Senescence-based colorectal cancer subtyping reveals distinct molecular characteristics and therapeutic strategies.

Cellular senescence has been listed as a hallmark of cancer, but its role in colorectal cancer (CRC) remains unclear. We comprehensively evaluated the transcriptome, genome, digital pathology, and clinical data from multiple datasets of CRC patients and proposed a novel senescence subtype for CRC. Multi-omics data was used to analyze the biological features, tumor microenvironment, and mutation landscape of senescence subtypes, as well as drug sensitivity and immunotherapy response. The senescence score was constructed to better quantify senescence in each patient for clinical use. Unsupervised learning revealed three transcriptome-based senescence subtypes. Cluster 1, characterized by low senescence and activated proliferative pathways, was sensitive to chemotherapeutic drugs. Cluster 2, characterized by intermediate senescence and high immune infiltration, exhibited significant immunotherapeutic advantages. Cluster 3, characterized by high senescence, high immune, and stroma infiltration, had a worse prognosis and maybe benefit from targeted therapy. We further constructed a senescence scoring system based on seven senescent genes through machine learning. Lower senescence scores were highly predictive of longer disease-free survival, and patients with low senescence scores may benefit from immunotherapy. We proposed the senescence subtypes of CRC and our findings provide potential treatment interventions for each CRC senescence subtype to promote precision treatment.

An immune, stroma, and epithelial-mesenchymal transition-related signature for predicting recurrence and chemotherapy benefit in stage II-III colorectal cancer.

BACKGROUND: Debates exist on the treatment decision of the stage II/III colorectal cancer (CRC) due to the insufficiency of the current TNM stage-based risk stratification system. Epithelial-mesenchymal transition (EMT) and tumor microenvironment (TME) have both been linked to CRC progression in recent studies. We propose to improve the prognosis prediction of CRC by integrating TME and EMT. METHODS: In total, 2382 CRC patients from seven datasets and one in-house cohort were collected, and 1640 stage II/III CRC patients with complete survival information and gene expression profiles were retained and divided into a training cohort and three independent validation cohorts. Integrated analysis of 398 immune, stroma, and epithelial-mesenchymal transition (ISE)-related genes identified an ISE signature independently associated with the recurrence of CRC. The underlying biological mechanism of the ISE signature and its influence on adjuvant chemotherapy was further explored. RESULTS: We constructed a 26-gene signature which was significantly associated with poor outcome in Training cohort (p < 0.001, HR [95%CI] = 4.42 [3.25-6.01]) and three independent validation cohorts (Validation cohort-1: p < 0.01, HR [95%CI] = 1.70 [1.15-2.51]; Validation cohort-2: p < 0.001, HR [95% CI] = 2.30 [1.67-3.16]; Validation cohort-3: p < 0.01, HR [95% CI] = 2.42 [1.25-4.70]). After adjusting for known clinicopathological factors, multivariate cox analysis confirmed the ISE signature's independent prognostic value. Subgroup analysis found that stage III patients with low ISE score might benefit from adjuvant chemotherapy (p < 0.001, HR [95%CI] = 0.15 [0.04-0.55]). Hypergeometric test and enrichment analysis revealed that low-risk group was enriched in thr immune pathway while high-risk group was associated with the EMT pathway and CMS4 subtype. CONCLUSION: We proposed an ISE signature for robustly predicting the recurrence of stage II/III CRC and help treatment decision by identifying patients who will not benefit from current standard treatment.

Linc-ROR drive adriamycin resistance by targeting AP-2α/Wnt/ß-catenin axis in hepatocellular carcinoma.

Adriamycin is widely used as a chemotherapeutic strategy for advanced hepatocellular carcinoma (HCC). However, the clinical response was disappointing because of the acquired drug resistance with long-term usage. Revealing the underlying mechanism could provide promising therapeutics for the drug-resistant patients. The recently identified linc-ROR (long intergenic non-protein-coding RNA, regulator of reprogramming) has been found to be an oncogene in various cancers, and it also demonstrated to mediate drug resistance and metastasis. We thereby wonder whether this lincRNA could mediate adriamycin chemoresistance in HCC. In this study, linc-ROR was found to be upregulated in adriamycin-resistant HCC cells. And its overexpression accelerated epithelial-mesenchymal transition (EMT) program and adriamycin resistance. Conversely, its silence suppressed EMT and made HCC cells sensitize to adriamycin in vitro and in vivo. Further investigation revealed that linc-ROR physically interacted with AP-2α, mediated its stability by a post-translational modification manner, and sequentially activated Wnt/ß-catenin pathway. Furthermore, linc-ROR expression was positively associated with ß-catenin expression in human clinical specimens. Taken together, linc-ROR promoted tumorigenesis and adriamycin resistance in HCC via a linc-ROR/AP-2α/Wnt/ß-catenin axis, which could be developed as a potential therapeutic target for the adriamycin-resistant patients.

Nomogram for predicting overall survival time of patients with stage IV colorectal cancer.

Background: Prognosis varies among stage IV colorectal cancer (CRC). Our study aimed to build a robust prognostic nomogram for predicting overall survival (OS) of patients with stage IV CRC in order to provide evidence for individualized treatment. Method: We collected the information of 16,283 patients with stage IV CRC in the Surveillance, Epidemiology, and End Results (SEER) database and then randomized these patients in a ratio of 7:3 into a training cohort and an internal validation cohort. In addition, 501 patients in the Sixth Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) database were selected and used as an external validation cohort. Univariate and multivariate Cox analyses were used to screen out significant variables for nomogram establishment. The nomogram model was assessed using time-dependent receiver-operating characteristic curve (time-dependent ROC), concordance index (C-index), calibration curve, and decision curve analysis. Survival curves were plotted using the Kaplan-Meier method. Result: The C-index of the nomogram for OS in the training, internal validation, and external validation cohorts were 0.737, 0.727, and 0.655, respectively. ROC analysis and calibration curves pronounced robust discriminative ability of the model. Further, we divided the patients into a high-risk group and a low-risk group according to the nomogram. Corresponding Kaplan-Meier curves showed that the prediction of the nomogram was consistent with the actual practice. Additionally, model comparisons and decision curve analysis proved that the nomogram for predicting prognosis was significantly superior to the tumor-node-metastasis (TNM) staging system. Conclusions: We constructed a nomogram to predict OS of the stage IV CRC and externally validate its generalization, which was superior to the TNM staging system.

Predicting prognosis and immunotherapy response among colorectal cancer patients based on a tumor immune microenvironment-related lncRNA signature.

Long non-coding RNAs (lncRNAs) remodel the tumor immune microenvironment (TIME) by regulating the functions of tumor-infiltrating immune cells. It remains uncertain the way that TIME-related lncRNAs (TRLs) influence the prognosis and immunotherapy response of colorectal cancer (CRC). Aiming at providing survival and immunotherapy response predictions, a CRC TIME-related lncRNA signature (TRLs signature) was developed and the related potential regulatory mechanisms were explored with a comprehensive analysis on gene expression profiles from 97 immune cell lines, 61 CRC cell lines and 1807 CRC patients. Stratifying CRC patients with the TRLs signature, prolonged survival was observed in the low-risk group, while the patients in the high-risk group had significantly higher pro-tumor immune cells infiltration and higher immunotherapy response rate. Through the complex TRLs-mRNA regulation network, immunoregulation pathways and immunotherapy response pathways were found to be differently activated between the groups. In conclusion, the CRC TRLs signature is capable of making prognosis and immunotherapy response predictions, which may find application in stratifying patients for immunotherapy in the bedside.

Multi-Size Deep Learning Based Preoperative Computed Tomography Signature for Prognosis Prediction of Colorectal Cancer.

Background: Preoperative and postoperative evaluation of colorectal cancer (CRC) patients is crucial for subsequent treatment guidance. Our study aims to provide a timely and rapid assessment of the prognosis of CRC patients with deep learning according to non-invasive preoperative computed tomography (CT) and explore the underlying biological explanations. Methods: A total of 808 CRC patients with preoperative CT (development cohort: n = 426, validation cohort: n = 382) were enrolled in our study. We proposed a novel end-to-end Multi-Size Convolutional Neural Network (MSCNN) to predict the risk of CRC recurrence with CT images (CT signature). The prognostic performance of CT signature was evaluated by Kaplan-Meier curve. An integrated nomogram was constructed to improve the clinical utility of CT signature by combining with other clinicopathologic factors. Further visualization and correlation analysis for CT deep features with paired gene expression profiles were performed to reveal the molecular characteristics of CRC tumors learned by MSCNN in radiographic imaging. Results: The Kaplan-Meier analysis showed that CT signature was a significant prognostic factor for CRC disease-free survival (DFS) prediction [development cohort: hazard ratio (HR): 50.7, 95% CI: 28.4-90.6, p < 0.001; validation cohort: HR: 2.04, 95% CI: 1.44-2.89, p < 0.001]. Multivariable analysis confirmed the independence prognostic value of CT signature (development cohort: HR: 30.7, 95% CI: 19.8-69.3, p < 0.001; validation cohort: HR: 1.83, 95% CI: 1.19-2.83, p = 0.006). Dimension reduction and visualization of CT deep features demonstrated a high correlation with the prognosis of CRC patients. Functional pathway analysis further indicated that CRC patients with high CT signature presented down-regulation of several immunology pathways. Correlation analysis found that CT deep features were mainly associated with activation of metabolic and proliferative pathways. Conclusions: Our deep learning based preoperative CT signature can effectively predict prognosis of CRC patients. Integration analysis of multi-omic data revealed that some molecular characteristics of CRC tumor can be captured by deep learning in CT images.

DNA Repair-Related Gene Signature in Predicting Prognosis of Colorectal Cancer Patients.

Background: Increasing evidence have depicted that DNA repair-related genes (DRGs) are associated with the prognosis of colorectal cancer (CRC) patients. Thus, the aim of this study was to evaluate the impact of DNA repair-related gene signature (DRGS) in predicting the prognosis of CRC patients. Method: In this study, we retrospectively analyzed the gene expression profiles from six CRC cohorts. A total of 1,768 CRC patients with complete prognostic information were divided into the training cohort (n = 566) and two validation cohorts (n = 624 and 578, respectively). The LASSO Cox model was applied to construct a prediction model. To further validate the clinical significance of the model, we also validated the model with Genomics of Drug Sensitivity in Cancer (GDSC) and an advanced clear cell renal cell carcinoma (ccRCC) immunotherapy data set. Results: We constructed a prognostic DRGS consisting of 11 different genes to stratify patients into high- and low-risk groups. Patients in the high-risk groups had significantly worse disease-free survival (DFS) than those in the low-risk groups in all cohorts [training cohort: hazard ratio (HR) = 2.40, p < 0.001, 95% confidence interval (CI) = 1.67-3.44; validation-1: HR = 2.20, p < 0.001, 95% CI = 1.38-3.49 and validation-2 cohort: HR = 2.12, p < 0.001, 95% CI = 1.40-3.21). By validating the model with GDSC, we could see that among the chemotherapeutic drugs such as oxaliplatin, 5-fluorouracil, and irinotecan, the IC50 of the cell line in the low-risk group was lower. By validating the model with the ccRCC immunotherapy data set, we can clearly see that the overall survival (OS) of the objective response rate (ORR) with complete response (CR) and partial response (PR) in the low-risk group was the best. Conclusions: DRGS is a favorable prediction model for patients with CRC, and our model can predict the response of cell lines to chemotherapeutic agents and potentially predict the response of patients to immunotherapy.

Risk factors for recurrence of colorectal conventional adenoma and serrated polyp.

Background: Removal of colorectal polyps during screening could reduce the incidence of colorectal cancer (CRC). However, there is a lack of data on risk factors associated with recurrence of polyps, including conventional adenomas and serrated polyps (SPs). This study aimed to determine risk factors for recurrence of colorectal polyps and their subtypes based on the characteristics of the patients and polyps. Methods: A total of 1,165 patients diagnosed with conventional adenoma or SP in the Sixth Affiliated Hospital of Sun Yat-sen University between January 2013 and December 2019 were enrolled in this study, including 668 cases with conventional adenomas, 385 with SPs, and 112 with coexistence of adenomas and SPs. Univariate analysis and multivariate logistic regression were used to identify potential risk factors for polyp recurrence. A nomogram was established according to risk factors and the performance was evaluated using calibration plots. Results: During a median follow-up of 24 months, recurrent polyps were observed in 531 (45.6%) cases. Male, age ≥50 years, body mass index (BMI) ≥24 kg/m2, at least three polyps, smoking, alcohol consumption, family history of polyps, and family history of CRC were independent risk factors for polyp recurrence. The Harrell's C-index of the nomogram developed with these parameters was 0.69 and the calibration plots showed good agreement between actual polyp recurrence and nomogram-predicted recurrence probability. In the subtype analyses, conventional adenomas had the same risk factors for recurrence as all polyps, while smoking, alcohol consumption, family history of polyps, and family history of CRC were not risk factors for SP recurrence. Conclusions: We identified several risk factors for recurrence of colorectal polyps and found that some of them could increase the risk of adenoma recurrence but not SP recurrence, including smoking, alcohol consumption, and family history of polyps/CRC, which might help us to understand different etiology and biology between conventional adenomas and SPs.

Increased risk of colorectal neoplasia in inflammatory bowel disease patients with post-inflammatory polyps: A systematic review and meta-analysis.

BACKGROUND: Inflammatory bowel disease (IBD) patients with post-inflammatory polyps (PIPs) may carry an increased risk of colorectal neoplasia (CRN) including dysplasia and cancer. Current guidelines recommend active colonoscopy follow-up for these patients. However, the evidence for guidelines is still poor. In addition, some recent high-quality reports present a different view, which challenges the current guidelines. We hypothesize that IBD patients with PIPs are at increased risk of CRN. AIM: To evaluate the risk of CRN in IBD patients with and without PIPs. METHODS: A systematic search of PubMed, Embase, Cochrane Library, and Web of Science was performed to identify studies that compared the risk of CRN in IBD patients with and without PIPs. In addition, we screened the reference lists and citation indices of the included studies. Quality assessment was performed using the Newcastle-Ottawa Scale. Pooled odds ratio (OR) was calculated using the random-effects model to explore the final pooled effect size of the included studies and determine whether PIPs increase the risk of CRN. Sensitivity analysis, subgroup analysis, and assessment of publication bias were performed to examine the sources of heterogeneity. RESULTS: Twelve studies with 5819 IBD patients, including 1281 (22.01%) with PIPs, were considered eligible for this meta-analysis. We found that IBD patients with PIPs were at an increased risk of CRN as compared to those without PIPs [OR 2.01; 95% confidence interval (CI): 1.43-2.83]. The results were similar when colorectal cancer was used as the study endpoint (OR 2.57; 95%CI: 1.69-3.91). Furthermore, the risk of CRN was still increased (OR 1.80; 95%CI: 1.12-2.91) when restricted to ulcerative colitis patients. Heterogeneity was high among the included studies (I² = 75%). Subgroup analysis revealed that the high heterogeneity was due to the study design. Sensitivity analysis showed that the main statistical outcomes did not essentially change after excluding any one of the included studies. No significant publication bias was found in the funnel plots. CONCLUSION: IBD patients with PIPs have an increased risk of CRN as compared with those without PIPs, which support the current guidelines. However, a high-quality randomized controlled trial is warranted.

Identification of an Autophagy-Related Gene Signature for the Prediction of Prognosis in Early-Stage Colorectal Cancer.

Purpose: A certain number of early-stage colorectal cancer (CRC) patients suffer tumor recurrence after initial curative resection. In this context, an effective prognostic biomarker model is constantly in need. Autophagy exhibits a dual role in tumorigenesis. Our study aims to develop an autophagy-related gene (ATG) signature-based on high-throughput data analysis for disease-free survival (DFS) prognosis of patients with stage I/II CRC. Methods: Gene expression profiles and clinical information of CRC patients extracted from four public datasets were distributed to discovery and training cohort (GSE39582), validation cohort (TCGA CRC, n = 624), and meta-validation cohort (GSE37892 and GSE14333, n = 420). Autophagy genes significantly associated with prognosis were identified. Results: Among 655 autophagy-related genes, a 10-gene ATG signature, which was significantly associated with DFS in the training cohort (HR, 2.76[1.56-4.82]; p = 2.06 × 10-4), was constructed. The ATG signature, stratifying patients into high and low autophagy risk groups, was validated in the validation (HR, 2.29[1.15-4.55]; p = 1.5 × 10-2) and meta-validation cohorts (HR, 2.5[1.03-6.06]; p = 3.63 × 10-2) and proved to be prognostic in a multivariate analysis. Functional analysis revealed enrichment of several immune/inflammatory pathways in the high autophagy risk group, where increased infiltration of T regulatory cells (Tregs) and decreased infiltration of M1 macrophages were observed. Conclusion: Our study established a prognostic ATG signature that effectively predicted DFS for early-stage CRC patients. Meanwhile, the study also revealed the possible relationship among autophagy process, immune/inflammatory response, and tumorigenesis.

Cancer-associated fibroblasts impact the clinical outcome and treatment response in colorectal cancer via immune system modulation: a comprehensive genome-wide analysis.

BACKGROUND: Cancer-associated fibroblasts (CAFs) in the tumour microenvironment are associated with poor prognosis and chemoresistance in multiple solid tumours. However, there is a lack of universal measures of CAFs in colorectal cancer (CRC). The aim of this study was to assess the utility of a fibroblast-related gene signature (FRGS) for predicting patient outcomes and reveal its relevant mechanism. METHODS: The GSE39582 dataset, which includes 316 CRC patients who did not receive adjuvant chemotherapy was used as a discovery cohort to identify the prognostic fibroblast-related genes (FRGs). A total of 1352 CRC patients were divided into one training cohort (GSE39582, n = 461) and two validation cohorts (TCGA, n = 338; meta-validation, n = 553) for the construction of the FRGS and the verification of its prognostic value in stage II/III CRC patients. Functional annotation and analysis were performed to explore the underlying mechanism. The ability of the FRGS to predict immunotherapy response was further tested in a clear cell renal cell carcinoma (ccRCC) cohort. RESULTS: An 11-gene signature that had prognostic value for stage II/III CRC patients in both validation cohorts was developed (TCGA cohort: HR = 1.90, 95% CI 1.16-3.12, P < 0.01; meta-validation cohort: HR = 1.95, 95% CI 1.39-2.73, P < 0.001). A high level of CAFs was correlated with worse prognosis in CRC patients who did not receive adjuvant chemotherapy (HR = 3.63, 95% CI 2.24-5.88, P < 0.001). Importantly, patients in the low-risk group were found to be benefit from chemotherapy (P < 0.01), but not in the high CAF group (P > 0.05). Similar results were found in the TCGA cohort. Integrated with clinical characteristics, the FRGS was confirmed to be an independent prognostic factor in the multivariate analysis after adjustment for tumour TNM stage (GSE39582 cohort: HR = 3.19, 95% CI 1.88-5.41, P < 0.001; TCGA cohort: HR = 5.00, 95% CI 1.58-15.85, P = 0.007; meta-validation cohort: HR = 2.99, 95% CI 1.44-6.21, P = 0.003). Furthermore, the enrichment analysis found that the antitumour immune response was suppressed and the infiltration of CD4 T cells and M1 macrophages was depressed in the high CAF group. The FRGS was also found to have value in predicting for immunotherapy response in the ccRCC cohort. CONCLUSIONS: The 11-gene FRGS had independent prognostic value for CRC patients, as well as utility in the prediction of benefit from chemotherapy. CAFs in the tumour microenvironment might have an impact on the prognosis of CRC patients via inhibiting immune response.

Genome-Wide Analysis Reveals Hypoxic Microenvironment Is Associated With Immunosuppression in Poor Survival of Stage II/III Colorectal Cancer Patients.

Background: Hypoxia is associated with a poorer clinical outcome and resistance to chemotherapy in solid tumors; identifying hypoxic-related colorectal cancer (CRC) and revealing its mechanism are important. The aim of this study was to assess hypoxia signature for predicting prognosis and analyze relevant mechanism. Methods: Patients without chemotherapy were selected for the identification of hypoxia-related genes (HRGs). A total of six independent datasets that included 1,877 CRC patients were divided into a training cohort and two validation cohorts. Functional annotation and analysis were performed to reveal relevant mechanism. Results: A 12-gene signature was derived, which was prognostic for stage II/III CRC patients in two validation cohorts [TCGA, n = 509, hazard ratio (HR) = 2.14, 95% confidence interval (CI) = 1.18 - 3.89, P = 0.01; metavalidation, n = 590, HR = 2.46, 95% CI = 1.59 - 3.81, P < 0.001]. High hypoxic risk was correlated with worse prognosis in CRC patients without adjuvant chemotherapy (HR = 5.1, 95% CI = 2.51 - 10.35, P < 0.001). After integration with clinical characteristics, hypoxia-related gene signature (HRGS) remained as an independent prognostic factor in multivariate analysis. Furthermore, enrichment analysis found that antitumor immune response was suppressed in the high hypoxic group. Conclusions: HRGS is a promising system for estimating disease-free survival of stage II/III CRC patients. Hypoxia tumor microenvironment may be via inhibiting immune response to promote chemoresistance in stage II/III CRC patients.

A Metabolism-Related Radiomics Signature for Predicting the Prognosis of Colorectal Cancer.

Background: Radiomics refers to the extraction of a large amount of image information from medical images, which can provide decision support for clinicians. In this study, we developed and validated a radiomics-based nomogram to predict the prognosis of colorectal cancer (CRC). Methods: A total of 381 patients with colorectal cancer (primary cohort: n = 242; validation cohort: n = 139) were enrolled and radiomic features were extracted from the vein phase of preoperative computed tomography (CT). The radiomics score was generated by using the least absolute shrinkage and selection operator algorithm (LASSO). A nomogram was constructed by combining the radiomics score with clinicopathological risk factors for predicting the prognosis of CRC patients. The performance of the nomogram was evaluated by the calibration curve, receiver operating characteristic (ROC) curve and C-index statistics. Functional analysis and correlation analysis were used to explore the underlying association between radiomic feature and the gene-expression patterns. Results: Five radiomic features were selected to calculate the radiomics score by using the LASSO regression model. The Kaplan-Meier analysis showed that radiomics score was significantly associated with disease-free survival (DFS) [primary cohort: hazard ratio (HR): 5.65, 95% CI: 2.26-14.13, P < 0.001; validation cohort: HR: 8.49, 95% CI: 2.05-35.17, P < 0.001]. Multivariable analysis confirmed the independent prognostic value of radiomics score (primary cohort: HR: 5.35, 95% CI: 2.14-13.39, P < 0.001; validation cohort: HR: 5.19, 95% CI: 1.22-22.00, P = 0.026). We incorporated radiomics signature with the TNM stage to build a nomogram, which performed better than TNM stage alone. The C-index of the nomogram achieved 0.74 (0.69-0.80) in the primary cohort and 0.82 (0.77-0.87) in the validation cohort. Functional analysis and correlation analysis found that the radiomic signatures were mainly associated with metabolism related pathways. Conclusions: The radiomics score derived from the preoperative CT image was an independent prognostic factor and could be a complement to the current staging strategies of colorectal cancer.

Urolithin B suppresses tumor growth in hepatocellular carcinoma through inducing the inactivation of Wnt/ß-catenin signaling.

Consumption of dietary ellagitannins (ETs) has been proven to benefit multiple chronic health disorders including cancers and cardiovascular diseases. Urolithins, gut microbiota metabolites derived from ETs, are considered as the molecules responsible for these health effects. Previous studies have demonstrated that urolithins exhibit antiproliferative effects on prostate, breast, and colon cancers. However, as for hepatocellular carcinoma (HCC), it remains elusive. Herein, we aim to investigate the function of urolithin B (UB), a member of urolithins family, in HCC. The effects of UB on cell viability, cell cycle and apoptosis were evaluated in HCC cells, and we found UB could inhibit the proliferation of HCC cells, which resulted from cell cycle arrest and apoptosis. Furthermore, UB could increase phosphorylated ß-catenin expression and block its translocation from nuclear to cytoplasm, thus inducing the inactivation of Wnt/ß-catenin signaling. Using a xenograft mice model, UB was found to suppress tumor growth in vivo. In conclusion, our data demonstrated that UB could inhibit the proliferation of HCC cells in vitro and in vivo via inactivating Wnt/ß-catenin signaling, suggesting UB could be a promising candidate in the development of anticancer drugs targeting HCC.

Ubiquitin specific peptidase 5 mediates Histidine-rich protein Hpn induced cell apoptosis in hepatocellular carcinoma through P14-P53 signaling.

Hpn is a small histidine-rich cytoplasmic protein from Helicobacter pylori and has been recognized as a high-risk factor for several cancers including gastric cancer, colorectal cancer, and MALT lymphoma. However, the relationship between Hpn and cancers remains elusive. In this study, we discovered that Hpn protein effectively suppressed cell growth and induced apoptosis in hepatocellular carcinoma (HCC). A two-dimensional gel electrophoresis and mass spectrometry-based comparative proteomics was performed to find the molecular targets of Hpn in HCC cells. It was identified that twelve proteins were differentially expressed, with USP5 being one of the most significantly downregulated protein. The P14ARF -P53 signaling was activated by USP5 knockdown in HCC cells. Furthermore, USP5 overexpression significantly rescued the suppressive effect of Hpn on the viability of HCC cells. In conclusion, our study suggests that Hpn plays apoptosis-inducing roles through suppressing USP5 expression and activating the P14ARF -P53 signaling. Therefore, Hpn may be a potential candidate for developing novel anti-HCC drugs.