Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has high relapse and low 5-year survival rates. Single-cell profiling in relapsed HCC may aid in the design of effective anticancer therapies, including immunotherapies. We profiled the transcriptomes of ∼17,000 cells from 18 primary or early-relapse HCC cases. Early-relapse tumors have reduced levels of regulatory T cells, increased dendritic cells (DCs), and increased infiltrated CD8+ T cells, compared with primary tumors, in two independent cohorts. Remarkably, CD8+ T cells in recurrent tumors overexpressed KLRB1 (CD161) and displayed an innate-like low cytotoxic state, with low clonal expansion, unlike the classical exhausted state observed in primary HCC. The enrichment of these cells was associated with a worse prognosis. Differential gene expression and interaction analyses revealed potential immune evasion mechanisms in recurrent tumor cells that dampen DC antigen presentation and recruit innate-like CD8+ T cells. Our comprehensive picture of the HCC ecosystem provides deeper insights into immune evasion mechanisms associated with tumor relapse.

Cancer-associated fibroblasts contributed to hepatocellular carcinoma recurrence and metastasis via CD36-mediated fatty-acid metabolic reprogramming.

Cancer-associated fibroblasts (CAFs) are the main components in the tumor microenvironment. Tumors activate fibroblasts from quiescent state into activated state by secreting cytokines, and activated CAFs may in turn promote tumor progression and metastasis. Therefore, studies targeting CAFs could enrich the therapeutic options for tumor treatment. In this study, we demonstrate that the content of lipid droplets and the expression of autophagosomes were higher in CAFs than in peri-tumor fibroblasts (PTFs), which was inhibited by 5-(tetradecyloxy)-2-furoic acid(TOFA). The expression of CD36 in CAFs was higher than that in PTFs at both mRNA and protein levels. Inhibition of CD36 activity using either the CD36 inhibitor SSO or siRNA had a significant negative impact on the proliferation and migration abilities of CAFs, which was associated with reduced levels of relevant activated genes (α-SMA, FAP, Vimentin) and cytokines (IL-6, TGF-ß and VEGF-α). SSO also inhibited HCC growth and tumorigenesis in nude mice orthotopically implanted with CAFs and HCC cells. Our data further show that CD36+CAFs affected the expression of PD-1 in CTLs leading to CTL exhaustion, and that patients with high CD36 expression in CAFs were correlated with shorter overall survival (OS). Together, our data demonstrate that CAFs were active in lipid metabolism with increased lipid content and lipophagy activity. CD36 may play a key role in the regulation of the biological behaviors of CAFs, which may influence the proliferation and migration of tumor cells by reprograming the lipid metabolism in tumor cells. Thus, CD36 could be an effective therapeutic target for the treatment of HCC.

Altered intersubject functional variability of brain white-matter in major depressive disorder and its association with gene expression profiles.

Major depressive disorder (MDD) is a clinically heterogeneous disorder. Its mechanism is still unknown. Although the altered intersubject variability in functional connectivity (IVFC) within gray-matter has been reported in MDD, the alterations to IVFC within white-matter (WM-IVFC) remain unknown. Based on the resting-state functional MRI data of discovery (145 MDD patients and 119 healthy controls [HCs]) and validation cohorts (54 MDD patients, and 78 HCs), we compared the WM-IVFC between the two groups. We further assessed the meta-analytic cognitive functions related to the alterations. The discriminant WM-IVFC values were used to classify MDD patients and predict clinical symptoms in patients. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging association analyses were further conducted to investigate gene expression profiles associated with WM-IVFC alterations in MDD, followed by a set of gene functional characteristic analyses. We found extensive WM-IVFC alterations in MDD compared to HCs, which were associated with multiple behavioral domains, including sensorimotor processes and higher-order functions. The discriminant WM-IVFC could not only effectively distinguish MDD patients from HCs with an area under curve ranging from 0.889 to 0.901 across three classifiers, but significantly predict depression severity (r = 0.575, p = 0.002) and suicide risk (r = 0.384, p = 0.040) in patients. Furthermore, the variability-related genes were enriched for synapse, neuronal system, and ion channel, and predominantly expressed in excitatory and inhibitory neurons. Our results obtained good reproducibility in the validation cohort. These findings revealed intersubject functional variability changes of brain WM in MDD and its linkage with gene expression profiles, providing potential implications for understanding the high clinical heterogeneity of MDD.

CD8+ T cell-based cancer immunotherapy.

The immune system in humans is a defense department against both exogenous and endogenous hazards, where CD8+ T cells play a crucial role in opposing pathological threats. Various immunotherapies based on CD8+ T cells have emerged in recent decades, showing their promising results in treating intractable diseases. However, in the fight against the constantly changing and evolving cancers, the formation and function of CD8+ T cells can be challenged by tumors that might train a group of accomplices to resist the T cell killing. As cancer therapy stepped into the era of immunotherapy, understanding the physiological role of CD8+ T cells, studying the machinery of tumor immune escape, and thereby formulating different therapeutic strategies become the imperative missions for clinical and translational researchers to fulfill. After brief basics of CD8+ T cell-based biology is covered, this review delineates the mechanisms of tumor immune escape and discusses different cancer immunotherapy regimens with their own advantages and setbacks, embracing challenges and perspectives in near future.

Application of a single-cell-RNA-based biological-inspired graph neural network in diagnosis of primary liver tumors.

Single-cell technology depicts integrated tumor profiles including both tumor cells and tumor microenvironments, which theoretically enables more robust diagnosis than traditional diagnostic standards based on only pathology. However, the inherent challenges of single-cell RNA sequencing (scRNA-seq) data, such as high dimensionality, low signal-to-noise ratio (SNR), sparse and non-Euclidean nature, pose significant obstacles for traditional diagnostic approaches. The diagnostic value of single-cell technology has been largely unexplored despite the potential advantages. Here, we present a graph neural network-based framework tailored for molecular diagnosis of primary liver tumors using scRNA-seq data. Our approach capitalizes on the biological plausibility inherent in the intercellular communication networks within tumor samples. By integrating pathway activation features within cell clusters and modeling unidirectional inter-cellular communication, we achieve robust discrimination between malignant tumors (including hepatocellular carcinoma, HCC, and intrahepatic cholangiocarcinoma, iCCA) and benign tumors (focal nodular hyperplasia, FNH) by scRNA data of all tissue cells and immunocytes only. The efficacy to distinguish iCCA from HCC was further validated on public datasets. Through extending the application of high-throughput scRNA-seq data into diagnosis approaches focusing on integrated tumor microenvironment profiles rather than a few tumor markers, this framework also sheds light on minimal-invasive diagnostic methods based on migrating/circulating immunocytes.

Monocarboxylate transporter 4 inhibition potentiates hepatocellular carcinoma immunotherapy through enhancing T cell infiltration and immune attack.

BACKGROUND AND AIMS: Monocarboxylate transporter (MCT) 4 is a high-affinity lactate transporter that is primarily involved in the maintenance of intracellular pH homeostasis and highly expressed in different tumors. However, the role of MCT4 in modulating immune responses against HCC remains unknown. APPROACH AND RESULTS: In this study, we demonstrated that MCT4 was overexpressed in HCC, which was associated with poor prognosis in patients. Genetic or pharmacological inhibition of MCT4 using VB124 (a highly potent MCT4 inhibitor) suppressed HCC tumor growth in immunocompetent mice model by enhancing CD8 + T cell infiltration and cytotoxicity. Such improved immunotherapy response by MCT4 targeting was due to combined consequences characterized by the alleviated acidification of tumor microenvironment and elevated the chemokine (C-X-C motif) ligand (CXCL) 9/CXCL10 secretion induced by reactive oxygen species/NF-κB signaling pathway. Combining MCT4 inhibition improved the therapeutic benefit of anti-programmed cell death 1 immunotherapy in HCC and prolonged mice survival. Moreover, higher MCT4 expression was observed in tumor tissues from nonresponder patients with HCC receiving neoadjuvant therapy with toripalimab. CONCLUSIONS: Our results revealed that lactate exportation by MCT4 has a tumor-intrinsic function in generating an immunosuppressive HCC environment and demonstrated the proof of the concept of targeting MCT4 in tailoring HCC immunotherapeutic approaches.

Diagnosis of Major Depressive Disorder Based on Individualized Brain Functional and Structural Connectivity.

BACKGROUND: Traditional neuroimaging studies have primarily emphasized analysis at the group level, often neglecting the specificity at the individual level. Recently, there has been a growing interest in individual differences in brain connectivity. Investigating individual-specific connectivity is important for understanding the mechanisms of major depressive disorder (MDD) and the variations among individuals. PURPOSE: To integrate individualized functional connectivity and structural connectivity with machine learning techniques to distinguish people with MDD and healthy controls (HCs). STUDY TYPE: Prospective. SUBJECTS: A total of 182 patients with MDD and 157 HCs and a verification cohort including 54 patients and 46 HCs. FIELD STRENGTH/SEQUENCE: 3.0 T/T1-weighted imaging, resting-state functional MRI with echo-planar sequence, and diffusion tensor imaging with single-shot spin echo. ASSESSMENT: Functional and structural brain networks from rs-fMRI and DTI data were constructed, respectively. Based on these networks, individualized functional connectivity (IFC) and individualized structural connectivity (ISC) were extracted using common orthogonal basis extraction (COBE). Subsequently, multimodal canonical correlation analysis combined with joint independent component analysis (mCCA + jICA) was conducted to fusion analysis to identify the joint and unique independent components (ICs) across multiple modes. These ICs were utilized to generate features, and a support vector machine (SVM) model was implemented for the classification of MDD. STATISTICAL TESTS: The differences in individualized connectivity between patients and controls were compared using two-sample t test, with a significance threshold set at P < 0.05. The established model was tested and evaluated using the receiver operating characteristic (ROC) curve. RESULTS: The classification performance of the constructed individualized connectivity feature model after multisequence fusion increased from 72.2% to 90.3%. Furthermore, the prediction model showed significant predictive power for assessing the severity of depression in patients with MDD (r = 0.544). DATA CONCLUSION: The integration of IFC and ISC through multisequence fusion enhances our capacity to identify MDD, highlighting the advantages of the individualized approach and underscoring its significance in MDD research. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Therapeutic effect of small extracellular vesicles from cytokine-induced memory-like natural killer cells on solid tumors.

Small extracellular vesicles (sEV) derived from diverse natural killer (NK) cell lines have proven their exceptional antitumor activities. However, sEV from human primary NK cells, especially memory-like NK cells, are rarely utilized for cancer treatment. In this study, we obtained sEV from IL-12, IL-15 and IL-18 cultured human memory-like NK cells (mNK-sEV) that showed strong cytokine-secretory ability. It was uncovered that mNK-sEV entered cancer cells via macropinocytosis and induced cell apoptosis via caspase-dependent pathway. Compared to sEV from conventionally cultured NK cells (conNK-sEV), mNK-sEV inhibited tumor growth to a greater extent. Concomitantly, pharmacokinetics and biodistribution results validated a higher accumulation of mNK-sEV than conNK-sEV in tumors of xenografted murine models. Notably, elevated containment of granulysin (GNLY) within mNK-sEV, at least in part, may contribute to the enhanced therapeutic effect. Herein our results present that mNK-sEV can be a novel class of therapeutic reagent for effective cancer treatment.

Deciphering intratumoral heterogeneity of hepatocellular carcinoma with microvascular invasion with radiogenomic analysis.

BACKGROUND AND AIMS: The recurrence and metastasis of hepatocellular carcinoma (HCC) are mainly caused by microvascular invasion (MVI). Our study aimed to uncover the cellular atlas of MVI+ HCC and investigate the underlying immune infiltration patterns with radiomics features. METHODS: Three MVI positive HCC and three MVI negative HCC samples were collected for single-cell RNA-seq analysis. 26 MVI positive HCC and 30 MVI negative HCC tissues were underwent bulk RNA-seq analysis. For radiomics analysis, radiomics features score (Radscore) were built using preoperative contrast MRI for MVI prediction and overall survival prediction. We deciphered the metabolism profiles of MVI+ HCC using scMetabolism and scFEA. The correlation of Radscore with the level of APOE+ macrophages and iCAFs was identified. Whole Exome Sequencing (WES) was applied to distinguish intrahepatic metastasis (IM) and multicentric occurrence (MO). Transcriptome profiles were compared between IM and MO. RESULTS: Elevated levels of APOE+ macrophages and iCAFs were detected in MVI+ HCC. There was a strong correlation between the infiltration of APOE+ macrophages and iCAFs, as confirmed by immunofluorescent staining. MVI positive tumors exhibited increased lipid metabolism, which was attributed to the increased presence of APOE+ macrophages. APOE+ macrophages and iCAFs were also found in high levels in IM, as opposed to MO. The difference of infiltration level and Radscore between two nodules in IM was relatively small. Furthermore, we developed Radscore for predicting MVI and HCC prognostication that were also able to predict the level of infiltration of APOE+ macrophages and iCAFs. CONCLUSION: This study demonstrated the interactions of cell subpopulations and distinct metabolism profiles in MVI+ HCC. Besides, MVI prediction Radscore and MVI prognostic Radscore were highly correlated with the infiltration of APOE+ macrophages and iCAFs, which helped to understand the biological significance of radiomics and optimize treatment strategy for MVI+ HCC.

CAFs shape myeloid-derived suppressor cells to promote stemness of intrahepatic cholangiocarcinoma through 5-lipoxygenase.

BACKGROUND AND AIMS: We previously demonstrated that cancer-associated fibroblasts (CAFs) promote tumor growth through recruitment of myeloid-derived suppressor cells (MDSCs). 5-lipoxygenase (5-LO) is highly expressed in myeloid cells and is critical for synthesizing leukotriene B4 (LTB4), which is involved in tumor progression by activating its receptor leukotriene B4 receptor type 2 (BLT2). In this study, we investigated whether and how CAFs regulate MDSC function to enhance cancer stemness, the driving force of the cancer aggressiveness and chemotherapy refractoriness, in highly desmoplastic intrahepatic cholangiocarcinoma (ICC). APPROACH AND RESULTS: RNA-sequencing analysis revealed enriched metabolic pathways but decreased inflammatory pathways in cancer MDSCs compared with blood MDSCs from patients with ICC. Co-injection of ICC patient-derived CAFs promoted cancer stemness in an orthotopic ICC model, which was blunted by MDSC depletion. Conditioned media (CM) from CAF-educated MDSCs drastically promoted tumorsphere formation efficiency and stemness marker gene expression in ICC cells. CAF-CM stimulation increased expression and activity of 5-LO in MDSCs, while 5-LO inhibitor impaired the stemness-enhancing capacity of MDSCs in vitro and in vivo. Furthermore, IL-6 and IL-33 primarily expressed by CAFs mediated hyperactivated 5-LO metabolism in MDSCs. We identified the LTB4-BLT2 axis as the critical downstream metabolite signaling of 5-LO in promoting cancer stemness, as treatment with LTB4 was elevated in CAF-educated MDSCs, or blockade of BLT2 (which was preferentially expressed in stem-like ICC cells) significantly reduced stemness-enhancing effects of CAF-educated MDSCs. Finally, BLT2 blockade augmented chemotherapeutic efficacy in ICC patient-derived xenograft models. CONCLUSIONS: Our study reveals a role for CAFs in orchestrating the optimal cancer stemness-enhancing microenvironment by educating MDSCs, and suggests the 5-LO/LTB4-BLT2 axis as promising therapeutic targets for ICC chemoresistance by targeting cancer stemness.

Classification of Major Depressive Disorder Based on Integrated Temporal and Spatial Functional MRI Variability Features of Dynamic Brain Network.

BACKGROUND: Characterization of the dynamics of functional brain network has gained increased attention in the study of depression. However, most studies have focused on single temporal dimension, while ignoring spatial dimensional information, hampering the discovery of validated biomarkers for depression. PURPOSE: To integrate temporal and spatial functional MRI variability features of dynamic brain network in machine-learning techniques to distinguish patients with major depressive disorder (MDD) from healthy controls (HCs). STUDY TYPE: Prospective. POPULATION: A discovery cohort including 119 patients and 106 HCs and an external validation cohort including 126 patients and 124 HCs from Rest-meta-MDD consortium. FIELD STRENGTH/SEQUENCE: A 3.0 T/resting-state functional MRI using the gradient echo sequence. ASSESSMENT: A random forest (RF) model integrating temporal and spatial variability features of dynamic brain networks with separate feature selection method (MSFS ) was implemented for MDD classification. Its performance was compared with three RF models that used: temporal variability features (MTVF ), spatial variability features (MSVF ), and integrated temporal and spatial variability features with hybrid feature selection method (MHFS ). A linear regression model based on MSFS was further established to assess MDD symptom severity, with prediction performance evaluated by the correlations between true and predicted scores. STATISTICAL TESTS: Receiver operating characteristic analyses with the area under the curve (AUC) were used to evaluate models' performance. Pearson's correlation was used to assess relationship of predicted scores and true scores. P < 0.05 was considered statistically significant. RESULTS: The model with MSFS achieved the best performance, with AUCs of 0.946 and 0.834 in the discovery and validation cohort, respectively. Additionally, altered temporal and spatial variability could significantly predict the severity of depression (r = 0.640) and anxiety (r = 0.616) in MDD. DATA CONCLUSION: Integration of temporal and spatial variability features provides potential assistance for clinical diagnosis and symptom prediction of MDD. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI.

BACKGROUND: Previous studies have explored the potential on radiomics features of primary breast cancer tumor to identify axillary lymph node (ALN) metastasis. However, the value of deep learning (DL) to identify ALN metastasis remains unclear. PURPOSE: To investigate the potential of the proposed attention-based DL model for the preoperative differentiation of ALN metastasis in breast cancer on dynamic contrast-enhanced MRI (DCE-MRI). STUDY TYPE: Retrospective. POPULATION: A total of 941 breast cancer patients who underwent DCE-MRI before surgery were included in the training (742 patients), internal test (83 patients), and external test (116 patients) cohorts. FIELD STRENGTH/SEQUENCE: A 3.0 T MR scanner, DCE-MRI sequence. ASSESSMENT: A DL model containing a 3D deep residual network (ResNet) architecture and a convolutional block attention module, named RCNet, was proposed for ALN metastasis identification. Three RCNet models were established based on the tumor, ALN, and combined tumor-ALN regions on the images. The performance of these models was compared with ResNet models, radiomics models, the Memorial Sloan-Kettering Cancer Center (MSKCC) model, and three radiologists (W.L., H.S., and F. L.). STATISTICAL TESTS: Dice similarity coefficient for breast tumor and ALN segmentation. Accuracy, sensitivity, specificity, intercorrelation and intracorrelation coefficients, area under the curve (AUC), and Delong test for ALN classification. RESULTS: The optimal RCNet model, that is, RCNet-tumor+ALN , achieved an AUC of 0.907, an accuracy of 0.831, a sensitivity of 0.824, and a specificity of 0.837 in the internal test cohort, as well as an AUC of 0.852, an accuracy of 0.828, a sensitivity of 0.792, and a specificity of 0.853 in the external test cohort. Additionally, with the assistance of RCNet-tumor+ALN , the radiologists' performance was improved (external test cohort, P < 0.05). DATA CONCLUSION: DCE-MRI-based RCNet model could provide a noninvasive auxiliary tool to identify ALN metastasis preoperatively in breast cancer, which may assist radiologists in conducting more accurate evaluation of ALN status. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Perioperative and oncologic outcomes of laparoscopic versus open liver resection for combined hepatocellular-cholangiocarcinoma: a propensity score matching analysis.

BACKGROUND: Laparoscopic liver resection (LLR) has now been established as a safe and minimally invasive technique that is deemed feasible for treating hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). However, the role of LLR in treating combined hepatocellular-cholangiocarcinoma (cHCC-CC) patients has been rarely reported. This study aimed to assess the efficacy of LLR when compared with open liver resection (OLR) procedure for patients with cHCC-CC. METHODS: A total of 229 cHCC-CC patients who underwent hepatic resection (34 LLR and 195 OLR patients) from January 2014 to December 2018 in Zhongshan Hospital, Fudan University were enrolled and underwent a 1:2 propensity score matching (PSM) analysis between the LLR and OLR groups to compare perioperative and oncologic outcomes. Overall survival (OS) and recurrence-free survival (RFS) parameters were assessed by the log-rank test and the sensitivity analysis. RESULTS: A total of 34 LLR and 68 OLR patients were included after PSM analysis. The LLR group displayed a shorter postoperative hospital stay (6.61 vs. 8.26 days; p value < 0.001) when compared with the OLR group. No significant differences were observed in the postoperative complications' incidence or a negative surgical margin rate between the two groups (p value = 0.409 and p value = 1.000, respectively). The aspartate aminotransferase (AST), alanine aminotransferase (ALT), and inflammatory indicators in the LLR group were significantly lower than those in the OLR group on the first and third postoperative days. Additionally, OS and RFS were comparable in both the LLR and OLR groups (p value = 0.700 and p value = 0.780, respectively), and similar results were obtained by conducting a sensitivity analysis. CONCLUSION: LLR can impart less liver function damage, better inflammatory response attenuation contributing to a faster recovery, and parallel oncologic outcomes when compared with OLR. Therefore, LLR can be recommended as a safe and effective therapeutic modality for treating selected cHCC-CC patients, especially for those with small tumors in favorable location.

Loss of SIRT5 promotes bile acid-induced immunosuppressive microenvironment and hepatocarcinogenesis.

BACKGROUND & AIMS: The liver is a metabolically active organ and is also 'tolerogenic', exhibiting sophisticated mechanisms of immune regulation that prevent pathogen attacks and tumorigenesis. How metabolism impacts the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) remains understudied. METHODS: We investigated the role of the metabolic regulator SIRT5 in HCC development by conducting metabolomic analysis, gene expression profiling, flow cytometry and immunohistochemistry analyses in oncogene-induced HCC mouse models and human HCC samples. RESULTS: We show that SIRT5 is downregulated in human primary HCC samples and that Sirt5 deficiency in mice synergizes with oncogenes to increase bile acid (BA) production, via hypersuccinylation and increased BA biosynthesis in the peroxisomes of hepatocytes. BAs act as a signaling mediator to stimulate their nuclear receptor and promote M2-like macrophage polarization, creating an immunosuppressive TME that favors tumor-initiating cells (TICs). Accordingly, high serum levels of taurocholic acid correlate with low SIRT5 expression and increased M2-like tumor-associated macrophages (TAMs) in HCC patient samples. Finally, administration of cholestyramine, a BA sequestrant and FDA-approved medication for hyperlipemia, reverses the effect of Sirt5 deficiency in promoting M2-like polarized TAMs and liver tumor growth. CONCLUSIONS: This study uncovers a novel function of SIRT5 in orchestrating BA metabolism to prevent tumor immune evasion and suppress HCC development. Our results also suggest a potential strategy of using clinically proven BA sequestrants for the treatment of patients with HCC, especially those with decreased SIRT5 and abnormally high BAs. LAY SUMMARY: Hepatocellular caricinoma (HCC) development is closely linked to metabolic dysregulation and an altered tumor microenvironment. Herein, we show that loss of the metabolic regulator Sirt5 promotes hepatocarcinogenesis, which is associated with abnormally elevated bile acids and subsequently an immunosuppressive microenvironment that favors HCC development. Targeting this mechanism could be a promising clinical strategy for HCC.

KRAS acting through ERK signaling stabilizes PD-L1 via inhibiting autophagy pathway in intrahepatic cholangiocarcinoma.

BACKGROUND: While the correlation between PD-L1 expression and KRAS mutation has been previously reported in other solid tumors such as non-small cell lung cancer (NSCLC), whether PD-L1 can be modulated by ERK signaling downstream of KRAS in intrahepatic cholangiocarcinoma (iCCA) and the underlying molecular regulatory mechanism remain unclear. METHODS: The expression of ERK, p-ERK, PD-L1 and autophagy markers following KRAS knockdown or Ras/Raf/MEK/ERK signaling inhibitors treatment was examined in two human iCCA cell lines (HuCCT1 and RBE) using western blotting and immunofluorescence. Both pharmacological autophagy inhibitors and short-interfering RNA against ATG7 were applied to inhibit autophagy. The apoptosis rates of iCCA cell lines were detected by flow cytometry and CCK-8 after co-culturing with CD3/CD28-activated human CD8+ T lymphocytes. Immunohistochemistry was applied to detect the correlation of ERK, p-ERK and PD-L1 in 92 iCCA tissues. RESULTS: The present study demonstrated that the PD-L1 expression level was distinctly reduced in KRAS-mutated iCCA cell lines when ERK signaling was inhibited and ERK phosphorylation levels were lowered. The positive association between p-ERK and PD-L1 was also verified in 92 iCCA tissue samples. Moreover, ERK inhibition induced autophagy activation. Both inhibiting autophagy via autophagy inhibitors and genetically silencing the ATG7 expression partially reversed the reduced PD-L1 expression caused by ERK inhibition. In addition, ERK-mediated down-regulation of PD-L1 via autophagy pathways induced the apoptosis of iCCA cells when co-cultured with CD3/CD28-activated human CD8+ T lymphocytes in vitro. CONCLUSIONS: Our results suggest that ERK signaling inhibition contributes to the reduction of PD-L1 expression through the autophagy pathway in iCCA. As a supplement to anti-PD-1/PD-L1 immunotherapy, ERK-targeted therapy may serve as a potentially novel treatment strategy for human KRAS-mutated iCCA.

Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography.

OBJECTIVE: To investigative the performance of intratumoral and peritumoral radiomics based on contrast-enhanced spectral mammography (CESM) to preoperatively predict the effect of the neoadjuvant chemotherapy (NAC) of breast cancers. MATERIALS AND METHODS: A total of 118 patients with breast cancer who underwent preoperative CESM and NAC from July 2017 to June 2020 were retrospectively analyzed, and the patients were grouped into training (n = 81) and test sets (n = 37) according to the CESM examination time. NAC effect for each patient was assessed by pathology. Intratumoral and peritumoral radiomics features were extracted from CESM images, and feature selection was performed through the Mann-Whitney U test and least absolute shrinkage and selection operator regression (LASSO). Five radiomics signatures based on intratumoral regions, 5-mm peritumoral regions, 10-mm peritumoral regions, intratumoral regions + 5-mm peritumoral regions, and intratumoral regions + 10-mm peritumoral regions were calculated through a linear combination of selected features weighted by their respective coefficients. The prediction performance of radiomics signatures was assessed by the area under the receiver operator characteristic (ROC) curve, the precision-recall (P-R) curve, the calibration curve, and decision curve analysis (DCA). RESULTS: Ten radiomics features were selected to establish the radiomics signature of intratumoral regions + 5-mm peritumoral regions, which yielded a maximum AUC of 0.85 (95% CI, 0.72-0.98) in the test set. The calibration curves, P-R curves, and DCA showed favorable predictive performance of the five radiomics signatures. CONCLUSION: The intratumoral and peritumoral radiomics based on CESM exhibited potential for predicting the NAC effect in breast cancer, which could guide treatment decisions. KEY POINTS: • The intratumoral and peritumoral CESM-based radiomics signatures show good performance in predicting the NAC effect in breast cancer.

Comprehensive analysis of complement-associated molecular features in hepatocellular carcinoma.

The complement cascade plays a "complementing" role in human immunity. However, the potential roles of complement system in impacting molecular and clinical features of hepatocellular carcinoma (HCC) remain unclear. In this study, eleven public datasets are analyzed to compare the complement status between normal and cancerous samples based on 18 classical complement-associated genes. The complement scores are constructed to quantify complement signatures of individual tumors. HCC patients in the The Cancer Genome Atlas (TCGA) cohort are focused to perform systematical analyses between complement status and immune infiltration, miRNA expression, DNA methylation, clinicopathological features, and drug response. The results show that the complement scores in normal tissues are dramatically higher than those of tumor tissues. Tumor samples in the TCGA cohort are classified into complement score-low and score-high groups. Pathway analysis reveals that tumor-promoting pathways are typically inhibited in complement score-high group. This study also shows that tumor-killing immune cells, such as CD8 + T cells and natural killer cells are abundant and tumor-suppressing miRNAs are upregulated in complement score-high samples. In addition, we identify that complement scores are negatively correlated with certain clinical features, including pathological grade, clinical-stage, and portal vein invasion. Moreover, various molecular features together with complement scores are found to be correlated with response to anti-cancer drugs. This study provides a comprehensive and multidimensional analysis conducive to understanding the role of complement in cancer.

Reticulon 3-mediated Chk2/p53 activation suppresses hepatocellular carcinogenesis and is blocked by hepatitis B virus.

OBJECTIVE: Dysfunction of endoplasmic reticulum (ER) proteins is closely related to homeostasis disturbance and malignant transformation of hepatocellular carcinoma (HCC). Reticulons (RTN) are a family of ER-resident proteins critical for maintaining ER function. Nevertheless, the precise roles of RTN in HCC remain largely unclear. The aim of the study is to examine the effect of reticulon family member RTN3 on HCC development and explore the underlying mechanisms. DESIGN: Clinical HCC samples were collected to assess the relationship between RTN3 expression and patients' outcome. HCC cell lines were employed to examine the effects of RTN3 on cellular proliferation, apoptosis and signal transduction in vitro. Nude mice model was used to detect the role of RTN3 in modulating tumour growth in vivo. RESULTS: We found that RTN3 was highly expressed in normal hepatocytes but frequently downregulated in HCC. Low RTN3 expression predicted poor outcome in patients with HCC in TP53 gene mutation and HBV infection status-dependent manner. RTN3 restrained HCC growth and induced apoptosis by activating p53. Mechanism studies indicated that RTN3 facilitated p53 Ser392 phosphorylation via Chk2 and enhanced subsequent p53 nuclear localisation. RTN3 interacted with Chk2, recruited it to ER and promoted its activation in an ER calcium-dependent manner. Nevertheless, the tumour suppressive effects of RTN3 were abrogated in HBV-positive cells. HBV surface antigen competed with Chk2 for RTN3 binding and blocked RTN3-mediated Chk2/p53 activation. CONCLUSION: The findings suggest that RTN3 functions as a novel suppressor of HCC by activating Chk2/p53 pathway and provide more clues to better understand the oncogenic effects of HBV.

Differentiation of COVID-19 from seasonal influenza: A multicenter comparative study.

As coronavirus disease 2019 (COVID-19) crashed into the influenza season, clinical characteristics of both infectious diseases were compared to make a difference. We reported 211 COVID-19 patients and 115 influenza patients as two separate cohorts at different locations. Demographic data, medical history, laboratory findings, and radiological characters were summarized and compared between two cohorts, as well as between patients at the intensive care unit (ICU) andnon-ICU within the COVID-19 cohort. For all 326 patients, the median age was 57.0 (interquartile range: 45.0-69.0) and 48.2% was male, while 43.9% had comorbidities that included hypertension, diabetes, bronchitis, and heart diseases. Patients had cough (75.5%), fever (69.3%), expectoration (41.1%), dyspnea (19.3%), chest pain (18.7%), and fatigue (16.0%), etc. Both viral infections caused substantial blood abnormality, whereas the COVID-19 cohort showed a lower frequency of leukocytosis, neutrophilia, or lymphocytopenia, but a higher chance of creatine kinase elevation. A total of 7.7% of all patients possessed no abnormal sign in chest computed tomography (CT) scans. For both infections, pulmonary lesions in radiological findings did not show any difference in their location or distribution. Nevertheless, compared to the influenza cohort, the COVID-19 cohort presented more diversity in CT features, where certain specific CT patterns showed significantly more frequency, including consolidation, crazy paving pattern, rounded opacities, air bronchogram, tree-in-bud sign, interlobular septal thickening, and bronchiolar wall thickening. Differentiable clinical manifestations and CT patterns may help diagnose COVID-19 from influenza and gain a better understanding of both contagious respiratory illnesses.

Laparoscopic hepatectomy enhances recovery for small hepatocellular carcinoma with liver cirrhosis by postoperative inflammatory response attenuation: a propensity score matching analysis with a conventional open approach.

BACKGROUND: The concurrent presence of liver cirrhosis and hepatocellular carcinoma (HCC) poses a challenge for laparoscopic surgeons to establish a routine practice. The aim of this study was to gather evidence and produce recommendations on the safe and effective practice of laparoscopic hepatectomy for patients with solitary HCC (≤ 5 cm) and liver cirrhosis. METHODS: Between October 2013 and October 2014, 356 curative hepatectomies were performed for patients pathologically diagnosed with solitary HCC (≤ 5 cm) accompanied by cirrhosis (stage 4 fibrosis). To overcome selection bias, a 1:2 match using propensity score matching analysis was conducted between laparoscopic and open hepatectomy. Perioperative outcomes were compared between the groups, including hospitalization, operation time, blood loss, and surgical complications. Perioperative inflammation-based markers, including systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) were collected from medical records and analyzed. RESULTS: There were 43 and 77 patients in the laparoscopic and open groups, respectively. The laparoscopic group had less hepatic inflow occlusion (16.3% vs. 61%; P < 0.001), shorter operation time (155 vs. 170 min; P = 0.004), and shorter postoperative hospital stay (4 vs. 7 days; P < 0.001). Although the difference was not significant (P = 0.154), the rate of postoperative complications tended to be lower in the laparoscopic group (2.3%) compared with the open group (9.1%). The increase in postoperative SII, NLR, and LMR for laparoscopic hepatectomy were significantly lower than for open hepatectomy. NLR < 5.8 on postoperative day 3 was significantly correlated with shorter hospital stay (P < 0.001). CONCLUSIONS: Compared with open hepatectomy, laparoscopic hepatectomy for selected HCC patients, even in the presence of cirrhosis, might result in better perioperative outcomes and postoperative inflammatory response attenuation, and ultimately promote faster recovery. This provides evidence for considering routine laparoscopic hepatectomy through careful selection of patients with HCC.