A novel photothermal agent (PTA) and gene co-delivery nanosystem (CSP@IL-12) for tumor localized NIR-II PTT and in situ immunotherapy through local generation of IL-12 cytokine.

Background Personalized neoantigen vaccine could induce a robust antitumor immune response in multiple cancers, whose efficacy could be further enhanced by combining with programmed cell death 1 blockade (α-PD-1). However, the corresponding immune response and synergistic mechanisms remain largely unclear. Here, we aimed to develop clinically available combinational therapeutic strategy and further explore its potential antitumor mechanisms in hepatocellular carcinoma (HCC). Methods Neoantigen peptide vaccine (NeoVAC) for murine HCC cell line Hepa1-6 was developed and optimized by neoantigen screening and adjuvant optimization. Then the synergistic efficacy and related molecular mechanisms of NeoVAC combined with α-PD-1 in HCC were evaluated by orthotopic HCC mouse model, single-cell RNA sequencing, tetramer flow cytometry, immunofluorescence, etc. The tumor-killing capacity of CD8 + tissue-resident memory T cells (CD8 + T RMs ) was assessed by orthotopic HCC mouse model, and autologous patient-derived cells. Results NeoVAC, which consisted of seven high immunogenic neoantigen peptides and clinical-grade Poly(I:C), could generate a strong antitumor immune response in HCC mouse models. Significantly, its efficacy could be further improved by combining with α-PD-1, with 80% of durable tumor regression and long-term immune memory in orthotopic HCC models. Moreover, in-depth analysis of the tumor immune microenvironment showed that the percentage of CD8 + T RMs was remarkedly increased in NeoVAC plus α-PD-1 treatment group, and positively associated with the antitumor efficacy. In vitro and in vivo T-cell cytotoxicity assay further confirmed the strong tumor-killing capacity of CD8 + T RMs sorting from orthotopic mouse HCC or patient’s HCC tissue. Conclusions This study showed that NeoVAC plus α-PD-1 could induce a strong antitumor response and long-term tumor-specific immune memory in HCC by increasing CD8 + T RMs infiltration, which might serve as a potential immune-therapeutic target for HCC.

Background: Non-intubated anesthesia thoracoscopic surgery is an evolving form of minimally invasive thoracic surgery. It has had encouraging results in the treatment of lung cancer, and the current concept of enhanced recovery after surgery has become indispensable to surgical treatment. Our center retrospectively evaluated the clinical effect of rapid postoperative rehabilitation in patients who underwent thoracoscopic lung surgery under non-intubated anesthesia. Methods:The clinical data of 192 patients undergoing video-assisted thoracoscopic surgery (VATS) at the

Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Proteomics-driven discovery of tumor biomarkers is an important direction for omics study. Here, we described a staged mass spectrometry (MS)-based discovery-verification-validation proteomics workflow to explore serum proteomic biomarkers for HCC early diagnosis in 662 individuals (373 HCC patients and 289 non-HCC patients). Our workflow reproducibly quantified 451serum proteins using a data independent acquisition mass spectrometry (DIA-MS) strategy from discovery cohort, and proteins with significantly altered abundance in HCC were validated as candidates in an independent validation cohort using targeted proteomics based on parallel reaction monitoring (PRM). Machine learning models determined as P4 serum protein-panels (two serum proteomics biomarkers: HABP2, CD163 and two clinical used serum biomarkers: AFP, PIVKA-II) could clearly distinguish HCC patients from LC patients in an independent validation cohort (AUC 0.979, sensitivity 0.925, specificity 0.915), outperforming existing clinical prediction strategies (p < 0.05). Moreover, the P4 panels showed high sensitivity in AFP negative (0.857) HCC patients and PIVKA-II negative HCC patients (0.813). Most importantly, the P4 panels were validated to be perfectly accurate in predicting the conversion of LC to HCC (accuracy: 100.0%) with predicting HCC at a median of 12.6 months prior to imaging in a prospective external validation cohort, which was superior to existing clinical prediction strategies. These results suggested that proteomics-driven serum biomarker discovery provided a valuable reference for the liquid biopsy, and had great potential to improve early diagnosis of HCC.

Soil bacterial play special roles in the maintenance and stabilization of wetland ecosystem. To investigate bacterial community structure and diversity in rhizosphere soils of four dominant plants in riparian wetlands of mountain reservoir in Zhejiang province, the V4+V5 areas of 16S rDNA gene of bacteria were sequenced and analyzed by the Illumina HiSeq 2500 high-throughput sequencing technology. The results indicated that 27 phylums, 70 classes, 144 orders, 218 families, and 370 genuses of bacteria were achieved, with Proteobacteria, Acidobacteria,Actinobacteria and Bacteroidetes being the dominant phylum and Gammaproteobacteria, Deltaproteobacteria, Acidobacteria, Actinobacteria, Betaproteobacteria and Thermoleophilia being the main class in the soils of riparian wetlands in this areas. The Shannon index and chao1 index of the rhizosphere soil bacteria of Salix babylonica were 8.64 and 585.58, respectively, which were the highest among the four plants, and that of Pterocarya stenoptera were the lowest, with 7.71 and 289.63, respectively. Soil pH, total nitrogen and organic matter were the main factors affecting the soil bacterial community structure in the soil rhizosphere of four dominant plants species in wetlands of riparian zone of reservoir in Zhejiang province.