Co-evolution of vaginal microbiome and cervical cancer.

BACKGROUND: Exploration of adaptive evolutionary changes at the genetic level in vaginal microbial communities during different stages of cervical cancer remains limited. This study aimed to elucidate the mutational profile of the vaginal microbiota throughout the progression of cervical disease and subsequently establish diagnostic models. METHODS: This study utilized a metagenomic dataset consisting of 151 subjects classified into four categories: invasive cervical cancer (CC) (n = 42), cervical intraepithelial neoplasia (CIN) (n = 43), HPV-infected (HPVi) patients without cervical lesions (n = 34), and healthy controls (n = 32). The analysis focused on changes in microbiome abundance and extracted information on genetic variation. Consequently, comprehensive multimodal microbial signatures associated with CC, encompassing taxonomic alterations, mutation signatures, and enriched metabolic functional pathways, were identified. Diagnostic models for predicting CC were established considering gene characteristics based on single nucleotide variants (SNVs). RESULTS: In this study, we screened and analyzed the abundances of 18 key microbial strains during CC progression. Additionally, 71,6358 non-redundant mutations were identified, predominantly consisting of SNVs that were further annotated into 25,773 genes. Altered abundances of SNVs and mutation types were observed across the four groups. Specifically, there were 9847 SNVs in the HPV-infected group and 14,892 in the CC group. Furthermore, two distinct mutation signatures corresponding to the benign and malignant groups were identified. The enriched metabolic pathways showed limited similarity with only two overlapping pathways among the four groups. HPVi patients exhibited active nucleotide biosynthesis, whereas patients with CC demonstrated a significantly higher abundance of signaling and cellular-associated protein families. In contrast, healthy controls showed a distinct enrichment in sugar metabolism. Moreover, biomarkers based on microbial SNV abundance displayed stronger diagnostic capability (cc.AUC = 0.87) than the species-level biomarkers (cc.AUC = 0.78). Ultimately, the integration of multimodal biomarkers demonstrated optimal performance for accurately identifying different cervical statuses (cc.AUC = 0.86), with an acceptable performance (AUC = 0.79) in the external testing set. CONCLUSIONS: The vaginal microbiome exhibits specific SNV evolution in conjunction with the progression of CC, and serves as a specific biomarker for distinguishing between different statuses of cervical disease.

A solid-state pulse power sub-nanosecond SiC DSRD-based generator with high-voltage and high repetition frequency for pulse discharge water treatment.

Water treatment is one of the most important issues for all walks of life around the world. The unique advantages of the solid-state power electronic pulses in water treatment make it attractive and promising in practical applications. The output voltage, rising time, repetition rate, and peak power of output pulses have a significant impact on the effectiveness of water treatment. Especially in pulse electric field treatment and pulse discharge treatment, the pulse with fast rising time achieves the advantage of generating plasma without corona, which can avoid water heating effect and greatly improve the efficiency of the pulse generator. High repetition rate can significantly reduce the peak power requirement of the pulse in water treatment application, making the equipment smaller and improving the power density. Therefore, the study developed a high-voltage high frequency sub-nanosecond pulse power generator (PPG) system for wastewater treatment. It adopts SiC DSRD (Drift Step Recovery Diode) solid-state switches and realize modular design, which can achieve high performance and can be flexible expanded according to the requirements of water treatment capacity. Finally, an expandable high-voltage PPG for water treatment is built. The output parameters of the PPG include output pulse voltage range from 1 to 5.28 kV, rise time <600 ps (20%-90%), repetition up to 1 MHz. The experiment results of PPG application for pulse discharge water treatment is presented. The results indicate that the proposed generator achieves high-efficiency degradation of 4-Chlorophenol (4-CP), which is one of the most common chlorophenol compounds in wastewater. From experiment, the homemade system can degrade 450 mL waste water containing 500 mg/L 4-CP in 35 min, with a degradation rate of 98%. Thereby, the requirement for electric field intensity decreased. Through the further quantitative analysis, the impact of frequency, voltage, and electrode spacing on the degradation effect of 4-CP is confirmed.

Prediction of Clinical Precision Chemotherapy by Patient-Derived 3D Bioprinting Models of Colorectal Cancer and Its Liver Metastases.

Methods accurately predicting the responses of colorectal cancer (CRC) and colorectal cancer liver metastasis (CRLM) to personalized chemotherapy remain limited due to tumor heterogeneity. This study introduces an innovative patient-derived CRC and CRLM tumor model for preclinical investigation, utilizing 3d-bioprinting (3DP) technology. Efficient construction of homogeneous in vitro 3D models of CRC/CRLM is achieved through the application of patient-derived primary tumor cells and 3D bioprinting with bioink. Genomic and histological analyses affirm that the CRC/CRLM 3DP tumor models effectively retain parental tumor biomarkers and mutation profiles. In vitro tests evaluating chemotherapeutic drug sensitivities reveal substantial tumor heterogeneity in chemotherapy responses within the 3DP CRC/CRLM models. Furthermore, a robust correlation is evident between the drug response in the CRLM 3DP model and the clinical outcomes of neoadjuvant chemotherapy. These findings imply a significant potential for the application of patient-derived 3DP cancer models in precision chemotherapy prediction and preclinical research for CRC/CRLM.

Interaction between intratumoral microbiota and tumor mediates the response of neoadjuvant therapy for rectal cancer.

Background: Previous observations have demonstrated that the response to neoadjuvant chemoradiotherapy (nCRT) is highly variable in patients with locally advanced rectal cancer (LARC). Recent studies focusing on the intratumoral microbiota of colorectal cancer have revealed its role in oncogenesis and tumor progression. However, limited research has focused on the influence of intratumoral microbiota on the nCRT of LARC. Methods: We explored the microbial profiles in the tumor microenvironment of LARC using RNA-seq data from a published European cohort. Microbial signatures were characterized in pathological complete response (pCR) and non-pCR groups. Multi-omics analysis was performed between intratumor microbiomes and transcriptomes. Results: Microbial α and ß diversity were significantly different in pCR and non-pCR groups. Twelve differential microbes were discovered between the pCR and non-pCR groups, six of which were related to subclusters of cancer-associated fibroblasts (CAFs) associated with extracellular matrix formation. A microbial risk score based on the relative abundance of seven differential microbes had predictive value for the nCRT response (AUC = 0.820, p < 0.001). Conclusion: Our study presents intratumoral microbes as potential independent predictive markers for the response of nCRT to LARC and demonstrates the underlying mechanism by which the interaction between intratumoral microbes and CAFs mediates the response to nCRT.

Intratumoural microbiome can predict the prognosis of hepatocellular carcinoma after surgery.

BACKGROUND: The dismal prognosis of hepatocellular carcinoma (HCC) is closely associated with characteristics of the tumour microenvironment (TME). Recent studies have confirmed the presence and potential influence of the microbiome in TME on cancer progression. Elucidating the relationship between microbes in the TME and cancer could provide valuable insights into novel diagnostic markers and therapeutic strategies for HCC and thus warrants a closer investigation of the role of intratumoural microbiome in the HCC TME. METHODS: We determined the presence of intratumoural microbiome using fluorescence in situ hybridisation, and explored the microbial community profiles in the HCC TME in paired tumour and adjacent normal tissues using 16S rDNA sequencing. Microbial signatures were characterised in the paired group, and their correlation with clinical characteristics was further investigated. We clustered the microbial signatures of tumour tissues by hepatotypes, and further analysis was performed to elucidate the independent prognostic value of the hepatotypes. RESULTS: This study revealed that microbial profiles and community networks differed notably between tumours and adjacent normal tissues. Proteobacteria and Actinobacteria were the most abundant phyla in the HCC TME. The TME microbial profiles also revealed heterogeneities between individuals and between multiple tumour lesions. Clustering of the microbial profiles into two hepatotypes revealed different microbial network patterns. Additionally, the hepatotypes were revealed to be independent prognostic factors in patients with resected HCC. CONCLUSIONS: Our study illuminates the microbial profiles in the TME of HCC and presents the hepatotype as a potential independent biomarker for the prognostic prediction of HCC after surgery.

3D bioprinted liver tissue and disease models: Current advances and future perspectives.

Three-dimensional (3D) bioprinting is a promising technology for fabricating complex tissue constructs with biomimetic biological functions and stable mechanical properties. In this review, the characteristics of different bioprinting technologies and materials are compared, and development in strategies for bioprinting normal and diseased hepatic tissue are summarized. In particular, features of bioprinting and other bio-fabrication strategies, such as organoids and spheroids are compared to demonstrate the strengths and weaknesses of 3D printing technology. Directions and suggestions, such as vascularization and primary human hepatocyte culture, are provided for the future development of 3D bioprinting.

Study on drug screening multicellular model for colorectal cancer constructed by three-dimensional bioprinting technology.

The existing in vitro models for antitumor drug screening have significant limitations. Many compounds that inhibit two-dimensional (2D) cultured cells do not exhibit the same pharmacological effects in vivo, thereby wasting human and material resources and time during drug development. Therefore, it is crucial to develop new models. Three-dimensional (3D) bioprinting technology has greater advantages in constructing human tissues than sandwich culture and organoid construction. We used 3D bioprinting technology to construct a 3D multicellular model of SW480 cells, tumor-associated macrophages, and endothelial cells. The biological activities of the model were evaluated by immunofluorescence, hematoxylin and eosin staining of frozen pathological sections, and transcriptome sequencing. Compared with 3D bioprinted single-cell model (3D printing-S), 3D bioprinted multicellular models (3D printing-M) showed significantly improved expression of tumor-related genes, including hub genes IL1B, FCGR2A, FCGR3A, CYBB, SPI1, CCL2, ITGAM, and ITGB2. Antitumor drug screening experiment showed that the IC50 values of 5-FU, oxaliplatin, and irinotecan in 3D printing-S group/2D culture group were 31.13 µM/12.79 µM, 26.79 µM/0.80 µM, and 16.73 µM/10.45 µM, respectively. Compared with the 3D printing-S group, 3D printing-M group was significantly more resistant to chemotherapy.

Characterization of immune features and immunotherapy response in subtypes of hepatocellular carcinoma based on mitophagy.

Mitophagy is suggested to be involved in tumor initiation and development; however, mitophagy heterogeneity in hepatocellular carcinoma (HCC) and its association with immune status and prognosis remain unclear. Differentially expressed genes (DEGs) were identified using expression profiles acquired from The Cancer Genome Atlas (TCGA). Mitophagy-related subtypes were identified using the ConsensusClusterPlus software. The differences in prognosis, clinical characteristics, and immune status, including immune cell infiltration, immune function, immune-checkpoint gene expression, and response to immunotherapy, were compared between subtypes. A mitophagy-related gene signature was constructed by applying least absolute shrinkage and selection operator regression to the TCGA cohort. The International Cancer Genome Consortium cohort and the cohort from Peking Union Medical College Hospital were utilized for validation. Carbonyl cyanide m-chlorophenylhydrazone was used to induce mitophagy in HCC cell lines to obtain our own mitophagy signature. Real-time polymerase chain reaction was used for the experimental validation of the expression of model genes. Two mitophagy-related subtypes with distinct prognoses, clinical characteristics, immune states, and biological function patterns were identified based on the mitophagy-related DEGs. The subtype that showed higher mitophagy-related DEG expression had worse survival outcomes, suppressed immune function, higher immune-checkpoint gene expression, and a better response to immunotherapy, indicating that this subpopulation in HCC may benefit from immune-checkpoint blockade therapy and other immunotherapies. A risk model consisting of nine mitophagy-related genes was constructed and its performance was confirmed in two validation cohorts. The risk score was an independent risk factor even when age, sex, and tumor stage were considered. Our study identified two distinct mitophagy subtypes and built a mitophagy signature, uncovering mitophagy heterogeneity in HCC and its association with immune status and prognosis. These findings shed light on the treatment of HCC, especially with immunotherapy.

Prognostic Value of the Albumin-to-γ-glutamyltransferase Ratio for Gallbladder Cancer Patients and Establishing a Nomogram for Overall Survival.

Purpose: The albumin-to-γ-glutamyltransferase ratio (AGR), a novel inflammation-related index, has been reported to have prognostic importance in several malignancies but not yet in gallbladder cancer (GBC). This study intended to assess the prognostic value of AGR in GBC and to develop a nomogram based on AGR for predicting overall survival (OS) in GBC patients after surgery. Methods: Medical records of 140 qualified GBC patients between July 2003 and June 2017 were retrospectively analyzed. The function "surv_cutpoint" in the R package "survminer" was implemented to discover the optimal cut-off value of AGR. A nomogram on the fundamental of Cox model was established in the training cohort and was internally validated using calibration curves, Harrell's concordance index, time-dependent AUC plots and decisive curve analyses. Results: The optimal AGR cut-off value concerning overall survival was 2.050. Univariate and multivariate analyses demonstrated that AGR (HR=0.354, P=0.004), T stage (HR=3.114, P=0.004), R0 resection (HR=0.448, P=0.003), BMI (HR=0.470, P=0.002) and CA19-9 (HR=1.704, P=0.048) were independent predictors for OS. The nomogram combining these prognostic factors showed considerable prognostic performance in term of consistency, discrimination and net benefit. Conclusion: AGR has independent prognostic value for OS in GBC patients receiving surgery. A nomogram incorporating AGR, T stage, R0 resection, CA19-9 and BMI achieved enhanced prognostic ability.

Controlling nutritional status score as a prognostic marker to predict overall survival in resected biliary tract cancers.

BACKGROUND: The aim of our study was to explore the prognostic significance of the preoperative controlling nutritional status (CONUT) score and establish a nomogram to predict overall survival (OS) and to achieve a more accurate prognostic risk stratification. METHODS: Clinicopathological records of 371 patients who underwent surgical resection for biliary tract cancers (BTC) from December 2002 to December 2017 were reviewed retrospectively. The associations of the CONUT score with clinicopathological factors and OS were evaluated. Univariate and multivariable Cox regression analysis were used to screen out independent predictors. A nomogram was developed and validated to estimate OS. RESULTS: The CONUT score was an independent predictor of OS [hazard ratio 1.478, 95% confidence interval (CI), 1.078-2.025, P=0.015]. And patients with a high CONUT score tended to have a poor prognosis with poor differentiation (P=0.011) of tumor cells and longer hospital stays (P=0.046). Besides the CONUT score, carbohydrate antigen 19-9, surgical method, and the American Joint Committee on Cancer (AJCC; 7th edition) TNM stage were contained in the final prognostic model. An OS nomogram was generated to visually predict 1-, 3-, and 5-year OS. The C-index was 0.714 (95% CI, 0.673-0.755) and 0.679 (95% CI, 0.616-0.742) in the development and validation cohort respectively. The nomogram provided superior discriminative power than the AJCC TNM staging system. The nomogram also demonstrated good risk stratification power in the entire cohort of BTC patients as well as for both BTC and surgical method subgroups. CONCLUSIONS: The nomogram based on the CONUT score can predict OS in patients with BTCs, and it performed better than the AJCC TNM staging system.

Comparison of Prognostic Value of Red Cell-Related Parameters of Biliary Tract Cancer After Surgical Resection and Integration of a Prognostic Nomogram: A Retrospective Study.

INTRODUCTION: Biliary tract cancer (BTC) comprises infrequently occurring neoplasms with poor prognoses. Red blood cell-related parameters are commonly reported prognostic factors. We aimed to compare and evaluate the clinical value of red blood cell-related parameters and develop a prognostic nomogram. METHODS: The analysis involved 418 patients with BTC who underwent surgery from December 2003 to April 2017. Patients were divided into training and validation cohorts. Red blood cell-related parameters were compared using Kaplan-Meier analysis, the area under receiver-operating characteristic curve (AUC), and C-index. Predictive abilities were evaluated using Cox regression. We developed a nomogram incorporating superior parameters verified using calibration curves, internal validation, and subgroup analysis. The nomogram was compared with the tumour-node-metastasis staging system through ROC, C-index, and Kaplan-Meier analysis. RESULTS: A combined parameter comprising haemoglobin, albumin, lymphocytes, and platelets (HALP), which was superior to other red blood cell-related parameters, indicated a high risk of worse overall survival when low. Univariate analysis revealed that HALP together with other clinical characteristics was associated with overall survival. Multivariate analysis revealed that HALP, tumour-node-metastasis staging, and operative outcome were independent predictors of poor overall survival. Internal validation proved the predictive value of the nomogram. Additional statistical analyses established the advantages of the nomogram vs. tumour-node-metastasis staging. CONCLUSION: HALP was a superior red blood cell-related parameter and an independent predictor of prognosis. Our nomogram based on HALP, tumour-node-metastasis staging, and operative outcome is a promising model for predicting overall survival.

Three-dimensional bioprinted hepatorganoids prolong survival of mice with liver failure.

OBJECTIVE: Shortage of organ donors, a critical challenge for treatment of end-stage organ failure, has motivated the development of alternative strategies to generate organs in vitro. Here, we aim to describe the hepatorganoids, which is a liver tissue model generated by three-dimensional (3D) bioprinting of HepaRG cells and investigate its liver functions in vitro and in vivo. DESIGN: 3D bioprinted hepatorganoids (3DP-HOs) were constructed using HepaRG cells and bioink, according to specific 3D printing procedures. Liver functions of 3DP-HOs were detected after 7 days of differentiation in vitro, which were later transplanted into Fah-deficient mice. The in vivo liver functions of 3DP-HOs were evaluated by survival time and liver damage of mice, human liver function markers and human-specific debrisoquine metabolite production. RESULTS: 3DP-HOs broadly acquired liver functions, such as ALBUMIN secretion, drug metabolism and glycogen storage after 7 days of differentiation. After transplantation into abdominal cavity of Fah-/-Rag2-/- mouse model of liver injury, 3DP-HOs further matured and displayed increased synthesis of liver-specific proteins. Particularly, the mice acquired human-specific drug metabolism activities. Functional vascular systems were also formed in transplanted 3DP-HOs, further enhancing the material transport and liver functions of 3DP-HOs. Most importantly, transplantation of 3DP-HOs significantly improved the survival of mice. CONCLUSIONS: Our results demonstrated a comprehensive proof of principle, which indicated that 3DP-HO model of liver tissues possessed in vivo hepatic functions and alleviated liver failure after transplantation, suggesting that 3D bioprinting could be used to generate human liver tissues as the alternative transplantation donors for treatment of liver diseases.

Unique TP53 neoantigen and the immune microenvironment in long-term survivors of Hepatocellular carcinoma.

Neoantigens are T-cell antigens derived from protein-coding mutations in tumor cells. Although neoantigens have recently been linked to anti-tumor immunity in long-term survivors of cancers such as melanoma, their prognostic and immune-modulatory role in many cancer types remain unexplored. We investigate neoantigens in hepatocellular carcinoma (HCC) through a combination of whole exome sequencing (WES), RNA sequencing (RNA-seq), computational bioinformation, and immunohistochemistry. Our analysis reveals that patients carried with TP53 neoantigen have a longer overall survival than others (p = 0.0371) and they showed higher Immune score (p = 0.0441), higher cytotoxic lymphocytes infiltration (p = 0.0428), and higher CYT score (p = 0.0388). In contrast, the prognosis is not associated with TMB and neoantigen load. Our study draws a preliminary conclusion that it is not TMB or neoantigen load but the TP53 specific neoantigen is related to overall survival of HCC patients. We suggest that the TP53 neoantigen may affect prognosis by regulating anti-tumor immunity and that the TP53 neoantigen may be harnessed as potential targets for immunotherapies of HCC.

Comparison of the Prognostic Value of Platelet-Related Indices in Biliary Tract Cancer Undergoing Surgical Resection.

PURPOSE: Platelet-related indices, including mean platelet volume (MPV) and plateletocrit (PCT), have been reported as new prognostic factors of overall survival (OS) in many cancers, but not yet in biliary tract cancer (BTC). We intended to assess these indices in predicting OS in BTC patients with the aim to build a new prognostic model for patients with BTC after surgical resection. MATERIALS AND METHODS: Survival analysis and time receiver operating characteristic analysis were applied to screen the platelet indices. Univariate and multivariate Cox analyses were used to identify independent prognostic factors and develop a new prognostic model. Harrell's C-statistics, calibration curves, and decisive curve analysis were used to assess the model. RESULTS: MPV and platelet distribution width (PDW)/PCT showed the best prognostic accuracy among the platelet indices. In multivariable analysis, factors predictive of poor OS were presence of nodal involvement, Non-radical surgery, poor tumor differentiation, carbohydrate antigen 19-9 > 100 U/mL, MPV > 8.1 fl, and PDW/PCT > 190. The new model was found to be superior to the TNM staging system and our new staging system showed higher discriminative power. CONCLUSION: MPV and PDW/PCT have high prognostic value in BTC patients, and the novel staging system based on these two indices showed good discrimination and accuracy compared with the American Joint Committee on Cancer 7th TNM staging system.