Association of Germline Variants in Natural Killer Cells With Tumor Immune Microenvironment Subtypes, Tumor-Infiltrating Lymphocytes, Immunotherapy Response, Clinical Outcomes, and Cancer Risk

Prognostic value of the international association for the study of lung cancer grading system and its association with the tumor microenvironment in stage I EGFR-muted lung adenocarcinoma

INTRODUCTION

The International Association for the Study of Lung Cancer (IASLC) grading system predicts early lung adenocarcinoma outcomes.

METHODS

The purpose of this study is to examine prognostic value of the IASLC grading system and its association with the tumor microenvironment (TME) in Stage I EGFR-muted lung adenocarcinoma. Based on the IASLC grading system, we compared the clinicopathological characteristics of EGFR-mutated lung adenocarcinoma (n = 296). In addition, we examined the expression level of E-cadherin in tumor cells and counted the number of tumor-infiltrating lymphocytes (TILs; CD8, CD20, CD138, and Foxp3), tumor-associated macrophages (TAMs; CD204), and cancer-associated fibroblasts (CAFs; podoplanin) using semi-automatic digital pathology image analysis.

RESULTS

Recurrence-free survival (RFS) curve showed that survival of grade 3 was significantly shorter than that of grade 1 (P < 0.01) and grade 2 (P = 0.03). Multivariate analysis of RFS revealed the invasive size, lymphatic permeation, and grade 3 (P < 0.01) as independent poor prognostic factors. The number of CD204 +TAMs and PDPN+CAFs was significantly higher in grade 3 than in grade 1 or 2 (all P < 0.01). Among the intermediate grade by the predominant subtype based classification, cases classified as grade 3 by the new classification had higher number of CD204 +TAMs (P < 0.01) and PDPN+CAFs (P = 0.02) than those classified as grade 2.

CONCLUSION

The IASLC grading system correlated with the outcomes of EGFR-mutated lung adenocarcinoma. Grade 3 was found to have the TME that most contributes to tumor progression, which probably explained their poor prognosis.

Sex and survival outcomes in patients with renal cell carcinoma receiving first-line immune-based combinations

BACKGROUND

There is an ongoing debate as to whether sex could be associated with immune checkpoint inhibitor (ICI) benefit. Existing literature data reveal contradictory results, and data on first-line immune combinations are lacking.

METHOD

This was a real-world, multicenter, international, observational study to determine the sex effects on the clinical outcomes in metastatic renal cell carcinoma (mRCC) patients treated with immuno-oncology combinations as first-line therapy.

RESULTS

A total of 1827 mRCC patients from 71 cancer centers in 21 countries were included. The median OS was 38.7 months (95% CI 32.7-44.2) in the overall study population: 40.0 months (95% CI 32.7-51.6) in males and 38.7 months (95% CI 26.4-41.0) in females (p = 0.202). The median OS was higher in males vs. females in patients aged 18-49y (36.9 months, 95% CI 29.0-51.6, vs. 24.8 months, 95% CI 16.8-40.4, p = 0.426, with + 19% of 2y-OS rate, 72% vs. 53%, p = 0.006), in the clear cell histology subgroup (44.2 months, 95% CI 35.8-55.7, vs. 38.7 months, 95% CI 26.0-41.0, p = 0.047), and in patients with sarcomatoid differentiation (34.4 months, 95% CI 26.4-59.0, vs. 15.3 months, 95% CI 8.9-41.0, p < 0.001). Sex female was an independent negative prognostic factor in the sarcomatoid population (HR 1.72, 95% CI 1.15 - 2.57, p = 0.008).

CONCLUSIONS

Although the female's innate and adaptive immunity has been observed to be more active than the male's, women in the subgroup of clear cell histology, sarcomatoid differentiation, and those under 50 years of age showed shorter OS than males.

A computational pipeline for identifying gene targets and signalling pathways in cancer cells to improve lymphocyte infiltration and immune checkpoint therapy efficacy

BACKGROUND

Tumour-infiltrating lymphocytes (TILs) are crucial for effective immune checkpoint blockade (ICB) therapy in solid tumours. However, ∼70% of these tumours exhibit poor lymphocyte infiltration, rendering ICB therapies less effective.

METHODS

We developed a bioinformatics pipeline integrating multiple previously unconsidered factors or datasets, including tumour cell immune-related pathways, copy number variation (CNV), and single tumour cell sequencing data, as well as tumour mRNA-seq data and patient survival data, to identify targets that can potentially improve T cell infiltration and enhance ICB efficacy. Furthermore, we conducted wet-lab experiments and successfully validated one of the top-identified genes.

FINDINGS

We applied this pipeline in solid tumours of the Cancer Genome Atlas (TCGA) and identified a set of genes in 18 cancer types that might potentially improve lymphocyte infiltration and ICB efficacy, providing a valuable drug target resource to be further explored. Importantly, we experimentally validated SUN1, which had not been linked to T cell infiltration and ICB therapy previously, but was one of the top-identified gene targets among 3 cancer types based on the pipeline, in a mouse colon cancer syngeneic model. We showed that Sun1 KO could significantly enhance antigen presentation, increase T-cell infiltration, and improve anti-PD1 treatment efficacy. Moreover, with a single-cell multiome analysis, we identified subgene regulatory networks (sub-GRNs) showing Stat proteins play important roles in enhancing the immune-related pathways in Sun1-KO cancer cells.

INTERPRETATION

This study not only established a computational pipeline for discovering new gene targets and signalling pathways in cancer cells that block T-cell infiltration, but also provided a gene target pool for further exploration in improving lymphocyte infiltration and ICB efficacy in solid tumours.

FUNDING

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Distinct CD16a features on human NK cells observed by flow cytometry correlate with increased ADCC

Natural killer (NK) cells destroy tissue that have been opsonized with antibodies. Strategies to generate or identify cells with increased potency are expected to enhance NK cell-based immunotherapies. We previously generated NK cells with increased antibody-dependent cell mediated cytotoxicity (ADCC) following treatment with kifunensine, an inhibitor targeting mannosidases early in the N-glycan processing pathway. Kifunensine treatment also increased the antibody-binding affinity of Fc γ receptor IIIa/CD16a. Here we demonstrate that inhibiting NK cell N-glycan processing increased ADCC. We reduced N-glycan processing with the CRIPSR-CAS9 knockdown of MGAT1, another early-stage N-glycan processing enzyme, and showed that these cells likewise increased antibody binding affinity and ADCC. These experiments led to the observation that NK cells with diminished N-glycan processing capability also revealed a clear phenotype in flow cytometry experiments using the B73.1 and 3G8 antibodies binding two distinct CD16a epitopes. We evaluated this "affinity profiling" approach using primary NK cells and identified a distinct shift and differentiated populations by flow cytometry that correlated with increased ADCC.

Inhibiting N-glycan processing increases the antibody binding affinity and effector function of human natural killer cells

Novel approaches are required to improve the efficacy of immunotherapies and increase the proportion of patients who experience a benefit. Antibody-dependent cell-mediated cytotoxicity (ADCC) contributes to the efficacy of many monoclonal antibodies therapies. Natural killer (NK) cells mediate ADCC, though responses are highly variable and depend on prior treatment as well as other factors. Thus, strategies to increase NK cell activity are expected to improve multiple therapies. Both cytokine treatment and NK cell receptor engineering are being explored to increase ADCC. Post-translational modifications, including glycosylation, are widely recognized as mediators of cellular processes but minimally explored as an alternative strategy to increase ADCC. We evaluated the impact of treatment with kifunensine, an inhibitor of asparagine-linked (N-)glycan processing, on ADCC using primary and cultured human NK cells. We also probed affinity using binding assays and CD16a structure with nuclear magnetic resonance spectroscopy. Treating primary human NK cells and cultured YTS-CD16a cells with kifunensine doubled ADCC in a CD16a-dependent manner. Kifunensine treatment also increased the antibody-binding affinity of CD16a on the NK cell surface. Structural interrogation identified a single CD16a region, proximal to the N162 glycan and the antibody-binding interface, perturbed by the N-glycan composition. The observed increase in NK cell activity following kifunensine treatment synergized with afucosylated antibodies, further increasing ADCC by an additional 33%. These results demonstrate native N-glycan processing is an important factor that limits NK cell ADCC. Furthermore, optimal antibody and CD16a glycoforms are defined that provide the greatest ADCC activity.

Natural killer cells strengthen antitumor activity of cisplatin by immunomodulation and ameliorate cisplatin-induced side effects

PURPOSE

Cisplatin-based chemotherapy is now an important treatment for improving bladder cancer prognosis. However, challenges in clinical treatment remain due to the numerous side effects of chemotherapy. Natural killer (NK) cells regulate certain immune responses and play a significant role in tumor surveillance and control. The efficacy of NK cells combined with cisplatin for chemoimmunotherapy in bladder cancer remains poorly understood.

METHODS

In this study, we established an MB49 tumor-bearing mouse model, tumor growth was measured in a control group and in groups treated with cisplatin, NK cells or both. Organ indices, biochemical indicators of blood serum, and expression of apoptotic proteins were used to assess the extent of organ damage. ELISA and immunohistochemistry were used to analyze the levels of immune cells and cytokine expression in serum, spleen, and tumor tissue.

RESULTS

NK cells combined with cisplatin exhibited better antitumor activity. NK cells also alleviated the organ damage caused by cisplatin and improved the survival rate. Treatment with NK cells increased the expression of IL-2 and IFN-γ as well as the number of CD4 + T cells. Additionally, cisplatin increased the expression of natural killer group 2, member D (NKG2D) ligands thus activating NK cells to kill tumor cells.

CONCLUSION

NK cells could alleviate the side effects of cisplatin treatment and enhance antitumor activity. The combination of NK cells and cisplatin thus provides a promising option for chemoimmunotherapy for bladder cancer.

Integrative Analysis Identified CD38 As a Key Node That Correlates Highly with Immunophenotype, Chemoradiotherapy Resistance, And Prognosis of Head and Neck Cancer

Head and neck cancer (HNC) is mainly treated by surgery, radiotherapy, and adjuvant chemotherapy; however, the prognosis of some patients with HNC is poor because of radiotherapy and chemotherapy resistance. In recent years, anti‑PD‑1 monoclonal antibodies have shown certain efficacy, and a change of the tumor immune microenvironment is the main reason for the failure of HNC immunotherapy. The present study aimed to identify and verify that CD38, which is closely related to the prognosis of HNC, is a potential biological marker of radiotherapy and chemotherapy resistance and PD-L1 immunotherapy resistance via a comprehensive bioinformatic analysis in The Cancer Genome Atlas and Gene Expression Omnibus databases. According to the UALCAN database, the transcript level of CD38 in HNC was analyzed using cluster analysis, and the expression of CD38 mRNA in HNC was detected using the Oncomine database. The characteristics of CD38-related oncogenes were identified by gene cluster enrichment analysis in LinkedOmics. The R2 and SEER databases were used to further evaluate the prognostic significance of the CD38 gene in HNC using receiver operating characteristic curve analysis of Kaplan-Meier (KM) survival and the clinical characteristics of the subjects. The protein-protein interaction network of the top 50 genes showing significant positive correlations with CD38 in HNC was analyzed using STRING. Finally, we used a nasopharyngeal carcinoma (NPC) cell line to verify the biological function. The results showed that the levels of CD38 mRNA expression in patients with HNC were significantly higher than those in healthy controls. The levels of CD38 mRNA expression in patients with HNC of different ages, sexes, and races were significantly higher than those in the healthy controls. CD38 is an independent prognostic factor for HNC, and high expression of CD38 indicates poor prognosis. CD38 expression correlated positively with the markers of many kinds of immune cells, and correlated significantly with the expression of PD-L1. We found that the high expression of CD38 suggested a poor prognosis in the subgroup of tumors treated with chemotherapeutic drugs in the G1/S phase. We used HNC cell lines to verify that the high expression of CD38 promoted the proliferation of NPC cells and produced radiotherapy tolerance. Through comprehensive bioinformatics analysis, we suggested that CD38 is a key gene involved in radiotherapy, chemotherapy, and immune drug resistance in HNC. This study provides a reliable biomarker to predict the prognosis of patients with HNC and a reference for clinical comprehensive treatment of HNC. Individualization combined with CD38 monoclonal antibodies might provide a promising treatment strategy for this fatal disease, and this comprehensive treatment might reduce the damage to normal tissue and improve the prognosis and quality of life of patients with HNC.

T Cell-Mediated Tumor Killing-Related Classification of the Immune Microenvironment and Prognosis Prediction of Lung Adenocarcinoma

BACKGROUND

Although immune checkpoint inhibitors (ICI) are a promising therapeutic strategy for lung adenocarcinoma (LUAD), individual subgroups that might benefit from them are yet to be identified. As T cell-mediated tumor killing (TTK) is an underlying mechanism of ICI, we identified subtypes based on genes associated with TTK sensitivity and assessed their predictive significance for LUAD immunotherapies.

METHODS

Using high-throughput screening techniques, genes regulating the sensitivity of T cell-mediated tumor killing (GSTTK) with differential expression and associations with prognosis were discovered in LUAD. Furthermore, patients with LUAD were divided into subgroups using unsupervised clustering based on GSTTK. Significant differences were observed in the tumor immune microenvironment (TIME), genetic mutation and immunotherapy response across subgroups. Finally, the prognostic significance of a scoring algorithm based on GSTTK was assessed.

RESULTS

A total of 6 out of 641 GSTTK exhibited differential expression in LUAD and were associated with prognosis. Patients were grouped into two categories based on the expression of the six GSTTK, which represented different TTK immune microenvironments in LUAD. Immune cell infiltration, survival difference, somatic mutation, functional enrichment and immunotherapy responses also varied between the two categories. Additionally, a scoring algorithm accurately distinguished overall survival rates across populations.

CONCLUSIONS

TTK had a crucial influence on the development of the varying TIME. Evaluation of the varied TTK modes of different tumors enhanced our understanding of TIME characteristics, wherein the changes in T cell activity in LUAD are reflected. Thus, this study guides the development of more effective therapeutic methods.

Impaired intratumoral natural killer cell function in head and neck carcinoma

Natural killer (NK) cells are emerging as unique players in the immune response against cancer; however, only limited data are available on tumor infiltrating NK cells in head and neck squamous cell carcinoma (HNSCC), one of the most common cancer. Occurrence of HNSCC is closely related to the immune microenvironment, and immunotherapy is increasingly being applied to this setting. However, the limited success of this type of treatment in this tumor calls for further investigation in the field.

Surgical HNSSC specimens of 32 consecutive patients were mechanically and enzymatically dissociated. Tumor cells were separated from infiltrating cells by short centrifugation and infiltrating NK cells were phenotypically and functionally characterized by multiple antibody staining and flow cytometry. Tumor infiltrating NK cells in HNSCC showed a peculiar phenotype predominantly characterized by increased NKG2A and reduced Siglec-7, NKG2D, NKp30 and CD16 expression. This phenotype was associated with a decreased ability to perform antibody-dependent cellular cytotoxicity (ADCC). However, NK, CD4 and CD8 shared an increment of glucocorticoid-induced tumor necrosis factor-related (GITR) costimulatory receptor which could be exploited for immunotherapy with agonistic anti-GITR antibodies combined with checkpoint inhibitors.

The expression and methylation of PITX genes is associated with the prognosis of head and neck squamous cell carcinoma

Background: The PITX gene family, comprising PITX1, PITX2, and PITX3, is critical in organogenesis and has been evolutionary conserved in animals. PITX genes are associated with the advanced progression and poor prognosis of multiple cancers. However, the relationship between the PITX genes and head and neck squamous cell carcinoma (HNSC) has not been reported.

Methods: We used data from The Cancer Genome Atlas (TCGA) to analyze the association between PITX mRNA expression and clinicopathological parameters of patients with HNSC. The prognostic value of PITX genes was evaluated using the Kaplan-Meier plotter. Multivariate Cox analysis was used to screen out prognosis-associated genes to identify better prognostic indicators. The potential roles of PITX1 and PITX2 in HNSC prognosis were investigated using the protein-protein interaction (PPI) network, Gene Ontology (GO) analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The correlation between PITX1 and PITX2 expression or methylation and immune cell infiltration was evaluated using the tumor-immune system interaction database (TISIDB). MethSurv was used to identify DNA methylation and its effect on HNSC prognosis.

Results:PITX genes expression was correlated with different cancers. PITX1 and PITX2 expression was lower in the patients with HNSC. In HNSC, PITX1 expression was significantly related to the clinical stage, histologic grade, and N stage, while PITX2 expression was only significantly related to the histologic grade. The high expression of PITX3 was significantly related to the histologic grade, T stage, and N stage. Survival analysis revealed that PITX genes had prognostic value in HNSC, which was supported by multivariate Cox analysis. PPI network and enrichment analysis showed that the genes interacting with PITX1 and PITX2 belonged predominantly to signaling pathways associated with DNA binding and transcription. Of the CpG DNA methylation sites in PITX1 and PITX2, 28 and 22 were related to the prognosis of HNSC, respectively. Additionally, PITX1 and PITX2 expression and methylation was associated with tumor-infiltrating lymphocytes (TILs).

Conclusion: The PITX genes were differentially expressed in patients with HNSC, highlighting their essential role in DNA methylation and tumor-infiltrating immune cell regulation, as well as overall prognostic value in HNSC.

Prognostic stratification based on m5C regulators acts as a novel biomarker for immunotherapy in hepatocellular carcinoma

Background

Immunotherapy is a promising anti-cancer strategy in hepatocellular carcinoma (HCC). However, a limited number of patients can benefit from it. There are currently no reliable biomarkers available to find the potential beneficiaries. Methylcytosine (m⁵C) is crucial in HCC, but its role in forecasting clinical responses to immunotherapy has not been fully clarified.

Methods

In this study, we analyzed 371 HCC patients from The Cancer Genome Atlas (TCGA) database and investigated the expression of 18 m⁵C regulators. We selected 6 differentially expressed genes (DEGs) to construct a prognostic risk model as well as 2 m⁵C-related diagnostic models.

Results

The 1-, 3-, and 5-year area under the curve (AUC) of m⁵C scores for the overall survival (OS) was 0.781/0.762/0.711, indicating the m⁵C score system had an ideal distinction of prognostic prediction for HCC. The survival analysis showed that patients with high-risk scores present a worse prognosis than the patients with low-risk scores (p< 0.0001). We got consistent results in 6 public cohorts and validated them in Xiangya real-world cohort by quantitative real-time PCR and immunohistochemical (IHC) assays. The high-m⁵C score group was predicted to be in an immune evasion state and showed low sensitivity to immunotherapy, but high sensitivity to chemotherapy and potential targeted drugs and agents, such as sepantronium bromide (YM-155), axitinib, vinblastine and docetaxel. Meanwhile, we also constructed two diagnostic models to distinguish HCC tumors from normal liver tissues or liver cirrhosis.

Conclusion

In conclusion, our study helps to early screen HCC patients and select patients who can benefit from immunotherapy. Step forwardly, for the less likely beneficiaries, this study provides them with new potential targeted drugs and agents for choice to improve their prognosis.

Immune Infiltration-Related ceRNA Network Revealing Potential Biomarkers for Prognosis of Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC.

Materials and Methods

ESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed.

Results

Survival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress.

Conclusion

In conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

Glioblastoma Associated Natural Killer Cell EVs Generating Tumour-Specific Signatures: Noninvasive GBM Liquid Biopsy with Self-Functionalized Quantum Probes

Diagnosis of glioblastoma (GBM) poses a recurring struggle due to many factors, including the presence of the blood-brain barrier (BBB) in addition to the significant tumor heterogeneity. Natural killer (NK) cells of the innate immune system are the primary immune surveillance mechanism for GBM and identify GBM tumors without any previous sensitization. The metabolic reprogramming of NK cells during GBM association is expected to be reflected in its extracellular vesicles. Therefore, tracking the activity of NK cell vesicles in circulation (circulating immune vesicles, CIVs) has great potential for accurate GBM diagnosis. However, identification GBM associated CIVs in circulation is immensely challenging as there is no availability of clinically validated GBM-specific circulating biomarkers. Here, we present GBM associated CIV profiling for noninvasive GBM diagnosis. We investigated the feasibility of using the signals derived from GBM associated CIVs as a de novo methodology for GBM diagnosis. An ultrasensitive sensor and a marker-free approach were essential for the detection of rare signals of GBM associated CIVs. For this purpose, we designed GBM ImmunoProfiler platform using scalable ultrafast laser multiphoton ionization mechanism and adopted surface enhanced Raman spectroscopy (SERS) ensuring simultaneous detection of multiple CIV signals to identify GBM. We experimentally demonstrated that GBM associated CIVs carry unique, tumor-specific signals. The features of GBM associated CIVs were explored through machine learning identifying its similarity with GBM patient blood (without cell isolation) using a very small amount of peripheral blood (5 μL) with 96.82% sensitivity and 100% specificity. In addition, we demonstrated that a tumor associated CIV profile can classify between multiple brain cancer types (astrocytoma, oligodendroglioma, and glioblastoma). We also experimentally demonstrated significant variation in the immune checkpoint protein expression (PDL-1 and CTLA-4) between GBM associated CIVs and uninteracted CIVs. Preclinical analysis with serum specimens of GBM patients showed the possibility of using our technology for minimally invasive GBM diagnosis. With clinical validation, our technology has potential to improve GBM diagnostics with a useful, minimally invasive GBM liquid biopsy.

TGFBR1*6A as a modifier of breast cancer risk and progression: advances and future prospects

There is growing evidence that germline mutations in certain genes influence cancer susceptibility, tumor evolution, as well as clinical outcomes. Identification of a disease-causing genetic variant enables testing and diagnosis of at-risk individuals. For breast cancer, several genes such as BRCA1, BRCA2, PALB2, ATM, and CHEK2 act as high- to moderate-penetrance cancer susceptibility genes. Genotyping of these genes informs genetic risk assessment and counseling, as well as treatment and management decisions in the case of high-penetrance genes. TGFBR1*6A (rs11466445) is a common variant of the TGF-β receptor type I (TGFBR1) that has a global minor allelic frequency (MAF) of 0.051 according to the 1000 Genomes Project Consortium. It is emerging as a high frequency, low penetrance tumor susceptibility allele associated with increased cancer risk among several cancer types. The TGFBR1*6A allele has been associated with increased breast cancer risk in women, OR 1.15 (95% CI 1.01–1.31). Functionally, TGFBR1*6A promotes breast cancer cell proliferation, migration, and invasion through the regulation of the ERK pathway and Rho-GTP activation. This review discusses current findings on the genetic, functional, and mechanistic associations between TGFBR1*6A and breast cancer risk and proposes future directions as it relates to genetic association studies and mechanisms of action for tumor growth, metastasis, and immune suppression.

Role of germline variants in the metastasis of breast carcinomas

Most cancer-related deaths in breast cancer patients are associated with metastasis, a multistep, intricate process that requires the cooperation of tumour cells, tumour microenvironment and metastasis target tissues. It is accepted that metastasis does not depend on the tumour characteristics but the host’s genetic makeup. However, there has been limited success in determining the germline genetic variants that influence metastasis development, mainly because of the limitations of traditional genome-wide association studies to detect the relevant genetic polymorphisms underlying complex phenotypes. In this work, we leveraged the extreme discordant phenotypes approach and the epistasis networks to analyse the genotypes of 97 breast cancer patients. We found that the host’s genetic makeup facilitates metastases by the dysregulation of gene expression that can promote the dispersion of metastatic seeds and help establish the metastatic niche—providing a congenial soil for the metastatic seeds.

Identification of tumour immune infiltration-associated snoRNAs (TIIsno) for predicting prognosis and immune landscape in patients with colon cancer via a TIIsno score model

Background

Colon cancer (CC) is the leading cause of tumour-related death worldwide. SnoRNA plays a critical role in the tumour microenvironment. The tumour microenvironment can be shaped by tumour-infiltrating immune cells, which control the destiny of immunotherapy efficacy. This study uniquely focused on snoRNAs derived from immune cells to identify new biomarkers for immune landscape.

Methods

A novel computational framework was initiated for identifying tumour immune infiltration-associated snoRNAs (TIIsno) signatures and developed a TIIsno score model from integrative snoRNA profiling analysis of 21 purified immune cell lines, 43 colon cancer cell lines, and three datasets (training, test, real-world validation set).

Findings

Our study found that a high TIIsno score was associated with poor CC prognosis. TIIsno scores were seen to be negatively correlated with (I) the infiltration level of most immune cells, (II) the inhibitory immune checkpoints expression level, and (III) the immune score. These findings, taken together with the observation that TIIsno score is lower in MSI-H patients, suggests that patients with a low TIIsno score may have a better response to immunotherapy.

Interpretation

In conclusion, we successfully identified TIIsno and constructed a TIIsno score model, a new potential biomarker of immunotherapy response, which can effectively predict the prognosis of CC patients as well.

Funding

National Key R & D Program of China, National Natural Science Foundation of China, key projects from the Nature Science Foundation of Hunan Province, projects from Beijing CSCO Clinical Oncology Research Foundation, Fundamental Research Funds for the Central Universities of Central South University.

The Expression Quantitative Trait Loci in Immune Response Genes Impact the Characteristics and Survival of Colorectal Cancer

The impact of germline variants on the regulation of the expression of tumor microenvironment (TME)-based immune response genes remains unclear. Expression quantitative trait loci (eQTL) provide insight into the effect of downstream target genes (eGenes) regulated by germline-associated variants (eVariants). Through eQTL analyses, we illustrated the relationships between germline eVariants, TME-based immune response eGenes, and clinical outcomes. In this study, both RNA sequencing data from primary tumor and germline whole-genome sequencing data were collected from patients with stage III colorectal cancer (CRC). Ninety-nine high-risk subjects were subjected to immune response gene expression analyses. Seventy-seven subjects remained for further analysis after quality control, of which twenty-two patients (28.5%) experienced tumor recurrence. We found that 65 eQTL, including 60 germline eVariants and 22 TME-based eGenes, impacted the survival of cancer patients. For the recurrence prediction model, 41 differentially expressed genes (DEGs) achieved the best area under the receiver operating characteristic curve of 0.93. In total, 19 survival-associated eGenes were identified among the DEGs. Most of these genes were related to the regulation of lymphocytes and cytokines. A high expression of HGF, CCR5, IL18, FCER1G, TDO2, IFITM2, and LAPTM5 was significantly associated with a poor prognosis. In addition, the FCER1G eGene was associated with tumor invasion, tumor nodal stage, and tumor site. The eVariants that regulate the TME-based expression of FCER1G, including rs2118867 and rs12124509, were determined to influence survival and chromatin binding preferences. We also demonstrated that FCER1G and co-expressed genes in TME were related to the aggregation of leukocytes via pathway analysis. By analyzing the eQTL from the cancer genome using germline variants and TME-based RNA sequencing, we identified the eQTL in immune response genes that impact colorectal cancer characteristics and survival.

Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis

Objectives

Patients with head and neck squamous cell carcinoma (HNSCC) have poor prognosis and show poor responses to immune checkpoint (IC) inhibitor (ICI) therapy. Competing endogenous RNA (ceRNA) networks, tumor-infiltrating immune cells (TIICs), and ICIs may influence tumor prognosis and response rates to ICI therapy. This study is aimed at identifying prognostic and IC-related biomarkers and key TIIC signatures to improve prognosis and ICI therapy response in HNSCC patients.

Methods and Results

Ninety-five long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and 1746 mRNAs were identified using three independent methods. We constructed a ceRNA network and estimated the proportions of 22 immune cell subtypes. Ten ceRNAs were related to prognosis according to Kaplan–Meier analysis. Two risk signatures based, respectively, on nine ceRNAs (ANLN, CFL2, ITGA5, KDELC1, KIF23, NFIA, PTX3, RELT, and TMC7) and three immune cell types (naïve B cells, neutrophils, and regulatory T cells) via univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses could accurately and independently predict the prognosis of HNSCC patients. Key mRNAs in the ceRNA network were significantly correlated with naïve B cells and regulatory T cells and with stage, grade, and immune and molecular subtype. Eight IC genes exhibited higher expression in tumor tissues and were correlated with eight key mRNAs in the ceRNA network in HNSCC patients with different HPV statuses according to coexpression and TIMER 2.0 analyses. Most drugs were effective in association with expression of these key signatures (ANLN, CFL2, ITGA5, KIF23, NFIA, PTX3, RELT, and TMC7) based on GSCALite analysis. The prognostic value of key biomarkers and associations between key ceRNAs and IC genes were validated using online databases. Eight key ceRNAs were confirmed to predict response to ICI in other cancers based on TIDE analysis.

Conclusions

We constructed two risk signatures to accurately predict prognosis in HNSCC. Key IC-related signatures may be associated with response to ICI therapy. Combinations of ICIs with inhibitors of eight key mRNAs may improve survival outcomes of HNSCC patients.

Immune Microenvironment and Response in Prostate Cancer Using Large Population Cohorts

Immune microenvironment of prostate cancer (PCa) is implicated in disease progression. However, previous studies have not fully explored PCa immune microenvironment. This study used ssGSEA algorithm to explore expression levels of 53 immune terms in a combined PCa cohort (eight cohorts; 1,597 samples). The top 10 immune terms were selected based on the random forest analysis and used for immune-related risk score (IRS) calculation. Furthermore, we explored differences in clinical and genomic features between high and low IRS groups. An IRS signature based on the 10 immune terms showed high prediction potential for PCa prognosis. Patients in the high IRS group showed significantly higher percentage of immunotherapy response factors, implying that IRS is effective in predicting immunotherapy response rate. Furthermore, consensus clustering was performed to separate the population into three IRSclusters with different clinical outcomes. Patients in IRScluster3 showed the worst prognosis and highest immunotherapy response rate. On the other hand, patients in IRScluster2 showed better prognosis and low immunotherapy response rate. In addition, VGLL3, ANPEP, CD38, CCK, DPYS, CST2, COMP, CRISP3, NKAIN1, and F5 genes were differentially expressed in the three IRSclusters. Furthermore, CMap analysis showed that five compounds targeted IRS signature, thioridazine, trifluoperazine, 0175029-0000, trichostatin A, and fluphenazine. In summary, immune characteristics of PCa tumor microenvironment was explored and an IRS signature was constructed based on 10 immune terms. Analysis showed that this signature is a useful tool for prognosis and prediction of immunotherapy response rate of PCa.

CARD11 is a prognostic biomarker and correlated with immune infiltrates in uveal melanoma

Uveal melanoma (UVM), the most common primary intraocular malignancy, has a high mortality because of a high propensity to metastasize. Our study analyzed prognostic value and immune-related characteristics of CARD11 in UVM, hoping to provide a potential management and research direction. The RNA-sequence data of 80 UVM patients were downloaded from The Cancer Genome Atlas database and divided them into high- and low-expression groups. We analyzed the differentially expressed genes, enrichment analyses and the infiltration of immune cells using the R package and Gene-Set Enrichment Analysis. A clinical prediction nomogram and protein-protein interaction network were constructed and the first 8 genes were considered as the hub-genes. Finally, we constructed a competing endogenous RNA (ceRNA) network by Cytoscape and analyzed the statistical data via the R software. Here we found that CARD11 expression had notable correlation with UVM clinicopathological features, which was also an independent predictor for overall survival (OS). Intriguingly, CARD11 had a positively correlation to autophagy, cellular senescence and apoptosis. Infiltration of monocytes was significantly higher in low CARD11 expression group, and infiltration of T cells regulatory was lower in the same group. Functional enrichment analyses revealed that CARD11 was positively related to T cell activation pathways and cell adhesion molecules. The expressions of hub-genes were all increased in the high CARD11 expression group and the ceRNA network showed the interaction among mRNA, miRNA and lncRNA. These findings show that high CARD11 expression in UVM is associated with poor OS, indicating that CARD11 may serve as a potential biomarker for the diagnosis and prognosis of the UVM.

Association of genetic variants of FBXO32 and FOXO6 in the FOXO pathway with breast cancer risk

Forkhead box class O (FOXO) transcription factors play a pivotal role in regulating a variety of biological processes, including organismal development, cell signaling, cell metabolism, and tumorigenesis. Therefore, we hypothesize that genetic variants in FOXO pathway genes are associated with breast cancer (BC) risk. To test this hypothesis, we conducted a large meta-analysis using 14 published genome-wide association study (GWAS) data sets in the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) study. We assessed associations between 5214 (365 genotyped in DRIVE and 4849 imputed) common single-nucleotide polymorphisms (SNPs) in 55 FOXO pathway genes and BC risk. After multiple comparison corrections by the Bayesian false-discovery probability method, we found five SNPs to be significantly associated with BC risk. In stepwise multivariate logistic regression analysis with adjustment for age, principal components, and previously published SNPs in the same data set, three independent SNPs (i.e., FBXO32 rs10093411 A>G, FOXO6 rs61229336 C>T, and FBXO32 rs62521280 C>T) remained to be significantly associated with BC risk (p = 0.0008, 0.0011, and 0.0017, respectively). Additional expression quantitative trait loci analysis revealed that the FBXO32 rs62521280 T allele was associated with decreased messenger RNA (mRNA) expression levels in breast tissue, while the FOXO6 rs61229336 T allele was found to be associated with decreased mRNA expression levels in the whole blood cells. Once replicated by other investigators, these genetic variants may serve as new biomarkers for BC risk.

Genetic variants in the human leukocyte antigen region and survival of Chinese patients with non-small cell lung carcinoma

Human leukocyte antigen (HLA) is highly polymorphic, driving antigen presentation, complement cascade and leukocyte maturation against cancer cells. Therefore, we extracted genotyping data in the HLA region from an ongoing Chinese genome-wide association study of non-small cell lung cancer (NSCLC). Using deep sequencing data of 10 689 healthy Han Chinese, we imputed for untyped genetic variants in the HLA region, followed by a two-stage survival analysis of 1531 NSCLC patients. In the discovery stage of 758 patients, we identified 301 out of 15 138 single-nucleotide polymorphisms to be independently associated with overall survival [P < 0.05 and Bayesian false-discovery probability < 0.8]. In further validation of another 773 patients, we confirmed chromosome 6p21, rs241424 (located at intron 3 of TAP2) and rs6457642 as two independent survival predictors. In the combined analysis of 1531 NSCLC patients, rs241424 G>A and rs6457642 C>T were associated with a hazards ratio of 1.26 [95% confidence interval (CI) = 1.14-1.40 and P = 4.04 × 10-6] and 0.76 (95% CI = 0.66-0.87 and P = 1.16 × 10-4), respectively. The analysis of publically available ChIP-sequencing and Hi-C data found that the rs241424 locus was involved in potential cis-regulatory element by a long-range interaction with the HLA-DQA1 promoter. Additional expression quantitative trait loci analysis showed that the rs241424 G>A change decreased HLA-DQA1 mRNA expression. Furthermore, expression levels of HLA-DQA1 were lower in lung cancer tissues than in adjacent normal tissues, and the lower expression was associated with a worse prognosis for patients with lung adenocarcinoma. Collectively, HLA genetic variants may modulate OS of NSCLC patients, possibly via a mechanism of long-range promoter interaction regulating HLA-DQA1 expression.

CD2 Is a Novel Immune-Related Prognostic Biomarker of Invasive Breast Carcinoma That Modulates the Tumor Microenvironment

Female breast cancer (BCa) is the most commonly occurring cancer worldwide. The tumor microenvironment (TME) plays an essential role in tumor invasion, angiogenesis, unlimited proliferation, and even immune escape, but we know little about the TME of BCa. In this study, we aimed to find a TME-related biomarker for BCa, especially for invasive breast carcinoma (BRCA), that could predict prognosis and immunotherapy efficacy. Based on RNA-seq transcriptome data and the clinical characteristics of 1222 samples (113 normal and 1109 tumor samples) from The Cancer Genome Atlas (TCGA) database, we used the ESTIMATE algorithm to calculate the ImmuneScore and StromalScore and then identified differentially expressed genes (DEGs) between the high and low ImmuneScore groups and the high and low StromalScore groups. Thereafter, a protein–protein interaction (PPI) network analysis and univariate Cox regression analyses of overall survival were used to identify potential key genes. Five candidate genes were identified, comprising CD2, CCL19, CD52, CD3E, and ITK. Thereafter, we focused on CD2, analyzing CD2 expression and its association with survival. CD2 expression was associated with tumor size (T stage) to some extent, but not with overall TNM stage, lymph node status (N stage), or distant metastasis (M stage). High CD2 expression was associated with longer survival. METABRIC data were used to validate the survival result (n = 276). Gene set enrichment analysis (GSEA) showed that the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly associated with high CD2 expression were mainly immune-related pathways. Furthermore, CD2 expression was correlated with 16 types of tumor-infiltrating immune cells (TICs). Hence, CD2 might be a novel biomarker in terms of molecular typing, and it may serve as a complementary approach to TNM staging to improve clinical outcome prediction for BCa patients.

The landscape of different molecular modules in an immune microenvironment during tuberculosis infection

Tuberculosis is a chronic inflammatory disease caused by Mycobacterium tuberculosis. When tuberculosis invades the human body, innate immunity is the first line of defense. However, how the innate immune microenvironment responds remains unclear. In this research, we studied the function of each type of cell and explained the principle of an immune microenvironment. Based on the differences in the innate immune microenvironment, we modularized the analysis of the response of five immune cells and two structural cells. The results showed that in the innate immune stress response, the genes CXCL3, PTGS2 and TNFAIP6 regulated by the nuclear factor kappa B(NK-KB) pathway played a crucial role in fighting against tuberculosis. Based on the active pathway algorithm, each immune cell showed metabolic heterogeneity. Besides, after tuberculosis infection, structural cells showed a chemotactic immunity effect based on the co-expression immunoregulatory module.

Plasma exosome-derived microRNAs expression profiling and bioinformatics analysis under cross-talk between increased low-density lipoprotein cholesterol level and ATP-sensitive potassium channels variant rs1799858

Background

Exosome-derived microRNAs (exo-miRs) as messengers play important roles, in the cross-talk between genetic [ATP-sensitive potassium channels (KATP) genetic variant rs1799858] and environmental [elevated serum low-density lipoprotein cholesterol (LDL-C) level] factors, but the plasma exo-miRs expression profile and its role in biological processes from genotype to phenotype remain unclear.

Methods

A total of 14 subjects with increased LDL-C serum levels (≥ 1.8 mmol/L) were enrolled in the study. The KATP rs1799858 was genotyped by the Sequenom MassARRAY system. The plasma exo-miRs expression profile was identified by next-generation sequencing.

Results

64 exo-miRs were significantly differentially expressed (DE), among which 44 exo-miRs were up-regulated and 20 exo-miRs were down-regulated in those subjects carrying T-allele (TT + CT) of rs1799858 compared to those carrying CC genotype. The top 20 up-regulated DE-exo-miRs were miR-378 family, miR-320 family, miR-208 family, miR-483-5p, miR-22-3p, miR-490-3p, miR-6515-5p, miR-31-5p, miR-210-3p, miR-17-3p, miR-6807-5p, miR-497-5p, miR-33a-5p, miR-3611 and miR-126-5p. The top 20 down-regulated DE-exo-miRs were let-7 family, miR-221/222 family, miR-619-5p, miR-6780a-5p, miR-641, miR-200a-5p, miR-581, miR-605-3p, miR-548ar-3p, miR-135a-3p, miR-451b, miR-509-3-5p, miR-4664-3p and miR-224-5p. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were subsequently implemented to identify the top 10 DE-exo-miRs related specific target genes and signaling pathways. Only 5 DE-exo-miRs were validated by qRT-PCR as follows: miR-31-5p, miR-378d, miR-619-5p, miR-320a-3p and let-7a-5p (all P < 0.05).

Conclusion

These results firstly indicated the plasma exo-miRs expression profile bridging the link between genotype (KATP rs1799858) and phenotype (higher LDL-C serum level), these 5 DE-exo-miRs may be potential target intermediates for molecular intervention points.

Development of cancer prognostic signature based on pan-cancer proteomics

Utilizing genomic data to predict cancer prognosis was insufficient. Proteomics can improve our understanding of the etiology and progression of cancer and improve the assessment of cancer prognosis. And the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has generated extensive proteomics data of the vast majority of tumors. Based on CPTAC, we can perform a proteomic pan-carcinoma analysis. We collected the proteomics data and clinical features of cancer patients from CPTAC. Then, we screened 69 differentially expressed proteins (DEPs) with R software in five cancers: hepatocellular carcinoma (HCC), children’s brain tumor tissue consortium (CBTTC), clear cell renal cell carcinoma (CCRC), lung adenocarcinoma (LUAD) and uterine corpus endometrial carcinoma (UCEC). GO and KEGG analysis were performed to clarify the function of these proteins. We also identified their interactions. The DEPs-based prognostic model for predicting over survival was identified by least absolute shrinkage and selection operator (LASSO)-Cox regression model in training cohort. Then, we used the time-dependent receiver operating characteristics analysis to evaluate the ability of the prognostic model to predict overall survival and validated it in validation cohort. The results showed that the DEPs-based prognostic model could accurately and effectively predict the survival rate of most cancers.

The Changing Landscape of Therapeutic Cancer Vaccines-Novel Platforms and Neoantigen Identification

Therapeutic cancer vaccines, an exciting development in cancer immunotherapy, share the goal of creating and amplifying tumor-specific T-cell responses, but significant obstacles still remain to their success. Here, we briefly outline the principles underlying cancer vaccine therapy with a focus on novel vaccine platforms and antigens, underscoring the renewed optimism. Numerous strategies have been investigated to overcome immunosuppressive mechanisms of the tumor microenvironment (TME) and counteract tumor escape, including improving antigen selection, refining delivery platforms, and use of combination therapies. Several new cancer vaccine platforms and antigen targets are under development. In an effort to amplify tumor-specific T-cell responses, a heterologous prime-boost antigen delivery strategy is increasingly used for virus-based vaccines. Viruses have also been engineered to express targeted antigens and immunomodulatory molecules simultaneously, to favorably modify the TME. Nanoparticle systems have shown promise as delivery vectors for cancer vaccines in preclinical research. T-win is another platform targeting both tumor cells and the TME, using peptide-based vaccines that engage and activate T cells to target immunoregulatory molecules expressed on immunosuppressive and malignant cells. With the availability of next-generation sequencing, algorithms for neoantigen selection are emerging, and several bioinformatic platforms are available to select therapeutically relevant neoantigen targets for developing personalized therapies. However, more research is needed before the use of neoepitope prediction and personalized immunotherapy becomes commonplace. Taken together, the field of therapeutic cancer vaccines is fast evolving, with the promise of potential synergy with existing immunotherapies for long-term cancer treatment.

Immune checkpoint molecules in natural killer cells as potential targets for cancer immunotherapy

Recent studies have demonstrated the potential of natural killer (NK) cells in immunotherapy to treat multiple types of cancer. NK cells are innate lymphoid cells that play essential roles in tumor surveillance and control that efficiently kill the tumor and do not require the major histocompatibility complex. The discovery of the NK's potential as a promising therapeutic target for cancer is a relief to oncologists as they face the challenge of increased chemo-resistant cancers. NK cells show great potential against solid and hematologic tumors and have progressively shown promise as a therapeutic target for cancer immunotherapy. The effector role of these cells is reliant on the balance of inhibitory and activating signals. Understanding the role of various immune checkpoint molecules in the exhaustion and impairment of NK cells when their inhibitory receptors are excessively expressed is particularly important in cancer immunotherapy studies and clinical implementation. Emerging immune checkpoint receptors and molecules have been found to mediate NK cell dysfunction in the tumor microenvironment; this has brought up the need to explore further additional NK cell-related immune checkpoints that may be exploited to enhance the immune response to refractory cancers. Accordingly, this review will focus on the recent findings concerning the roles of immune checkpoint molecules and receptors in the regulation of NK cell function, as well as their potential application in tumor immunotherapy.

A Multi-Gene Model Effectively Predicts the Overall Prognosis of Stomach Adenocarcinomas With Large Genetic Heterogeneity Using Somatic Mutation Features

Background

Stomach adenocarcinoma (STAD) is one of the most common malignancies worldwide with poor prognosis. It remains unclear whether the prognosis is associated with somatic gene mutations.

Methods

In this research, we collected two independent STAD cohorts with both genetic profiling and clinical follow-up data, systematically investigated the association between the prognosis and somatic mutations, and analyzed the influence of heterogeneity on the prognosis-genetics association.

Results

Typical association was identified between somatic mutations and overall prognosis for individual cohorts. In The Cancer Genome Atlas (TCGA) cohort, a list of 24 genes was also identified that tended to mutate within cases of the poorest prognosis. The association showed apparent heterogeneity between different cohorts, although common signatures could be identified. A machine-learning model was trained with 20 common genes that showed a similar mutation rate difference between prognostic groups in the two cohorts, and it classified the cases in each cohort into two groups with significantly different prognosis. The model outperformed both single-gene models and TNM-based staging system significantly.

Conclusion

The study made a systematic analysis on the association between STAD prognosis and somatic mutations, identified signature genes that showed mutation preference in different prognostic groups, and developed an effective multi-gene model that can effectively predict the overall prognosis of STAD in different cohorts.

Prognostic value of FoxP3 and CTLA-4 expression in patients with oral squamous cell carcinoma

Background

Tumor-infiltrating lymphocytes include tumor-reactive lymphocytes and regulatory T-cells. However, the prognostic value of tumor-infiltrating lymphocytes in oral squamous cell carcinoma (OSCC) remains unclear.

Methods

We used immunohistochemistry to evaluate the presence of tumor-infiltrating FoxP3⁺ T-cells and CTLA-4⁺ cells in four distinct histological compartments (tumor parenchyma and stroma at the tumor center, and parenchyma and stroma at the invasive front) and assessed the association between the prevalence of these cells and the histopathological status of 137 patients with OSCC.

Results

Five-year overall survival, disease-specific survival, and recurrence-free survival were favorable in patients with high numbers of FoxP3⁺ T-cells in the parenchyma of the invasive front. Recurrence-free survival and metastasis-free survival were decreased in patients with high numbers of CTLA-4⁺ cells in the parenchyma of the invasive front.

Conclusions

The presence of FoxP3⁺ T-cells in the parenchyma of the invasive front may be a useful prognostic factor. Our results indicate that FoxP3⁺ T-cells may exert site-specific anti-tumor effects but may not play an immunosuppressive role in OSCC. In addition, our results suggest that CTLA-4⁺ cells suppress the function of FoxP3⁺ T-cells and promote anti‐tumor immunity in OSCC.

Microbes and complex diseases: from experimental results to computational models

Studies have shown that the number of microbes in humans is almost 10 times that of cells. These microbes have been proven to play an important role in a variety of physiological processes, such as enhancing immunity, improving the digestion of gastrointestinal tract and strengthening metabolic function. In addition, in recent years, more and more research results have indicated that there are close relationships between the emergence of the human noncommunicable diseases and microbes, which provides a novel insight for us to further understand the pathogenesis of the diseases. An in-depth study about the relationships between diseases and microbes will not only contribute to exploring new strategies for the diagnosis and treatment of diseases but also significantly heighten the efficiency of new drugs development. However, applying the methods of biological experimentation to reveal the microbe-disease associations is costly and inefficient. In recent years, more and more researchers have constructed multiple computational models to predict microbes that are potentially associated with diseases. Here, we start with a brief introduction of microbes and databases as well as web servers related to them. Then, we mainly introduce four kinds of computational models, including score function-based models, network algorithm-based models, machine learning-based models and experimental analysis-based models. Finally, we summarize the advantages as well as disadvantages of them and set the direction for the future work of revealing microbe-disease associations based on computational models. We firmly believe that computational models are expected to be important tools in large-scale predictions of disease-related microbes.

Transcriptomic landscape profiling of metformin-treated healthy mice: Implication for potential hypertension risk when prophylactically used

Recently, the first-line anti-diabetic drug metformin shows versatile protective effects against several diseases and is potentially prescribed to healthy individual for prophylactic use against ageing or other pathophysiological processes. However, for healthy individuals, it remains unclear what effects metformin treatment will induce on their bodies. A systematic profiling of the molecular landscape of metformin treatment is expected to provide crucial implications for this issue. Here, we delineated the first transcriptomic landscape induced by metformin in 10 tissues (aorta, brown adipose, brain, eye, heart, liver, kidney, skeletal muscle, stomach and testis) of healthy mice by using RNA-sequencing technique. A comprehensive computational analysis was performed. The overrepresentation of cardiovascular disease-related gene sets, positive correlation with hypertension-related transcriptomic signatures and the associations of drugs with hypertensive side effect together indicate that although metformin does exert various beneficial effects, it would also increase the risk of hypertension in healthy mice. This prediction was experimentally validated by an independent animal experiments. Together, this study provided important resource necessary for investigating metformin's beneficial/deleterious effects on various healthy tissues, when it is potentially prescribed to healthy individual for prophylactic use.

Methylation-Based Signatures for Gastroesophageal Tumor Classification

Contention exists within the field of oncology with regards to gastroesophageal junction (GEJ) tumors, as in the past, they have been classified as gastric cancer, esophageal cancer, or a combination of both. Misclassifications of GEJ tumors ultimately influence treatment options, which may be rendered ineffective if treating for the wrong cancer attributes. It has been suggested that misclassification rates were as high as 45%, which is greater than reported for junctional cancer occurrences. Here, we aimed to use the methylation profiles of GEJ tumors to improve classifications of GEJ tumors. Four cohorts of DNA methylation profiles, containing ~27,000 (27k) methylation sites per sample, were collected from the Gene Expression Omnibus and The Cancer Genome Atlas. Tumor samples were assigned into discovery (nEC = 185, nGC = 395; EC, esophageal cancer; GC gastric cancer) and validation (nEC = 179, nGC = 369) sets. The optimized Multi-Survival Screening (MSS) algorithm was used to identify methylation biomarkers capable of distinguishing GEJ tumors. Three methylation signatures were identified: They were associated with protein binding, gene expression, and cellular component organization cellular processes, and achieved precision and recall rates of 94.7% and 99.2%, 97.6% and 96.8%, and 96.8% and 97.6%, respectively, in the validation dataset. Interestingly, the methylation sites of the signatures were very close (i.e., 170-270 base pairs) to their downstream transcription start sites (TSSs), suggesting that the methylations near TSSs play much more important roles in tumorigenesis. Here we presented the first set of methylation signatures with a higher predictive power for characterizing gastroesophageal tumors. Thus, they could improve the diagnosis and treatment of gastroesophageal tumors.

Tumor-infiltrating immune cells in hepatocellular carcinoma: Tregs is correlated with poor overall survival

Systematic interrogation of tumor-infiltrating immune cells (TIICs) is key to the prediction of clinical outcome and development of immunotherapies. However, little is known about the TIICs of hepatocellular carcinoma (HCC) and its impact on the prognosis of patients and potential for immunotherapy. We applied CIBERSORT of 1090 tumors to infer the infiltration of 22 subsets of TIICs using gene expression data. Unsupervised clustering analysis by 22 TIICs revealed 4 clusters of tumors, mainly defined by macrophages and T cells, with distinct prognosis and associations with immune checkpoint molecules, including PD-1, CD274, CTLA-4, LAG-3 and IFNG. We found tumors with decreased number of M1 macrophages or increased regulatory T cells were associated with poor prognosis. Based on the multivariate Cox analysis, a nomogram was also established for clinical application. In conclusion, composition of the TIICs in HCC was quite different, which is an important determinant of prognosis with great potential to identify candidates for immunotherapy.

A Computational Study of Potential miRNA-Disease Association Inference Based on Ensemble Learning and Kernel Ridge Regression

As increasing experimental studies have shown that microRNAs (miRNAs) are closely related to multiple biological processes and the prevention, diagnosis and treatment of human diseases, a growing number of researchers are focusing on the identification of associations between miRNAs and diseases. Identifying such associations purely via experiments is costly and demanding, which prompts researchers to develop computational methods to complement the experiments. In this paper, a novel prediction model named Ensemble of Kernel Ridge Regression based MiRNA-Disease Association prediction (EKRRMDA) was developed. EKRRMDA obtained features of miRNAs and diseases by integrating the disease semantic similarity, the miRNA functional similarity and the Gaussian interaction profile kernel similarity for diseases and miRNAs. Under the computational framework that utilized ensemble learning and feature dimensionality reduction, multiple base classifiers that combined two Kernel Ridge Regression classifiers from the miRNA side and disease side, respectively, were obtained based on random selection of features. Then average strategy for these base classifiers was adopted to obtain final association scores of miRNA-disease pairs. In the global and local leave-one-out cross validation, EKRRMDA attained the AUCs of 0.9314 and 0.8618, respectively. Moreover, the model’s average AUC with standard deviation in 5-fold cross validation was 0.9275 ± 0.0008. In addition, we implemented three different types of case studies on predicting miRNAs associated with five important diseases. As a result, there were 90% (Esophageal Neoplasms), 86% (Kidney Neoplasms), 86% (Lymphoma), 98% (Lung Neoplasms), and 96% (Breast Neoplasms) of the top 50 predicted miRNAs verified to have associations with these diseases.

NCMCMDA: miRNA-disease association prediction through neighborhood constraint matrix completion

Emerging evidence shows that microRNAs (miRNAs) play a critical role in diverse fundamental and important biological processes associated with human diseases. Inferring potential disease related miRNAs and employing them as the biomarkers or drug targets could contribute to the prevention, diagnosis and treatment of complex human diseases. In view of that traditional biological experiments cost much time and resources, computational models would serve as complementary means to uncover potential miRNA-disease associations. In this study, we proposed a new computational model named Neighborhood Constraint Matrix Completion for MiRNA-Disease Association prediction (NCMCMDA) to predict potential miRNA-disease associations. The main task of NCMCMDA was to recover the missing miRNA-disease associations based on the known miRNA-disease associations and integrated disease (miRNA) similarity. In this model, we innovatively integrated neighborhood constraint with matrix completion, which provided a novel idea of utilizing similarity information to assist the prediction. After the recovery task was transformed into an optimization problem, we solved it with a fast iterative shrinkage-thresholding algorithm. As a result, the AUCs of NCMCMDA in global and local leave-one-out cross validation were 0.9086 and 0.8453, respectively. In 5-fold cross validation, NCMCMDA achieved an average AUC of 0.8942 and standard deviation of 0.0015, which demonstrated NCMCMDA's superior performance than many previous computational methods. Furthermore, NCMCMDA was applied to three different types of case studies to further evaluate its prediction reliability and accuracy. As a result, 84% (colon neoplasms), 98% (esophageal neoplasms) and 98% (breast neoplasms) of the top 50 predicted miRNAs were verified by recent literature.

Natural Killer Cell Therapy: A New Treatment Paradigm for Solid Tumors

In treatments of solid tumors, adoptive transfer of ex vivo expanded natural killer (NK) cells has dawned as a new paradigm. Compared with cytotoxic T lymphocytes, NK cells take a unique position targeting tumor cells that evade the host immune surveillance by down-regulating self-antigen presentation. Recent findings highlighted that NK cells can even target cancer stem cells. The efficacy of allogeneic NK cells has been widely investigated in the treatment of hematologic malignancies. In solid tumors, both autologous and allogeneic NK cells have demonstrated potential efficacy. In allogeneic NK cell therapy, the mismatch between the killer cell immunoglobulin-like receptor (KIR) and human leukocyte antigen (HLA) can be harnessed to increase the antitumor activity. However, the allogeneic NK cells cause more adverse events and can be rejected by the host immune system after repeated injections. In this regard, the autologous NK cell therapy is safer. This article reviews the published results of clinical trials and discusses strategies to enhance the efficacy of the NK cell therapy. The difference in immunophenotype of the ex vivo expanded NK cells resulted from different culture methods may affect the final efficacy. Furthermore, currently available standard anticancer therapy, molecularly targeted agents, and checkpoint inhibitors may directly or indirectly enhance the efficacy of NK cell therapy. A recent study discovered that NK cell specific genetic defects are closely associated with the tumor immune microenvironment that determines clinical outcomes. This finding warrants future investigations to find the implication of NK cell specific genetic defects in cancer development and treatment, and NK cell deficiency syndrome should be revisited to enhance our understanding. Overall, it is clear that NK cell therapy is safe and promises a new paradigm for the treatment of solid tumors.