Diverse regulated cell death modes predict the immune microenvironment and drug sensitivity in lung adenocarcinoma.

Integrated action modes of regulated cell death (RCD) in lung adenocarcinoma (LUAD) have not been comprehensively dissected. Here, we adopted 15 RCD modes, including 1350 related genes, and established RCD signature scores. We found that LUAD patients with high RCD scores had a significantly worse prognosis in all four different cohorts (TCGA, KM-plotter, GSE31210, and GSE30219). Our nomogram established based on the RCD score and clinical characteristics performed well in both the discovery and validation sets. There was a close correlation between the RCD scores and LUAD molecular subtypes identified by unsupervised consensus clustering. Furthermore, we profiled the tumor microenvironment via deconvolution and found significant differences in immune activity, transcription factor activity and molecular pathway enrichment between the RCD-high and RCD-low groups. More importantly, we revealed that the regulation of antigen presentation is the crucial mechanism underlying RCD. In addition, higher RCD scores predict poorer sensitivity to multiple therapeutic drugs, which indicates that RCD scores may serve as a promising predictor of chemotherapy and immunotherapy outcomes. In summary, this work is the first to reveal the internal links between RCD modes, LUAD, and cancer immunity and highlights the necessity of RCD scores in personalizing treatment plans.

Leveraging circulating microbiome signatures to predict tumor immune microenvironment and prognosis of patients with non-small cell lung cancer.

BACKGROUND: Accumulating evidence supports the significant role of human microbiome in development and therapeutic response of tumors. Circulating microbial DNA is non-invasive and could show a general view of the microbiome of host, making it a promising biomarker for cancers. However, whether circulating microbiome is associated with prognosis of non-small cell lung cancer (NSCLC) and its potential mechanisms on tumor immune microenvironment still remains unknown. METHODS: The blood microbiome data and matching tumor RNA-seq data of TCGA NSCLC patients were obtained from Poore's study and UCSC Xena. Univariate and multivariate Cox regression analysis were used to identify circulating microbiome signatures associated with overall survival (OS) and construct the circulating microbial abundance prognostic scoring (MAPS) model. Nomograms integrating clinical characteristics and circulating MAPS scores were established to predict OS rate of NSCLC patients. Joint analysis of blood microbiome data and matching tumor RNA-seq data was used to deciphered the tumor microenvironment landscape of patients in circulating MAPS-high and MAPS-low groups. Finally, the predictive value of circulating MAPS on the efficacy of immunotherapy and chemotherapy were assessed. RESULTS: A circulating MAPS prediction model consisting of 14 circulating microbes was constructed and had an independent prognostic value for NSCLC. The integration of circulating MAPS into nomograms may improve the prognosis predictive power. Joint analysis revealed potential interactions between prognostic circulating microbiome and tumor immune microenvironment. Especially, intratumor plasma cells and humoral immune response were enriched in circulating MAPS-low group, while intratumor CD4 + Th2 cells and proliferative related pathways were enriched in MAPS-high group. Finally, drug sensitivity analysis indicated the potential of circulating MAPS as a predictor of chemotherapy efficacy. CONCLUSION: A circulating MAPS prediction model was constructed successfully and showed great prognostic value for NSCLC. Our study provides new insights of interactions between microbes, tumors and immunity, and may further contribute to precision medicine for NSCLC.

The long non-coding RNA HOXA11-AS activates ITGB3 expression to promote the migration and invasion of gastric cancer by sponging miR-124-3p.

BACKGROUND: miR-124-3p can inhibit integrin ß3 (ITGB3) expression to suppress the migration and invasion of gastric cancer (GC), and in the process lncRNA HOXA11-AS may act as a molecular sponge. METHODS: Luciferase reporter assay was conducted to verify the binding of miR-124-3p and HOXA11-AS. RT-PCR and western blot were performed to detect the expression of HOXA11-AS, miR-124-3p and ITGB3 in GC tissues and cells. Gene silence and overexpression experiments as well as cell migration and invasion assays on GC cell lines were performed to determine the regulation of molecular pathways, HOXA11-AS/miR-124-3p/ITGB3. Furthermore, the role of HOXA11-AS in GC was confirmed in mice models. RESULTS: We found HOXA11-AS is up-regulated in GC tissues and can bind with miR-124-3p. Through overexpression/knockdown experiments and function tests in vitro, we demonstrated HOXA11-AS can promote ITGB3 expression by sponging miR-124-3p, consequently enhance the proliferation, migration, and invasion of GC cells. Meanwhile, we validated that HOXA11-AS promotes migration and invasion of GC cells via down-regulating miR-124-3p and up-regulating ITGB3 in vivo. CONCLUSIONS: We demonstrated that lncRNA HOXA11-AS can increase ITGB3 expression to promote the migration and invasion of gastric cancer by sponging miR-124-3p. Our results suggested that HOXA11-AS may reasonably serve as a promising diagnostic biomarker and a potential therapeutic target of GC.

[Methylation Chip Screening and Verification of Differential Genes Related to Tuberculosis Infection].

OBJECTIVE: To screen the genes with significant changes in DNA methylation level in active tuberculosis patients, we used the methylation chips and expanded the sample size to verify candidate genes. METHODS: ① This study enrolled 9 cases of active tuberculosis patients, 3 cases of latent tuberculosis patients and 3 cases of healthy controls whose age and gender were all matched. Genome DNA was extracted from peripheral blood mononuclear cell in blood samples collected from these candidates, and bisulfite conversion treatment was then conducted. After hybridization with the Illumina HD 450K Infinium Mehtylation BeadChip, the results were compared between patients group and control group, and GO and KEGG pathway analyses were performed to evaluate the function of differentially expressed genes. ② We further enrolled 60 cases of active tuberculosis patients and 60 cases of health controls (age-and gender-matched), DNA was extracted from their peripheral blood and also followed bisulfite conversion treatment. Pyrosequencing method was used to detect the methylation levels of candidate genes (IFNGR2, PTPN6, CRK1, ATP6V0B, WIF1, DKK1 and SFRP1) screened by gene chip. RESULTS: Compared with healthy controls, the fragments in the patients that showed low methylation change accounted for the vast majority. Most of the methylation differential fragments (DMRs) were located in the main body region, followed by the upstream region of transcription initiation site, and the lowest DMRs distribution area was 3´UTR area. GO and Pathway analysis showed that the functions of the differentially methylated regions related genes are mainly enriched in the biological processes of the regulation of leukocyte differentiation, apoptosis, cytokine regulation and inflammatory response which are closely related to tuberculosis. There were 32 CpG sites involved in the verified 7 tuberculosis related genes, and 16 CpG locus showed significant difference (P<0.05), they were distributed in 6 genes: PTPN6, WIF1, CRK1, SFRP1, DKK1 and IFNGR2.Of these genes with significant difference, PTPN6 genes showed hypermethylation status and WIF1, CRK1, SFRP1, DKK1 and IFNGR2 genes exhibited demethylation status in the patients group compared to the health controls. SFRP1 and CRK-1 mRNA up-regulated in the patients group compared with health controls. CONCLUSION: In the course of MTB infection, the methylation status of genomic DNA is altered, and most of the differentially methylated regions (DMRs) are showed status of demethylation. The expressions ofSFRP1and CRK-1gene up-regulate in tuberculosis infection.

Allele frequency and proportion defined by circulating tumor DNA profiling predict tyrosine kinase inhibitors' therapeutic outcomes for non-small cell lung cancer.

PURPOSE: Circulating tumor DNA is more and more accessible for patients who cannot undergo biopsy. No consistent conclusion has been reached on whether frequency and proportion of mutations defined by ctDNA profiling can predict therapeutic outcomes. METHODS: One hundred patients with non-small cell lung cancer harboring activating EGFR mutations (exon 19 deletion, L858R and T790M mutation) were collected in West China hospital from December 18, 2017 to December 31, 2019. We retrospectively analyzed the frequency and proportion distribution of ctDNA mutations and its relationship with tyrosine kinase inhibitors therapeutic outcomes. RESULTS: Patients with lower frequency of sensitizing EGFR mutations (< 3%) had a longer progression-free survival (PFS) time than those with higher frequency (15 months vs. 10 months, p = 0.028). Moreover, patients with the lower ratio of T790M mutation frequency and the maximum-somatic-allele-frequency (T790M/MSAF < 30%) had a less prolonged PFS than those with higher T790M/MSAF (7 months vs. 15 months, p = 0.013). CONCLUSION: The frequency and proportion of ctDNA mutations are worth clinical attention in the prediction of therapeutic outcomes.

Immunogenetic polymorphisms predict therapeutic efficacy and survival outcomes in tumor patients receiving PD-1/PD-L1 blockade.

BACKGROUND: While immune checkpoint inhibitors (ICIs) demonstrate remarkable clinical responses, only a small subset of patients obtains benefits. Genes linked to the tumor immune system are confirmed to be critical for the treatment of ICIs, and their polymorphisms can contribute to ICI efficacy. Here, we examined the potential of immunogenetic variations to predict the efficacy and survival of the PD-1/PD-L1 blockade. METHODS: Cancerous patients receiving PD-1/PD-L1 blockade were recruited and followed up. Pivotal genes related to tumor-immunity were filtered through a protein-protein interaction network and the degree algorithm in Cytoscape. Finally, 39 genetic variants were genotyped through multiplex genotyping assays. Association analyses between variants and ICI efficacy and progression-free survival (PFS) were performed. RESULTS: Overall, 318 patients were ultimately enrolled. Hence, three immunogenetic variants were identified as predictors of PD-1/PD-L1 blockade response. Mutant alleles from ATG7 rs7625881, CD274 rs2297136, and TLR4 rs1927911 were all at increased risk of tumor progression following ICI therapy (OR: 1.475, 1.641, 1.462, respectively; P value: 0.028, 0.017, 0.027, respectively). Significant immunogenetic variants also attained similar trends in the PD-1 blockade, lung cancer, or lung cancer using PD-1 blockade subgroups. Furthermore, the mutant genotypes of CD274 rs2297136 (GG as the reference: HR: 0.50 (95%CI: 0.29-0.88), P value: 0.015) and TLR4 rs1927911 (AA as the reference: HR: 0.65 (95%CI: 0.47-0.91), P value: 0.012) indicated poorer PFS and were both independent prognostic factors. CONCLUSION: Immunogenetic polymorphisms, including ATG7 rs7625881, CD274 rs2297136, and TLR4 rs1927911, were first identified as potential predictors of response to PD-1/PD-L1 blockade in tumor patients.

Immunogenetic variations predict immune-related adverse events for PD-1/PD-L1 inhibitors.

BACKGROUND: PD-1/PD-L1 inhibitors have brought remarkable benefits but can cause profound immune-related adverse events (irAEs). The host immunogenetic background is likely to play a role in irAE susceptibility. In this study, we aimed to identify potential immunogenetic biomarkers to predict irAEs. METHODS: Patients with solid tumours receiving PD-1/PD-L1 blockade were recruited and followed up. Genes considered pivotal contributors to tumour-immunity and autoimmune diseases were screened out via protein-protein interaction network and Cytoscape. Consequently, thirty-nine variants in eighteen genes were genotyped using the multiplex genotyping assay. Association analysis between genetic variants and irAEs as well as irAEs-free survival was performed. RESULTS: Four immunogenetic variants as predictive biomarkers of irAEs were identified. The C allele of Mitogen-Activated Protein Kinase 1 (MAPK1) rs3810610 (odds ratio [OR] = 1.495, 95% confidence interval [CI] = 1.093-2.044, P = 0.012) was a risk predictor while the A allele of PTPRC rs6428474 (OR = 0.717, 95% CI = 0.521-0.987, P = 0.041) was a protective factor for all-grade irAEs. The A allele of ADAD1 rs17388568 (OR = 2.599, 95% CI = 1.355-4.983, P = 0.003) increased the risk while the G allele of IL6 rs1800796 (OR = 0.425, 95% CI = 0.205-0.881, P = 0.018) protected patients from high-grade irAEs. Significant immunogenetic variants reached a similar tendency in PD-1 blockade or lung cancer subgroups. In multivariate Cox regression analysis, the MAPK1 rs3810610 was an independent factor regarding all-grade irAEs-free survival (CC versus CT or TT: hazard ratio [HR] = 0.71, 95% CI = 0.52-0.99, P = 0.042). ADAD1 rs17388568 (AA versus AG or GG: HR = 0.11, 95% CI = 0.025-0.49, P = 0.004) and IL6 rs1800796 (GG or GC versus CC: HR = 3.10, 95% CI = 1.315-7.29, P = 0.01) were independent variables for high-grade irAEs-free survival. CONCLUSION: We first identified several immunogenetic polymorphisms associated with irAEs and irAEs-free survival in PD-1/PD-L1 blockade-treated tumour patients, and they may serve as potential predictive biomarkers.

A Promising Preoperative Prediction Model for Microvascular Invasion in Hepatocellular Carcinoma Based on an Extreme Gradient Boosting Algorithm.

Background: The non-invasive preoperative diagnosis of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is vital for precise surgical decision-making and patient prognosis. Herein, we aimed to develop an MVI prediction model with valid performance and clinical interpretability. Methods: A total of 2160 patients with HCC without macroscopic invasion who underwent hepatectomy for the first time in West China Hospital from January 2015 to June 2019 were retrospectively included, and randomly divided into training and a validation cohort at a ratio of 8:2. Preoperative demographic features, imaging characteristics, and laboratory indexes of the patients were collected. Five machine learning algorithms were used: logistic regression, random forest, support vector machine, extreme gradient boosting (XGBoost), and multilayer perception. Performance was evaluated using the area under the receiver operating characteristic curve (AUC). We also determined the Shapley Additive exPlanation value to explain the influence of each feature on the MVI prediction model. Results: The top six important preoperative factors associated with MVI were the maximum image diameter, protein induced by vitamin K absence or antagonist-II, α-fetoprotein level, satellite nodules, alanine aminotransferase (AST)/aspartate aminotransferase (ALT) ratio, and AST level, according to the XGBoost model. The XGBoost model for preoperative prediction of MVI exhibited a better AUC (0.8, 95% confidence interval: 0.74-0.83) than the other prediction models. Furthermore, to facilitate use of the model in clinical settings, we developed a user-friendly online calculator for MVI risk prediction based on the XGBoost model. Conclusions: The XGBoost model achieved outstanding performance for non-invasive preoperative prediction of MVI based on big data. Moreover, the MVI risk calculator would assist clinicians in conveniently determining the optimal therapeutic remedy and ameliorating the prognosis of patients with HCC.

Novel directions of precision oncology: circulating microbial DNA emerging in cancer-microbiome areas.

Microbiome research has extended into the cancer area in the past decades. Microbes can affect oncogenesis, progression, and treatment response through various mechanisms, including direct regulation and indirect impacts. Microbiota-associated detection methods and agents have been developed to facilitate cancer diagnosis and therapy. Additionally, the cancer microbiome has recently been redefined. The identification of intra-tumoral microbes and cancer-related circulating microbial DNA (cmDNA) has promoted novel research in the cancer-microbiome area. In this review, we define the human system of commensal microbes and the cancer microbiome from a brand-new perspective and emphasize the potential value of cmDNA as a promising biomarker in cancer liquid biopsy. We outline all existing studies on the relationship between cmDNA and cancer and the outlook for potential preclinical and clinical applications of cmDNA in cancer precision medicine, as well as critical problems to be overcome in this burgeoning field.

Cancer Genomic Alterations Can Be Potential Biomarkers Predicting Microvascular Invasion and Early Recurrence of Hepatocellular Carcinoma.

BACKGROUND: High recurrence incidence and poor survival after hepatectomy are enormous threats to hepatocellular carcinoma (HCC) patients, which can be caused by microvascular invasion (MVI). However, it is difficult to predict preoperative MVI status. In this study, we focus on cancer genomic alterations to comprehensively explore potential MVI and early recurrence biomarkers and provide clues to the mechanisms of HCC invasion and metastasis. METHODS: Forty-one patients with initially suspected HCC who were undergoing hepatectomy were finally enrolled. High-throughput targeted sequencing was performed on genomic alterations in their preoperative plasma and surgical fresh tumor tissues utilizing the 1,021-gene panel. RESULTS: HCC patients without MVI had longer RFS than MVI ones (p < 0.0001). The mutant incidence of genes like KEAP1, TP53, HIST1H3D, NFKBIA, PIK3CB, and WRN was higher in both MVI and early-recurrence patients than their counterparts. Besides, the alteration rates of Rap1 and Ras signaling pathways were significantly higher in MVI patients than NMVI ones (p < 0.05), and a similar trend of differences was also found in early-recurrence/non-recurrence comparison. The maximal variant allele frequency (VAF) of circulating tumor DNA (ctDNA) was statistically higher in MVI patients than NMVI ones (0.038 vs. 0.012, p = 0.0048). With the cutoff value of 0.018, ctDNA maximal VAF could potentially predict the presence of MVI with an AUC of 0.85 (95% CI 0.693-0.998, p = 0.0062). CONCLUSION: The integration of a panel containing specific mutated genes and ctDNA maximal VAF for predicting MVI and early recurrence of HCC may achieve better performance.

Ultrasensitive Nanopore Sensing of Mucin 1 and Circulating Tumor Cells in Whole Blood of Breast Cancer Patients by Analyte-Triggered Triplex-DNA Release.

The characterization of circulating tumor cells (CTCs) by liquid biopsy has a great potential for precision medicine in oncology. Here, a universal and tandem logic-based strategy is developed by combining multiple nanomaterials and nanopore sensing for the determination of mucin 1 protein (MUC1) and breast cancer CTCs in real samples. The strategy consists of analyte-triggered signal conversion, cascaded amplification via nanomaterials including copper sulfide nanoparticles (CuS NPs), silver nanoparticles (Ag NPs), and biomaterials including DNA hydrogel and DNAzyme, and single-molecule-level detection by nanopore sensing. The amplification of the non-DNA nanomaterial gives this method considerable stability, significantly lowers the limit of detection (LOD), and enhances the anti-interference performance for complicated samples. As a result, the ultrasensitive detection of MUC1 could be achieved in the range of 0.0005-0.5 pg/mL, with an LOD of 0.1 fg/mL. Moreover, we further tested MUC1 as a biomarker for the clinical diagnosis of breast cancer CTCs under double-blind conditions on the basis of this strategy, and MCF-7 cells could be accurately detected in the range from 5 to 2000 cells/mL, with an LOD of 2 cells/mL within 6 h. The detection results of the 19 clinical samples were highly consistent with those of the clinical pathological sections, nuclear magnetic resonance imaging, and color ultrasound. These results demonstrate the validity and reliability of our method and further proved the feasibility of MUC1 as a clinical diagnostic biomarker for CTCs.

Analysis of Factors Influencing Kidney Function of Recipients After Renal Transplantation in Southwestern China: A Retrospective Study.

Background: Factors influencing the kidney function of patients after renal transplantation include both recipient-related factors and donor-related factors. To gain a better understanding of these factors and to improve clinical decision-making, we performed a retrospective study of southwestern Chinese people receiving kidney transplantation. Methods: In this retrospective analysis, a total of 2,462 recipients receiving allogeneic kidney transplantation in West China Hospital of Sichuan University from December 13, 2008 to January 10, 2018 were included. Data on recipient and donor characteristics were extracted from the Transplant Center Database and stratified by discrete time points after kidney transplantation. Univariate and multivariate logistic regression analyses were carried out on the study variables, and kidney function of postoperative patients was monitored using cystatin C (CysC) as the outcome indicator. Results: From the univariate analysis, several factors showed statistically significant short-term impact on kidney function based on CysC after kidney transplantation, including age, ethnicity, body mass index (BMI), and HLA A-B-DR-DQ loci mismatch. Gender of recipients and gender-consistency between donors and recipients revealed both short-term and long-term influence. Younger donors had significantly better medium-and-long-term influence on kidney function. From the multivariate logistic regression analysis, recipient gender, ethnicity, BMI, and donor age were independent factors affecting postoperative CysC recovery at discrete time points. Conclusion: Several factors of recipients related to renal function after kidney transplantation, such as gender, ethnicity, BMI and donor's age should be paid more attention to. Moreover, female and non-Han recipients decreased the risk of poor outcome during postoperative kidney function recovery while large BMI of recipients and higher donor age increased the risk. It is useful to predict the postoperative renal function earlier according to corresponding factors, and improve the patient's quality of life.