The Mutation and Expression Level of LRP1B are Associated with Immune Infiltration and Prognosis in Hepatocellular Carcinoma

Pan-cancer analysis of the prognostic and immunological role of FKBP4

Objectives

Our previous studies revealed the significant roles of FK506-binding protein 4 (FKBP4) in tumorigenesis, however, there has been no pan-cancer analysis of FKBP4. Using bioinformatics, the current study reported the expression and prognostic role of FKBP4, and the correlation between FKBP4 and clinicopathological parameters, methylation, molecular network, immunological traits and drug sensitivity.

Methods

RNA sequencing data, somatic mutation, and related clinical information were obtained from TCGA using UCSC Xena. The association between FKBP4 expression and clinical features was assessed using TISIDB. The relationships between FKBP4 expression and tumour stage, OS, DSS, DFS, and PFS were analysed using univariate cox regression analysis. The radar plots for TMB and MSI were obtained using "Fmsb" R package. UALCAN was used to explore the effect of FKBP4 methylation on tumour and normal samples. CBioportal was used to analyse copy number mutations in FKBP4 Gene expression and drug sensitivity data were downloaded from the CellMiner database. GO analysis was performed for the high and the low expression of FKBP4 compared with the median level of FKBP4 using clusterProfiler4.0.

Results

FKBP4 expression is significantly upregulated in various types of cancers. Cox regression analysis showed that high FKBP4 levels were correlated with poor OS, DSS, DFS, and PFS in most patients with cancer. Methylation of FKBP4 DNA was upregulated in most cancers, and FKBP4 expression is positively associated with transmethylase expression. FKBP4 and its copy were significantly associated with the expression of immune-infiltrating cells, immune checkpoint genes, immune modulators, TMB, MMR, and MSI. FKBP4 expression levels significantly correlated with 16 different drug sensitivities (all p < 0.05).

Conclusions

Our pan-cancer bioinformatic analysis revealed a potential mechanism underlying the effects of FKBP4 on the prognosis and progression of various cancers.

Multi-omics Analysis Reveals Immune Features Associated with Immunotherapy Benefit in Patients with Squamous Cell Lung Cancer from Phase III Lung-MAP S1400I Trial

PURPOSE

Identifying molecular and immune features to guide immune checkpoint inhibitor (ICI)-based regimens remains an unmet clinical need.

EXPERIMENTAL DESIGN

Tissue and longitudinal blood specimens from phase III trial S1400I in patients with metastatic squamous non-small cell carcinoma (SqNSCLC) treated with nivolumab monotherapy (nivo) or nivolumab plus ipilimumab (nivo+ipi) were subjected to multi-omics analyses including multiplex immunofluorescence (mIF), nCounter PanCancer Immune Profiling Panel, whole-exome sequencing, and Olink.

RESULTS

Higher immune scores from immune gene expression profiling or immune cell infiltration by mIF were associated with response to ICIs and improved survival, except regulatory T cells, which were associated with worse overall survival (OS) for patients receiving nivo+ipi. Immune cell density and closer proximity of CD8+GZB+ T cells to malignant cells were associated with superior progression-free survival and OS. The cold immune landscape of NSCLC was associated with a higher level of chromosomal copy-number variation (CNV) burden. Patients with LRP1B-mutant tumors had a shorter survival than patients with LRP1B-wild-type tumors. Olink assays revealed soluble proteins such as LAMP3 increased in responders while IL6 and CXCL13 increased in nonresponders. Upregulation of serum CXCL13, MMP12, CSF-1, and IL8 were associated with worse survival before radiologic progression.

CONCLUSIONS

The frequency, distribution, and clustering of immune cells relative to malignant ones can impact ICI efficacy in patients with SqNSCLC. High CNV burden may contribute to the cold immune microenvironment. Soluble inflammation/immune-related proteins in the blood have the potential to monitor therapeutic benefit from ICI treatment in patients with SqNSCLC.

A genome-wide and candidate gene association study of preterm birth in Korean pregnant women

Preterm birth (PTB) refers to delivery before 37 weeks of gestation. Premature neonates exhibit higher neonatal morbidity and mortality rates than term neonates; therefore, it is crucial to predict and prevent PTB. Advancements enable the prediction and prevention of PTB using genetic approaches, especially by investigating its correlation with single nucleotide polymorphisms (SNPs). We aimed to identify impactive and relevant SNPs for the prediction of PTB via whole-genome sequencing analyses of the blood of 31 pregnant women with PTB (n = 13) and term birth (n = 18) who visited the Ewha Womans University Mokdong Hospital from November 1, 2018 to February 29, 2020. A genome-wide association study was performed using PLINK 1.9 software and 256 SNPs were selected and traced through protein-protein interactions. Moreover, a validation study by genotyping was performed on 60 other participants (preterm birth, n = 30; term birth, n = 30) for 25 SNPs related to ion channel binding and receptor complex pathways. Odds ratios were calculated using additive, dominant, and recessive genetic models. The risk of PTB in women with the AG allele of rs2485579 (gene name: RYR2) was significantly 4.82-fold increase, and the risk of PTB in women with the AG allele of rs7903957 (gene name: TBX5) was significantly 0.25-fold reduce. Our results suggest that rs2485579 (in RYR2) can be a genetic marker of PTB, which is considered through the association with abnormal cytoplasmic Ca2+ concentration and dysfunctional uterine contraction due to differences of RYR2 in the sarcoplasmic reticulum.

Prognosis and personalized medicine prediction by integrated whole exome and transcriptome sequencing of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a clinically and genetically heterogeneous disease. To better describe the clinical value of the main driver gene mutations of HCC, we analyzed the whole exome sequencing data of 125 patients, and combined with the mutation data in the public database, 14 main mutant genes were identified. And we explored the correlation between the main mutation genes and clinical features. Consistent with the results of previous data, we found that TP53 and LRP1B mutations were related to the prognosis of our patients by WES data analysis. And we further explored the associated characteristics of TP53 and LRP1B mutations. However, it is of great clinical significance to tailor a unique prediction method and treatment plan for HCC patients according to the mutation of TP53. For TP53 wild-type HCC patients, we proposed a prognostic risk model based on 11 genes for better predictive value. According to the median risk score of the model, HCC patients with wild-type TP53 were divided into high-risk and low-risk groups. We found significant transcriptome changes in the enrichment of metabolic-related pathways and immunological characteristics between the two groups, suggesting the predictability of HCC immunotherapy by using this model. Through the CMap database, we found that AM580 had potential therapeutic significance for high-risk TP53 wild-type HCC patients.

Establishment and genetically characterization of patient-derived xenograft models of cervical cancer

Purpose

Patient-derived xenograft (PDX) models were established to reproduce the clinical situation of original cancers and have increasingly been applied to preclinical cancer research. Our study was designed to establish and genetically characterize cervical cancer PDX models.

Methods

A total of 91 fresh fragments obtained from 22 surgically resected cervical cancer tissues were subcutaneously engrafted into female NOD-SCID mice. Hematoxylin and eosin (H&E) staining was performed to assess whether the established PDX models conserved the histological features of original patient cervical cancer tissues. Moreover, a Venn diagram was applied to display the overlap of all mutations detected in whole-genome sequencing (WGS) data from patient original cervical cancer (F0) and F2-, F3-PDX models. The whole exome sequencing (WES) and the “maftools” package were applied to determine the somatic mutations among primary cervical cancers and the established PDX models.

Results

Our study successfully developed a panel of cervical cancer PDX models and the latency time of cervical cancer PDX model establishment was variable with a progressive decrease as the passage number increased, with a mean time to initial growth of 94.71 days in F1 engraftment to 40.65 days in F3 engraftment. Moreover, the cervical cancer PDX models preserved the histological features of their original cervical cancer. WGS revealed that the genome of original cervical cancer was preserved with high fidelity in cervical cancer PDX models throughout the xenografting and passaging process. Furthermore, WES demonstrated that the cervical cancer PDX models maintained the majority somatic mutations of original cervical cancer, of which the KMT2D, LRP1B, NAV3, TP53, FAT1, MKI67 and PKHD1L1 genes were identified as the most frequently mutated genes.

Conclusions

The cervical cancer PDX models preserved the histologic and genetic characteristics of their original cervical cancer, which helped to gain a deeper insight into the genetic alterations and lay a foundation for further investigation of the molecular targeted therapy of cervical cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01342-5.

LRP1B is a Potential Biomarker for Tumor Immunogenicity and Prognosis of HCC Patients Receiving ICI Treatment

Background

New predictors of the efficacy of hepatocellular carcinoma (HCC) immunotherapy are needed. The ability of a single gene mutation to predict the therapeutic effect of immune checkpoint inhibitors (ICI) in HCC remains unknown.

Methods

The most frequently mutated genes in HCC were analyzed using the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Mutant genes that correlated with the tumor mutational burden (TMB) and prognosis were obtained. The mutation pattern and immunological function of one of the most frequently mutated genes, LRP1B, were determined. A pan-tumor analysis of LRP1B expression, association with cancer prognosis, and immunological role was also explored. A retrospective clinical study was conducted using 102 HCC patients who received ICI treatment to further verify whether gene mutations can predict the effectiveness of immunotherapy and prognosis of HCC.

Results

LRP1B is among the most frequently mutated genes in HCC cohorts in TCGA and ICGC datasets. TCGA data showed that the LRP1B mutation activated immune signaling pathways and promoted mast cell activation. Patients with LRP1B mutations had significantly higher TMB than those with wild-type LRP1B. LRP1B expression correlated with the cancer-immunity cycle and immune cell infiltration. High LRP1B expression was also associated with poor survival among HCC patients. Results from the clinical study showed that HCC patients in the LRP1B mutation group had a poor response to ICI and worse prognosis than the wild-type group. The LRP1B mutation group had significantly higher TMB and mast cell infiltration in tumor tissues.

Conclusion

This study is the first to report that a single gene LRP1B mutation is associated with a poor clinical response to ICI treatment and negative outcomes in HCC patients. HighLRP1B expression correlated with tumor immunity and HCC prognosis.