Hepatocellular carcinoma (HCC) is a common malignant tumor in China. In the present study, we aimed to construct and verify a prediction model of recurrence in HCC patients using databases (TCGA, AMC and Inserm) and machine learning methods and obtain the gene signature that could predict early relapse of HCC. Statistical methods, such as feature selection, survival analysis and Chi-Square test in R software, were used to analyze and select mutant genes related to disease free survival (DFS), race and vascular invasion. In addition, whole-exome sequencing was performed on 10 HCC patients recruited from our center, and the sequencing results were compared with the databases. Using the databases and machine learning methods, the prediction model of recurrence was constructed and optimized, and the selected mutant genes were verified in the test group. The accuracy of prediction was 74.19%. Moreover, these 10 patients from our center were used to verify these mutant genes and the prediction model, and a success rate of 80% was achieved. Collectively, we discovered recurrence-related genes and established recurrence prediction model of recurrence for HCC patients, which could provide significant guidance for clinical prediction of recurrence. Hepatocellular carcinoma (HCC) is a common malignant tumor in China, which ranks the third in morbidity and the second in mortality. Its morbidity is usually associated with specific risk factors, including infections with HBV and HCV, high alcohol intake, obesity and consumption of aflatoxin-containing food 1. With the development of the second-generation sequencing techniques increasing research on HCC has been conducted on the molecular level. In 2014, Totoki et al. 2 have reported the whole-genome sequencing of 608 HCC patients from Asia and Europe. In 2015, Schulze et al. 3 have reported the whole-genome sequencing of 243 HCC patients from Europe and America. In 2016, Fujimoto et al. 4 have reported the whole-genome sequencing of 300 HCC patients from Japan. The molecular blueprint of HCC including somatic mutation, mRNA expression, methylation and miRNA regulation has been gradually outlined, which could be used for the diagnosis, treatment, and prediction of recurrence and survival of liver cancer patients. In 2017, TCGA working group 5 has systematically analyzed the sequencing results of the whole exome of more than 360 HCC patients in TCGA database and compared these data with other published HCC sequencing samples. Various statistical methods, related classification and clustering algorithms of machine learning have been used. TERT, TP53, CTNNB1, AXIN1, ARID1A, ARID2, RB1, ALB, APOB, PTEN, CDKN2A, DOCK2 6-15 and other somatic cells with significantly mutant genes (SMGs) and driver mutation have been identified. These findings have been rapidly applied as potential therapeutic targets and prognostic indicators in clinical practice. However, the high cost of whole-exome sequencing and whole-genome sequencing limits its use in clinical practice. Actually, patients often ...
2567 Background: Liposomes deliver the drug to tumors based on enhanced permeability and retention (EPR) effects. Radiotherapy further prompts the distribution of liposomal drugs to tumor sites receiving radiotherapy by altering the tumor microenvironment. In addition, radiotherapy might enhance systemic antitumoral responses to immunotherapy. Herein, we aimed to explore safety and efficacy of radiotherapy in combination with irinotecan liposome, immunotherapy, and antiangiogenic therapy in advanced solid tumors patients (pts) that failed standard treatments. Methods: Anopen single-arm, multi-center, phase II study was conducted to enroll solid tumors pts who have failed standard treatments. Eligible pts would receive radiotherapy combined with irinotecan liposome followed by camrelizumab and apatinib. Radiotherapy of 24 Gy/3 fractions/3-10 days was given to the targeted lesions. Irinotecan liposome (80mg/m2 i.v.) was administered once within 48 hours after radiotherapy and followed by camrelizumab (200mg i.v. q3w) and apatinib (250mg po qd) until disease progression or unacceptable toxicity. The primary endpoint was the objective response rate (ORR) of the irradiated lesions evaluated by the investigators as per RECIST V1.1. The secondary endpoints were disease control rate (DCR) and treatment-related adverse event (TRAE). Results: As of Dec 2021, 55 pts were enrolled includin 9 with biliary tract cancer, 8 with pancreatic cancer, 8 with sarcoma, 5 with lung cancer, 2 with liver cancer, 2 with cervical cancer, 2 with gastric cancer, and 22 with other cancer types. 26 (47.3%) pts failed at least 3 lines of therapy before enrollment. The median follow-up was 41 weeks and 42 pts can be evaluated. 15 partial response, 26 stable disease, and 1 progressive disease were achieved. The ORR and DCR of irradiated target lesions were 35.7% and 97.6%, respectively. The ORR and DCR of every cancer type are listed in table. TRAEs (all grades) occurred in 87.3% (48/55) pts. The most common grade 3-4 related TRAEs were lymphocyte count decreased (29.1%), white blood cell count decreased (10.9%), and anaemia (10.9%). Conclusions: The combination of radiotherapy, irinotecan liposome, camrelizumab, and apatinib demonstrated promising anti-tumor activity and well tolerance in various advanced solid tumors that failed standard treatments. Clinical trial information: NCT04569916. [Table: see text]
Introduction: Current treatments for patients with previously treated advanced hepatocellular carcinoma (HCC) provide modest survival benefits. We evaluated the safety and antitumor activity of serplulimab, an anti-PD-1 antibody, plus the bevacizumab biosimilar HLX04 in this patient population. Methods: In this open-label, multicenter, phase 2 study in China, patients with advanced HCC who failed prior systemic therapy received serplulimab 3 mg/kg plus HLX04 5 mg/kg (group A) or 10 mg/kg (group B) intravenously every 2 weeks. The primary endpoint was safety. Results: As of April 8, 2021, 20 and 21 patients were enrolled into group A and B, and they had received a median of 7 and 11 treatment cycles, respectively. Grade ≥3 treatment-emergent adverse events were reported by 14 (70.0%) patients in group A and 12 (57.1%) in group B. Most immune-related adverse events were grade ≤3. The objective response rate was 30.0% (95% confidence interval (CI), 11.9–54.3) in group A and 14.3% (95% CI, 3.0–36.3) in group B. Median duration of response was not reached (95% CI, 3.3–not evaluable (NE)) in group A and was 9.0 months (95% CI, 7.9–NE) in group B. Median progression-free survival was 2.2 months (95% CI, 1.4–5.5) and 4.1 months (95% CI, 1.5–NE), and median overall survival was 11.6 months (95% CI, 6.4–NE) and 14.3 months (95% CI, 8.2–NE) in group A and B, respectively. Conclusion: Serplulimab plus HLX04 showed a manageable safety profile and antitumor activity in patients with previously treated advanced HCC.
Objective: The treatment model of targeted therapy combined with immunotherapy has become the treatment modality for hepatocellular carcinoma due to problems such as single drug resistance. This trial was designed to evaluate the safety and tolerability of the fibroblast growth factor receptor 4 inhibitor CS3008 (BLU-554) in combination with the anti-PD-L1 monoclonal antibody CS1001 in patients with locally advanced or metastatic hepatocellular carcinoma (HCC). patients and methods: This multicenter, open-label, multidose Phase Ib/II trial enrolled patients with locally advanced or metastatic hepatocellular carcinoma (HCC). Patients received CS1001 1200 mg intravenously every three weeks and BLU-554 600 mg orally daily. The primary endpoint was objective response rate (ORR) as assessed according to RECISTv1.1. Result: A total of 18 patients were screened, of which 8 patients were FGF19 positive. And only four patients ultimately received the combination of treatment CS3008 (BLU-554) and CS1001 after entry row review, with ORR of 50% and DCR of 100%, and only one patient had an immune-related adverse reaction. Conclusion: Preliminary confirmation that CS3008 (BLU-554) in combination with CS1001 is safe and effective in the treatment of patients with locally advanced or metastatic hepatocellular carcinoma. Registration number: NCT04194801
The sparse model plays an important role in many aeras, such as in the machine learning, image processing and signal processing. The sparse model has the ability of variable selection, so they can solve the over-fitting problem. The sparse model can be introduced into the field of support vector machine in order to get classification of the labels and sparsity of the variables simultaneously. This paper summarizes various sparse support vector machines. Finally, we revealed the research directions of the sparse support vector machines in the future.
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