Integrating holotomography and deep learning for rapid detection of NPM1 mutations in AML.

Rapid and accurate diagnosis of acute myeloid leukemia (AML) remains a significant challenge, particularly in the context of myelodysplastic syndrome (MDS) or MDS/myeloproliferative neoplasm with NPM1 mutations. This study introduces an innovative approach using holotomography (HT), a 3D label-free quantitative phase imaging technique, to detect NPM1 mutations. We analyzed a dataset of 2073 HT myeloblast images from 48 individuals, including both NPM1 wild-type and mutated samples, to distinguish subcellular morphological changes associated with NPM1 mutations. Employing a convolutional neural network, we analyzed 3D cell morphology, focusing on refractive index distributions. The machine learning model showed high accuracy, with an area under the receiver operating characteristic curve of 0.9375 and a validation accuracy of 76.0%. Our findings reveal distinct morphological differences between the NPM1 wild-type and mutation at the subcellular level. This study demonstrates the potential of HT combined with deep learning for early, efficient, and cost-effective diagnosis of AML, offering a promising alternative to traditional stepwise genetic testing methods and providing additional assistance in morphological myeloblast discrimination. This approach may revolutionize the diagnostic process in leukemia, facilitating early detection and potentially reducing the reliance on extensive genetic testing.

Recent advances in label-free imaging and quantification techniques for the study of lipid droplets in cells.

Lipid droplets (LDs), once considered mere storage depots for lipids, have gained recognition for their intricate roles in cellular processes, including metabolism, membrane trafficking, and disease states like obesity and cancer. This review explores label-free imaging techniques' applications in LD research. We discuss holotomography and vibrational spectroscopic microscopy, emphasizing their potential for studying LDs without molecular labels, and we highlight the growing integration of artificial intelligence. Clinical applications in disease diagnosis and therapy are also considered.

Cryobiopsy: A Breakthrough Strategy for Clinical Utilization of Lung Cancer Organoids.

One major challenge associated with lung cancer organoids (LCOs) is their predominant derivation from surgical specimens of patients with early-stage lung cancer. However, patients with advanced lung cancer, who are in need of chemotherapy, often cannot undergo surgery. Therefore, there is an urgent need to successfully generate LCOs from biopsy specimens. Conventional lung biopsy techniques, such as transthoracic needle biopsy and forceps biopsy, only yield small amounts of lung tissue, resulting in a low success rate for culturing LCOs from biopsy samples. Furthermore, potential complications, like bleeding and pneumothorax, make it difficult to obtain sufficient tissue. Another critical issue is the overgrowth of normal lung cells in later passages of LCO culture, and the optimal culture conditions for LCOs are yet to be determined. To address these limitations, we attempted to create LCOs from cryobiopsy specimens obtained from patients with lung cancer (n = 113). Overall, the initial success rate of establishing LCOs from cryobiopsy samples was 40.7% (n = 46). Transbronchial cryobiopsy enables the retrieval of significantly larger amounts of lung tissue than bronchoscopic forceps biopsy. Additionally, cryobiopsy can be employed for peripheral lesions, and it is aided via radial endobronchial ultrasonography. This study significantly improved the success rate of LCO culture and demonstrated that the LCOs retained characteristics that resembled the primary tumors. Single-cell RNA sequencing confirmed high cancer cell purity in early passages of LCOs derived from patients with advanced lung cancer. Furthermore, the three-dimensional structure and intracellular components of LCOs were characterized using three-dimensional holotomography. Finally, drug screening was performed using a specialized micropillar culture system with cryobiopsy-derived LCOs. LCOs derived from cryobiopsy specimens offer a promising solution to the critical limitations of conventional LCOs. Cryobiopsy can be applied to patients with lung cancer at all stages, including those with peripheral lesions, and can provide sufficient cells for LCO generation. Therefore, we anticipate that cryobiopsy will serve as a breakthrough strategy for the clinical application of LCOs in all stages of lung cancer.

Machine-learning-based diagnosis of thyroid fine-needle aspiration biopsy synergistically by Papanicolaou staining and refractive index distribution.

We developed a machine learning algorithm (MLA) that can classify human thyroid cell clusters by exploiting both Papanicolaou staining and intrinsic refractive index (RI) as correlative imaging contrasts and evaluated the effects of this combination on diagnostic performance. Thyroid fine-needle aspiration biopsy (FNAB) specimens were analyzed using correlative optical diffraction tomography, which can simultaneously measure both, the color brightfield of Papanicolaou staining and three-dimensional RI distribution. The MLA was designed to classify benign and malignant cell clusters using color images, RI images, or both. We included 1535 thyroid cell clusters (benign: malignancy = 1128:407) from 124 patients. Accuracies of MLA classifiers using color images, RI images, and both were 98.0%, 98.0%, and 100%, respectively. As information for classification, the nucleus size was mainly used in the color image; however, detailed morphological information of the nucleus was also used in the RI image. We demonstrate that the present MLA and correlative FNAB imaging approach has the potential for diagnosing thyroid cancer, and complementary information from color and RI images can improve the performance of the MLA.

Quantification of structural heterogeneity in H&E stained clear cell renal cell carcinoma using refractive index tomography.

Clear cell renal cell carcinoma (ccRCC) is a common histopathological subtype of renal cancer and is notorious for its poor prognosis. Its accurate diagnosis by histopathology, which relies on manual microscopic inspection of stained slides, is challenging. Here, we present a correlative approach to utilize stained images and refractive index (RI) tomography and demonstrate quantitative assessments of the structural heterogeneities of ccRCC slides obtained from human patients. Machine-learning-assisted segmentation of nuclei and cytoplasm enabled the quantification at the subcellular level. Compared to benign regions, malignant regions exhibited a considerable increase in structural heterogeneities. The results demonstrate that RI tomography provides quantitative information in synergy with stained images on the structural heterogeneities in ccRCC.

Comparing efficacies of different treatment regimens in patients with hepatocellular carcinoma accompanied by portal vein tumor thrombus using network meta-analysis.

Purpose: Although various treatment regimens have been introduced for hepatocellular carcinoma (HCC) accompanied by portal vein tumor thrombosis (PVTT), comprehensive and direct comparisons between them are limited. Thus, the purpose of this study was to perform a network meta-analysis (NMA) to compare the efficacies of different treatment regimens for HCC accompanied by PVTT. Methods: A systematic review was conducted to identify studies comparing 2 or more treatment regimens for HCC accompanied by PVTT without extrahepatic metastasis and reporting each overall survival (OS). Endpoints of this NMA were to hazard ratios with confidential intervals for OS and mean survival time difference of each treatment regimen comparison using a random-effects model. Each treatment regimen was then ranked using the P-score to assess the probability of the superiority of each one. Results: Eleven studies involving 1,623 patients that yielded 16 comparisons were identified and enrolled in this NMA. There were 12 different treatment regimens as comparators, including sorafenib therapy alone (reference treatment). The NMA suggested that the following 4 treatment regimens improved OS compared to sorafenib: surgical resection followed by portal vein chemotherapy (SR plus PVC), SR, radiofrequency ablation plus sorafenib, and transarterial chemoembolization combined with selective internal radiation therapy. SR plus PVC was ranked the best treatment regimen for OS (P-score, 93.9%). Conclusion: Comparative efficacy based on this NMA may help clinicians select treatment for HCC accompanied by PVTT. If amenable, aggressive locoregional treatment regimens such as SR plus PVC should be considered for HCC accompanied by PVTT.

Alpha-Lipoic Acid Attenuates Apoptosis and Ferroptosis in Cisplatin-Induced Ototoxicity via the Reduction of Intracellular Lipid Droplets.

Alpha-lipoic acid (α-LA) is a potent antioxidant that can prevent apoptosis associated with cisplatin-induced ototoxicity through ROS. Ferroptosis is defined as an iron-dependent cell death pathway that has recently been highlighted and is associated with the accumulation of intracellular lipid droplets (LDs) due to an inflammatory process. Herein, we investigated the impact of α-LA on ferroptosis and analyzed the characteristics of LDs in auditory hair cells treated with cisplatin using high-resolution 3D quantitative-phase imaging with reconstruction of the refractive index (RI) distribution. HEI-OC1 cells were treated with 500 µM α-LA for 24 h and then with 15 µM cisplatin for 48 h. With 3D optical diffraction tomography (3D-ODT), the RI values of treated cells were analyzed. Regions with high RI values were considered to be LDs and labelled to measure the count, mass, and volume of LDs. The expression of LC3-B, P62, GPX4, 4-hydroxynonenal (4-HNE), and xCT was evaluated by Western blotting. HEI-OC1 cells damaged by cisplatin showed lipid peroxidation, depletion of xCT, and abnormal accumulation of 4-HNE. Additionally, the count, mass, and volume of LDs increased in the cells. Cells treated with α-LA had inhibited expression of 4-HNE, while the expression of xCT and GPX4 was recovered, which restored LDs to a level that was similar to that in the control group. Our research on LDs with 3D-ODT offers biological evidence of ferroptosis and provides insights on additional approaches for investigating the molecular pathways.

Interactions of Nanoparticles with Macrophages and Feasibility of Drug Delivery for Asthma.

Understanding the interaction between nanoparticles and immune cells is essential for the evaluation of nanotoxicity and development of nanomedicines. However, to date, there is little data on the membrane microstructure and biochemical changes in nanoparticle-loaded immune cells. In this study, we observed the microstructure of nanoparticle-loaded macrophages and changes in lipid droplets using holotomography analysis. Quantitatively analyzing the refractive index distribution of nanoparticle-loaded macrophages, we identified the interactions between nanoparticles and macrophages. The results showed that, when nanoparticles were phagocytized by macrophages, the number of lipid droplets and cell volume increased. The volume and mass of the lipid droplets slightly increased, owing to the absorption of nanoparticles. Meanwhile, the number of lipid droplets increased more conspicuously than the other factors. Furthermore, alveolar macrophages are involved in the development and progression of asthma. Studies have shown that macrophages play an essential role in the maintenance of asthma-related inflammation and tissue damage, suggesting that macrophage cells may be applied to asthma target delivery strategies. Therefore, we investigated the target delivery efficiency of gold nanoparticle-loaded macrophages at the biodistribution level, using an ovalbumin-induced asthma mouse model. Normal and severe asthma models were selected to determine the difference in the level of inflammation in the lung. Consequently, macrophages had increased mobility in models of severe asthma, compared to those of normal asthma disease. In this regard, the detection of observable differences in nanoparticle-loaded macrophages may be of primary interest, as an essential endpoint analysis for investigating nanomedical applications and immunotheragnostic strategies.

Is partial hepatectomy a curable treatment option for hepatocellular carcinoma accompanied by cirrhosis? A meta-analysis and cure model analysis.

BACKGROUNDS/AIMS: It is challenging to assess the efficacy of partial hepatectomy (PH) as a treatment option for patients with hepatocellular carcinoma (HCC) accompanied by cirrhosis. This study aimed to determine the cure fraction of PH for HCC accompanied by cirrhosis compared to that for HCC without cirrhosis. METHODS: A systematic review was performed on outcomes of previous studies that compared recurrence-free survival (RFS) after PH in patients with HCC with or without cirrhosis. A meta-analysis was conducted to obtain the cumulative hazard ratio for two patient groups: cirrhosis and non-cirrhosis. Cure fractions after PH in both groups were determined using a cure model analysis. RESULTS: A total of 18 studies were eligible for meta-analysis and 13 studies were selected for the cure model analysis. The cumulative hazard ratio for RFS of the cirrhosis group compared to that of the non-cirrhosis group was 1.66 (95% confidence interval [CI], 1.43-1.93). Survival data of 3,512 patients in both groups were reconstructed from survival curves of original articles for cure model analysis. The probability of being statistically cured after PH for HCC was 14.1% (95% CI, 10.6%-18.1%) in the cirrhosis group lower than that (32.5%) in the non-cirrhosis group (95% CI, 28.6%-36.4%). CONCLUSIONS: The prognosis after PH for HCC accompanied by cirrhosis is inferior to that for HCC without cirrhosis. However, a cure can be expected for one-seventh of patients with HCC accompanied by cirrhosis after PH.

Machine Learning Approach Using Routine Immediate Postoperative Laboratory Values for Predicting Postoperative Mortality.

BACKGROUND: Several prediction models have been proposed for preoperative risk stratification for mortality. However, few studies have investigated postoperative risk factors, which have a significant influence on survival after surgery. This study aimed to develop prediction models using routine immediate postoperative laboratory values for predicting postoperative mortality. METHODS: Two tertiary hospital databases were used in this research: one for model development and another for external validation of the resulting models. The following algorithms were utilized for model development: LASSO logistic regression, random forest, deep neural network, and XGBoost. We built the models on the lab values from immediate postoperative blood tests and compared them with the SASA scoring system to demonstrate their efficacy. RESULTS: There were 3817 patients who had immediate postoperative blood test values. All models trained on immediate postoperative lab values outperformed the SASA model. Furthermore, the developed random forest model had the best AUROC of 0.82 and AUPRC of 0.13, and the phosphorus level contributed the most to the random forest model. CONCLUSIONS: Machine learning models trained on routine immediate postoperative laboratory values outperformed previously published approaches in predicting 30-day postoperative mortality, indicating that they may be beneficial in identifying patients at increased risk of postoperative death.

Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose using the refractive index (RI), an intrinsic quantity governing light-matter interaction, as a means for such measurement. We show that major endogenous subcellular structures, which are conventionally accessed via exogenous fluorescence labelling, are encoded in three-dimensional (3D) RI tomograms. We decode this information in a data-driven manner, with a deep learning-based model that infers multiple 3D fluorescence tomograms from RI measurements of the corresponding subcellular targets, thereby achieving multiplexed microtomography. This approach, called RI2FL for refractive index to fluorescence, inherits the advantages of both high-specificity fluorescence imaging and label-free RI imaging. Importantly, full 3D modelling of absolute and unbiased RI improves generalization, such that the approach is applicable to a broad range of new samples without retraining to facilitate immediate applicability. The performance, reliability and scalability of this technology are extensively characterized, and its various applications within single-cell profiling at unprecedented scales (which can generate new experimentally testable hypotheses) are demonstrated.

Combined Therapy with microRNA-Expressing Salmonella and Irradiation in Melanoma.

Anticancer treatment strategies using bacteria as a vector are currently expanding with the development of anticancer drugs. Here, we present a research strategy to develop anticancer drugs using bacteria that contain miRNAs. We also present a strategy for the development of novel bacterial anticancer drugs in combination with radiation. Salmonella strains expressing miRNA were produced by modifying the miRNA expression vector encoding INHA, a radiation-resistant gene developed previously. The anticancer effect of INHA was confirmed using skin cancer cell lines. We also tested a combination strategy comprising bacteria and radiation for its anticancer efficacy against radiation-resistant mouse melanoma to increase the efficacy of radiation therapy as a novel strategy. The recombinant strain was confirmed to promote effective cell death even when combined with radiation therapy, which exerts its cytotoxicity by enhancing reactive oxygen species production. Moreover, a combination of bacterial and radiation therapy enhanced radiotherapy efficacy. When combined with radiation therapy, bacterial therapy exhibited effective anti-cancer properties even when administered to animals harboring radiation-resistant tumors. This strategy may promote the secretion of cytokines in cells and more effectively reduce the number of bacteria remaining in the animal. Thus, this study may lead to the development of a strategy to improve the effectiveness of radiation therapy using Salmonella expressing cancer-specific miRNA for intractable cancers such as those resistant to radiation.

Secondarily estimated cure fraction and five-year recurrence-free conditional survival probabilities among patients undergoing surgical resection for hepatocellular carcinoma presenting with minor gross vascular invasion.

BACKGROUND: Surgical resection (SR) has been selectively applied in hepatocellular carcinoma (HCC) presenting with minor gross vascular invasion (mGVI) which is defined when tumor invasion is confined to second-order portal branches or segmental branches of hepatic vein. However, little data of long-term outcomes are available for supporting the role of SR as a potentially curable therapeutic option for HCC presenting with mGVI. This study is aimed to estimate a statistical cure fraction and the improvement of recurrence-free conditional survival (RFCS) over time among patients undergoing SR for HCC presenting with mGVI. METHODS: The literature search was conducted focusing on previous studies that investigated the long-term survival rates of patients after SR for HCC presenting with mGVI. The reference cohort was extracted from a study including patients undergoing SR for HCC without vascular invasion. A non-mixture cure model was adopted to estimate the statistical cure fraction. The 5-year RFCS probabilities were also calculated. RESULTS: Three retrospective studies were secondarily analyzed. The probability of being statistically cured after SR for HCC presenting with mGVI was 7.3% (95% confidence interval, 4.4%-11.2%) in the mGVI group, lower than that of the reference cohort (hazard ratio, 1.81; 95% confidence interval, 1.59-2.05). The estimated 5-year RFCS probabilities improved with each additional year of survival. Moreover, 1 year after SR, the 5-year RFCS probabilities of patients with HCC presenting with mGVI was essentially the same as that of the reference cohort. CONCLUSIONS: This study shows that a cure can be expected in around seven percent of patients undergoing SR for HCC presenting with mGVI. Furthermore, recurrence-free survival expectancy improves dramatically over time among those patients who do not have recurrence. Overall, these findings suggest that SR should be considered as a potentially curable treatment for patients with HCC presenting with mGVI.

Detection of intracellular monosodium urate crystals in gout synovial fluid using optical diffraction tomography.

Optical diffraction tomography (ODT) enables imaging of unlabeled intracellular components by measuring the three-dimensional (3D) refractive index (RI). We aimed to detect intracellular monosodium urate (MSU) crystals in synovial leukocytes derived from gout patients using ODT. The 3D RI values of the synthetic MSU crystals, measured by ODT, ranged between 1.383 and 1.440. After adding synthetic MSU crystals to a macrophage, RI tomograms were reconstructed using ODT, and the reconstructed RI tomograms discerned intracellular and extracellular MSU crystals. We observed unlabeled synthetic MSU crystal entry into the cytoplasm of a macrophage through time-lapse imaging. Furthermore, using gout patient-derived synovial leukocytes, we successfully obtained RI tomogram images of intracellular MSU crystals. The 3D RI identification of MSU crystals was verified with birefringence through polarization-sensitive ODT measurements. Together, our results provide evidence that this novel ODT can identify birefringent MSU crystals in synovial leukocytes of patients with gout.

Chemotherapy confers a conserved secondary tolerance to EGFR inhibition via AXL-mediated signaling bypass.

Drug resistance remains the major culprit of therapy failure in disseminated cancers. Simultaneous resistance to multiple, chemically different drugs feeds this failure resulting in cancer relapse. Here, we investigate co-resistance signatures shared between antimitotic drugs (AMDs) and inhibitors of receptor tyrosine kinases (RTKs) to probe mechanisms of secondary resistance. We map co-resistance ranks in multiple drug pairs and identified a more widespread occurrence of co-resistance to the EGFR-tyrosine kinase inhibitor (TKI) gefitinib in hundreds of cancer cell lines resistant to at least 11 AMDs. By surveying different parameters of genomic alterations, we find that the two RTKs EGFR and AXL displayed similar alteration and expression signatures. Using acquired paclitaxel and epothilone B resistance as first-line AMD failure models, we show that a stable collateral resistance to gefitinib can be relayed by entering a dynamic, drug-tolerant persister state where AXL acts as bypass signal. Delayed AXL degradation rendered this persistence to become stably resistant. We probed this degradation process using a new EGFR-TKI candidate YD and demonstrated that AXL bypass-driven collateral resistance can be suppressed pharmacologically. The findings emphasize that AXL bypass track is employed by chemoresistant cancer cells upon EGFR inhibition to enter a persister state and evolve resistance to EGFR-TKIs.

Label-Free White Blood Cell Classification Using Refractive Index Tomography and Deep Learning.

Objective and Impact Statement. We propose a rapid and accurate blood cell identification method exploiting deep learning and label-free refractive index (RI) tomography. Our computational approach that fully utilizes tomographic information of bone marrow (BM) white blood cell (WBC) enables us to not only classify the blood cells with deep learning but also quantitatively study their morphological and biochemical properties for hematology research. Introduction. Conventional methods for examining blood cells, such as blood smear analysis by medical professionals and fluorescence-activated cell sorting, require significant time, costs, and domain knowledge that could affect test results. While label-free imaging techniques that use a specimen's intrinsic contrast (e.g., multiphoton and Raman microscopy) have been used to characterize blood cells, their imaging procedures and instrumentations are relatively time-consuming and complex. Methods. The RI tomograms of the BM WBCs are acquired via Mach-Zehnder interferometer-based tomographic microscope and classified by a 3D convolutional neural network. We test our deep learning classifier for the four types of bone marrow WBC collected from healthy donors (n=10): monocyte, myelocyte, B lymphocyte, and T lymphocyte. The quantitative parameters of WBC are directly obtained from the tomograms. Results. Our results show >99% accuracy for the binary classification of myeloids and lymphoids and >96% accuracy for the four-type classification of B and T lymphocytes, monocyte, and myelocytes. The feature learning capability of our approach is visualized via an unsupervised dimension reduction technique. Conclusion. We envision that the proposed cell classification framework can be easily integrated into existing blood cell investigation workflows, providing cost-effective and rapid diagnosis for hematologic malignancy.

Value of surgical resection compared to transarterial chemoembolization in the treatment of hepatocellular carcinoma with portal vein tumor thrombus: A meta-analysis of hazard ratios from five observational studies.

BACKGROUNDS/AIMS: Although systemic therapy is recommended in advanced hepatocellular carcinoma (HCC), treatment options for advanced HCC with portal vein tumor thrombosis (PVTT) are debatable. Recent studies have recommended other treatments, such as surgical resection (SR) and transarterial chemoembolization (TACE). Therefore, we performed a meta-analysis of hazard ratio (HR) for overall survival (OS) between the two modalities using previous reports in order to compare the two treatment options. METHODS: A systematic review was performed on previously reported data that compared the survival benefits of SR and TACE in patients with advanced HCC with PVTT. Thereafter, the meta-analysis was performed to determine the cumulative HR between the two different treatment groups. We used the HR and 95% CI directly from the original data, when available; however, if these data were unavailable, reconstruction was performed with the secondary data from the original Kaplan-Meier survival curve. RESULTS: A total of seven studies were eligible; however, 2 were excluded from the meta-analysis. The remaining 5 studies that included 1422 patients (SR group=559, TACE group=863) were studied for the meta-analysis. The median OS was longer in the SR group (8.2-64 months in SR vs. 6.6-32 months in TACE), proving that SR offered survival benefits. Moreover, the HR for the OS in the TACE group was 1.64 (95% CI, 1.43-1.88) compared to SR group, depicting that TACE was a less favorable option compared to SR. CONCLUSIONS: There is evidence that SR may be a better viable option for advanced HCC with PVTT.

Single-molecule functional anatomy of endogenous HER2-HER3 heterodimers.

Human epidermal growth factor receptors (HERs) are the primary targets of many directed cancer therapies. However, the reason a specific dimer of HERs generates a stronger proliferative signal than other permutations remains unclear. Here, we used single-molecule immunoprecipitation to develop a biochemical assay for endogenously-formed, entire HER2-HER3 heterodimers. We observed unexpected, large conformational fluctuations in juxta-membrane and kinase domains of the HER2-HER3 heterodimer. Nevertheless, the individual HER2-HER3 heterodimers catalyze tyrosine phosphorylation at an unusually high rate, while simultaneously interacting with multiple copies of downstream signaling effectors. Our results suggest that the high catalytic rate and multi-tasking capability make a concerted contribution to the strong signaling potency of the HER2-HER3 heterodimers.

MicroRNAs associated with microvascular invasion in hepatocellular carcinoma and their prognostic impacts in patients undergoing hepatic resection.

Although microvascular invasion (McVI) has prognostic value for patients with hepatocellular carcinoma (HCC) who have undergone hepatic resection, few studies have investigated the relationship between McVI and the aberrant expression of microRNAs (miRNAs). The present study identified the miRNAs that were selectively expressed in HCC with McVI and investigated their prognostic value. Clinical data and the miRNA expression profiles of 372 patients with HCC were extracted from The Cancer Genome Atlas database. miRNAs that were differentially expressed between patients with McVI and those without vascular invasion (VI) were identified and investigated as potential prognostic factors for HCC. The results demonstrated that McVI was a significant predictor of shortened recurrence-free survival (RFS). The 3 year RFS rate in patients with HCC accompanied by McVI was 28.2 and 49.3% in HCC without VI (P<0.001). miRNA-141/-582/-9 were upregulated, while miRNA-675 was downregulated in patients with McVI when compared with HCC patients without VI. Log2 fold-changes of miRNA-141/-582/-675/-9 were 0.80 [false discovery rate (FDR), 0.005], 0.55 (FDR, 0.045), -0.99 (FDR, 0.005) and 1.22 (FDR, <0.001), respectively. Kaplan-Meier analysis indicated that the overexpression of miR-141/-582/-9 was significantly associated with poor RFS and a poor overall survival. A text mining analysis revealed that these miRNAs were significantly associated with multifaceted hallmarks of cancer, including 'invasion and metastasis'. In conclusion, the overexpression of miRNA-141/-582/-9 was associated with McVI and a poor survival in patients undergoing hepatic resection for HCC.

Significantly different expression levels of microRNAs associated with vascular invasion in hepatocellular carcinoma and their prognostic significance after surgical resection.

BACKGROUND: Although gross vascular invasion (VI) has prognostic significance in patients with hepatocellular carcinoma (HCC) who have undergone hepatic resection, few studies have investigated the relationship between gross VI and aberrant expression of microribonucleic acids (miRNAs and miRs). Thus, the objective of this study was to identify miRNAs selectively expressed in HCC with gross VI and investigate their prognostic significance. MATERIALS AND METHODS: Eligible two datasets (accession number: GSE20594 and GSE67140) were collected from the National Center for Biotechnology Information's (NCBI) Gene Expression Omnibus (GEO) database to compare miRNAs expression between HCC with and without gross VI. Differentially expressed miRNAs were externally validated using expression data from The Cancer Genome Atlas (TCGA) database. Prognostic significance and predicted functions of selected miRNAs for HCC were also investigated. RESULTS: Thirty-five miRNAs were differentially expressed between HCC with and without gross VI in both datasets. Among them, three miRNAs were validated using TCGA database. miR-99a, miR-100, and miR-148a were downregulated to a greater extent in patients with HCC and gross VI than in those with HCC but no gross VI. Receiver operating characteristic (ROC) curve analysis showed discriminatory power of these miRNAs in predicting gross VI. Multivariate survival analysis revealed that types of surgery, advanced tumor node metastasis (TNM) stage, and low expression of miR-100-5p were independently associated with tumor recurrence. It also revealed that types of surgery, advanced TNM stage, low expression of miR-100-5p and miR-148a-3p were independent risk factors for overall survival (OS) after hepatic resection for HCC. A text mining analysis revealed that these miRNAs were linked to multifaceted hallmarks of cancer, including "invasion and metastasis." CONCLUSIONS: Low expressions of miR-100-5p and miR-148a-3p were associated with gross VI and poor survival of patients after hepatic resection for HCC.