formulated should help reduce human exposure to viruses.

Simultaneous liver kidney allocation policy and the Safety Net: an early examination of utilization and outcomes in the United States.

Rates of simultaneous liver kidney (SLK) transplantation in the United States have progressively risen. On 8/10/17, the Organ Procurement and Transplantation Network implemented a policy defining criteria for SLK, with a "Safety Net" to prioritize kidney allocation to liver recipients with ongoing renal failure. We performed a retrospective review of the United Network for Organ Sharing (UNOS) database to evaluate policy impact on SLK, kidney after liver (KAL) and kidney transplant alone (KTA). Rates and outcomes of SLK and KAL transplants were compared, as was utilization of high-quality kidney allografts with Kidney Donor Profile Indices (KDPI) <35%. Here, SLK transplants comprised 9.0% and 4.5% of total postpolicy liver and kidney transplants compared to 10.2% and 5.5% prior. Policy enactment did not affect 1-year graft or patient survival for SLK and KAL populations. Less postpolicy SLK transplants utilized high-quality kidney allografts; in all transplant settings, outcomes using high-quality grafts remained stable. These findings suggest that policy implementation has reduced kidney allograft use in SLK transplantation, although both SLK and KAL rates have recently increased. Despite decreased high-quality kidney allograft use, SLK and KAL outcomes have remained stable. Additional studies and long-term follow-up will ensure optimal organ access and sharing.

Population genetic structure and demographic history of the dipterocarp species Anisoptera costata Korth revealed by microsatellite analysis.

MAIN CONCLUSION: Moderate levels of genetic diversity and differentiation of Anisoptera costata were determined. A population divergence occurred during Younger Dryas. The anthropogenic disturbance had significantly affected the genetic diversity of the species in low tropical forests. Anisoptera costata Korth, an endangered species, is mainly distributed in the lowland tropical forests of the Southeast region in Vietnam, which has not been explored for genetic diversity and demographic history. In this study, eight polymorphic microsatellite markers were used to analyze 232 wild trees of A. costata at nine different populations, representing the natural distribution range of the species in Vietnam. Genetic diversity within the populations was determined with mean values of 0.284 and 0.327 observed and expected heterozygosity, respectively, while genetic differentiation among populations was found with Weir and Cockerham index of 0.12 and Hedrick index of 1.38. These results indicated that habitat fragmentation by the anthropogenic disturbance may be the major factor for the low heterozygosity values and affected the number of alleles in all the targeted populations of A. costata in lowland tropical forests. Populations in the Central Southeast area had a higher level of genetic diversity than the populations in the Coastal and Western Southeast areas. The analysis of molecular variance showed that high genetic variation existed within populations (86.15%) compared to the variation among populations. A reduction in the population size of A. costata was determined by BOTTLENECK. Different clustering methods (Bayesian analysis, the neighbor-joining tree, and principal coordinate analysis) suggested optimal genetic clusters related to gene flow among different areas. Approximate Bayesian computation suggested that population divergence occurred during Younger Dryas. We also discussed the measures for species conservation based on these results.

Intratumoral γδ T-Cell Infiltrates, Chemokine (C-C Motif) Ligand 4/Chemokine (C-C Motif) Ligand 5 Protein Expression and Survival in Patients With Hepatocellular Carcinoma.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is an aggressive malignancy which is often associated with a complex tumor microenvironment attributable to etiology-induced cellular inflammation. γδ T cells are known to detect and react to chronic inflammation, which is linked to cancer development, progression, and metastasis. Our recent genomic study revealed an increased infiltration of several immune cell types, including γδ T cells, in tumor microenvironments of a Thai HCC subtype associated with a good prognosis. APPROACH AND RESULTS: Here, we quantified the amount of γδ T cells using a γδ T-cell-specific gene signature in 247 Chinese HCC patients. We also validated the γδ T-cell signature in American HCC patients. Additionally, such an association was only found in tumor transcriptomic data, but not in adjacent nontumor transcriptomic data, suggesting a selective enrichment of γδ T cells in the tumor microenvironment. Moreover, the γδ T-cell signature was positively correlated with the expression of natural killer cell receptor genes, such as NKG2D and cytolytic T-cell genes granzymes and perforin, suggesting a stronger T-cell-mediated cytotoxic activity. Furthermore, we found that the γδ T-cell-specific gene expression is positively correlated with the expression of chemokine (C-C motif) ligand 4 (CCL4)/chemokine (C-C motif) ligand 5 (CCL5) and C-C chemokine receptor type 1 (CCR1)/C-C chemokine receptor type 5 (CCR5), the receptors for γδ T cells. We validated these results using immunohistochemical analysis of formalin-fixed, paraffin-embedded tumor biopsies from 182 HCC patients. Moreover, we found evidence of CCL4/CCL5-mediated recruitment of γδ T cells both in vitro and in a murine orthotopic Hepa1-6 HCC model. CONCLUSIONS: We propose that CCL4/CCL5 may interact with their receptor, CCR1/CCR5, which may facilitate the recruitment of γδ T cells from peripheral blood or peritumor regions to the tumor regions. Consequently, an increasing infiltration of γδ T cells in tumors may enhance antitumor immunity and improve patients' prognosis.

Serum IL6 as a Prognostic Biomarker and IL6R as a Therapeutic Target in Biliary Tract Cancers.

PURPOSE: Biliary tract cancer (BTC) is a heterogeneous group of rare gastrointestinal malignancies with dismal prognosis often associated with inflammation. We assessed the prognostic value of IL6 and YKL-40 compared with CA19-9 before and during palliative chemotherapy. We also investigated in mice whether IL6R inhibition in combination with gemcitabine could prolong chemosensitivity. EXPERIMENTAL DESIGN: A total of 452 Danish participants with advanced (locally advanced and metastatic) BTC were included from six clinical trials (February 2004 to March 2017). Serum CA19-9, IL6, and YKL-40 were measured before and during palliative treatment. Associations between candidate biomarkers and progression-free survival (PFS) and overall survival (OS) were analyzed by univariate and multivariate Cox regression. Effects of inhibiting IL6R and YKL-40 were assessed in vitro, and of IL6R inhibition in vivo. RESULTS: High pretreatment levels of CA19-9, IL6, and YKL-40, and increasing levels during treatment, were associated with short PFS and OS in patients with advanced BTC. IL6 provided independent prognostic information, independent of tumor location and in patients with normal serum CA19-9. ROC analyses showed that IL6 and YKL-40 were predictive of very short OS (OS < 6 months), whereas CA19-9 was best to predict OS > 1.5 years. Treatment with anti-IL6R and gemcitabine significantly diminished tumor growth when compared with gemcitabine monotherapy in an in vivo transplant model of BTC. CONCLUSIONS: Serum IL6 and YKL-40 are potential new prognostic biomarkers in BTC. IL6 provides independent prognostic information and may be superior to CA19-9 in certain contexts. Moreover, anti-IL6R should be considered as a new treatment option to sustain gemcitabine response in patients with BTC.

Hepatocellular Carcinoma-The Influence of Immunoanatomy and the Role of Immunotherapy.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related morbidity and mortality worldwide. Most patients are diagnosed with advanced disease, limiting their options for treatment. While current treatments are adequate for lower staged disease, available systemic treatments are limited, with marginal benefit at best. Chimeric antigen receptor (CAR) T cell therapy, effective in treating liquid tumors such as B-cell lymphoma, presents a potentially promising treatment option for advanced HCC. However, new challenges specific to solid tumors, such as tumor immunoanatomy or the immune cell presence and position anatomically and the tumor microenvironment, need to be defined and overcome. Immunotherapy currently in use must be re-engineered and re-envisioned to treat HCC with the hopes of ushering in an answer to advanced stage solid tumor disease processes. Future therapy options must address the uniqueness of the tumors under the umbrella of HCC. This review strives to summarize HCC, its staging system, current therapy and immunotherapy medications currently being utilized or studied in the treatment of HCC with the hopes of highlighting what is being done and suggesting what needs to be done in the future to champion this therapy as an effective option.

Hepatic Stellate Cells and Hepatocarcinogenesis.

Hepatic stellate cells (HSCs) are a significant component of the hepatocellular carcinoma (HCC) tumor microenvironment (TME). Activated HSCs transform into myofibroblast-like cells to promote fibrosis in response to liver injury or chronic inflammation, leading to cirrhosis and HCC. The hepatic TME is comprised of cellular components, including activated HSCs, tumor-associated macrophages, endothelial cells, immune cells, and non-cellular components, such as growth factors, proteolytic enzymes and their inhibitors, and other extracellular matrix (ECM) proteins. Interactions between HCC cells and their microenvironment have become topics under active investigation. These interactions within the hepatic TME have the potential to drive carcinogenesis and create challenges in generating effective therapies. Current studies reveal potential mechanisms through which activated HSCs drive hepatocarcinogenesis utilizing matricellular proteins and paracrine crosstalk within the TME. Since activated HSCs are primary secretors of ECM proteins during liver injury and inflammation, they help promote fibrogenesis, infiltrate the HCC stroma, and contribute to HCC development. In this review, we examine several recent studies revealing the roles of HSCs and their clinical implications in the development of fibrosis and cirrhosis within the hepatic TME.