Background: SARS-CoV-2-caused coronavirus disease (COVID-19) is posing a large casualty. The features of COVID-19 patients with and without pneumonia, SARS-CoV-2 transmissibility in asymptomatic carriers, and factors predicting disease progression remain unknown. Methods: We collected information on clinical characteristics, exposure history, and laboratory examinations of all laboratory-confirmed COVID-19 patients admitted to PLA General Hospital. Cox regression analysis was applied to identify prognostic factors. The last follow-up was February 18, 2020. Results: We characterized 55 consecutive COVID-19 patients. The mean incubation was 8.42 (95% confidence interval [CI], 6.55-10.29) days. The mean SARS-CoV-2-positive duration from first positive test to conversion was 9.71 (95%CI, 8.21-11.22) days. COVID-19 course was approximately 2 weeks. Asymptomatic carriers might transmit SARS-CoV-2. Compared to patients without pneumonia, those with pneumonia were 15 years older and had a higher rate of hypertension, higher frequencies of having a fever and cough, and higher levels of interleukin-6 (14.61 vs. 8.06pg/mL, P=0.040), B lymphocyte proportion (13.0% vs.10.0%, P=0.024), low account (<190/µL) of CD8 ⁺ T cells (33.3% vs. 0, P=0.019). Multivariate Cox regression analysis indicated that circulating interleukin-6 and lactate independently predicted COVID-19 progression, with a hazard ratio (95%CI) of 1.052 (1.000-1.107) and 1.082 (1.013-1.155), respectively. During disease course, T lymphocytes were generally lower, neutrophils higher, in pneumonia patients than in pneumonia-free patients. CD8 ⁺ lymphocytes did not increase at the 20 ^th days after illness onset. Conclusion: The epidemiological features are important for COVID-19 prophylaxis. Circulating interleukin-6 and lactate are independent prognostic factors. CD8 ⁺ T cell exhaustion might be critical in the development of COVID-19.

Background and Aims: HBV shapes the T-cell immune responses in HBV-related HCC. T cells can be recruited to the nidus, but limited T cells participate specifically in response to the HBV-related tumor microenvironment and HBV antigens. How epigenomic programs regulate T-cell compartments in virus-specific immune processes is unclear. Approach and Results: We developed Ti-ATAC-seq. 2 to map the T-cell receptor repertoire, epigenomic, and transcriptomic landscape of αβ T cells at both the bulk-cell and single-cell levels in 54 patients with HCC. We deeply investigated HBV-specific T cells and HBV-related T-cell subsets that specifically responded to HBV antigens and the HBV ⁺ tumor microenvironment, respectively, characterizing their T-cell receptor clonality and specificity and performing epigenomic profiling. A shared program comprising NFKB1/2-, Proto-Oncogene, NF-KB Sub unit, NFATC2-, and NR4A1-associated unique T-cell receptor-downstream core epigenomic and transcriptomic regulome commonly regulated the differentiation of HBV-specific regulatory T-cell (Treg) cells and CD8 ⁺ exhausted T cells; this program was also selectively enriched in the HBV-related Treg-CTLA4 and CD8-exhausted T cell-thymocyte selection associated high mobility subsets and drove greater clonal expansion in HBV-related Treg-CTLA4 subset. Overall, 54% of the effector and memory HBV-specific T cells are governed by transcription factor motifs of activator protein 1, NFE2, and BACH1/2, which have been reported to be associated with prolonged patient relapse-free survival. Moreover, HBV-related tumor-infiltrating Tregs correlated with both increased viral titer and poor prognosis in patients. Conclusions: This study provides insight into the cellular and molecular basis of the epigenomic programs that regulate the differentiation and generation of HBV-related T cells from viral infection and HBV + HCC unique immune exhaustion.

Patients suffering from advanced stage hepatocellular carcinoma (HCC) often exhibit a poor prognosis or dismal clinical outcomes due to ineffective chemotherapy or a multi-drug resistance (MDR) process. Thus, it is urgent to develop a new chemotherapeutic sensitivity testing system for HCC treatment. The presence study investigated the potential application of a novel chemotherapeutic sensitivity-testing system based on a collagen gel droplet embedded 3D–culture system (CD-DST). Primary cells were separating from surgical resection specimens and then tested by CD-DST. To identify whether HCC cell lines or cells separating from clinical specimens contain MDR features, the cells were treated with an IC 50 (half maximal inhibitory concentration) or IC max (maximal inhibitory concentration) concentration of antitumor agents, e.g., 5-furuolouracil (5-FU), paclitaxel (PAC), cisplatin (CDDP), epirubicin (EPI), or oxaliplatin (L-OHP), and the inhibitory rates (IRs) were calculated. HepG2 cells were sensitive to 5-FU, PAC, CDDP, EPI, or L-OHP; the IC 50 value is 0.83 ± 0.45 μg/ml, 0.03 ± 0.02 μg/ml, 1.15 ± 0.75 μg/ml, 0.09 ± 0.03 μg/ml, or 1.76 ± 0.44 μg/ml, respectively. Only eight (8/26), nine (9/26), or five (5/26) patients were sensitive to the IC max concentration of CDDP, EPI, or L-OHP; whereas only three (3/26), four (4/26), or two (2/26) patients were sensitive to the IC 50 concentration of CDDP, EPI, or L-OHP. No patients were sensitive to 5-FU or PAC. The in vitro drug sensitivity exanimation revealed the MDR features of HCC and examined the sensitivity of HCC cells from clinical specimens to anti-tumor agents. CD-DST may be a useful method to predict the potential clinical benefits of anticancer agents for HCC patients.

Background: Evidence concerning long-term outcome of robotic liver resection (RLR) and laparoscopic liver resection (LLR) for hepatocellular carcinoma (HCC) patients is scarce. Methods: This study enrolled all patients who underwent RLR and LLR for resectable HCC between July 2016 and July 2021. Propensity score matching (PSM) was employed to create a 1:3 match between the RLR and LLR groups. A comprehensive collection and analysis of patient data regarding efficacy and safety have been conducted, along with the evaluation of the learning curve for RLR. Results: Following PSM, a total of 341 patients were included, with 97 in the RLR group and 244 in the LLR group. RLR group demonstrated a significantly longer operative time (median [IQR], 210 [152.0–298.0] min vs. 183.5 [132.3–263.5] min; p = 0.04), with no significant differences in other perioperative and short-term postoperative outcomes. Overall survival (OS) was similar between the two groups (p = 0.43), but RLR group exhibited improved recurrence-free survival (RFS) (median of 65 months vs. 56 months, p = 0.006). The estimated 5-year OS for RLR and LLR were 74.8% (95% CI: 65.4–85.6%) and 80.7% (95% CI: 74.0–88.1%), respectively. The estimated 5-year RFS for RLR and LLR were 58.6% (95% CI: 48.6–70.6%) and 38.3% (95% CI: 26.4–55.9%), respectively. In the multivariate Cox regression analysis, RLR (HR: 0.586, 95% CI (0.393–0.874), p = 0.008) emerged as an independent predictor of reducing recurrence rates and enhanced RFS. The operative learning curve indicates that approximately after the 11th case, the learning curve of RLR stabilized and entered a proficient phase. Conclusions: OS was comparable between RLR and LLR, and while RFS was improved in the RLR group. RLR demonstrates oncological effectiveness and safety for resectable HCC.