Cell adhesion-related gene somatic mutations are enriched in aggressive papillary thyroid microcarcinomas

An individualized protein-based prognostic model to stratify pediatric patients with papillary thyroid carcinoma

Pediatric papillary thyroid carcinomas (PPTCs) exhibit high inter-tumor heterogeneity and currently lack widely adopted recurrence risk stratification criteria. Hence, we propose a machine learning-based objective method to individually predict their recurrence risk. We retrospectively collect and evaluate the clinical factors and proteomes of 83 pediatric benign (PB), 85 pediatric malignant (PM) and 66 adult malignant (AM) nodules, and quantify 10,426 proteins by mass spectrometry. We find 243 and 121 significantly dysregulated proteins from PM vs. PB and PM vs. AM, respectively. Function and pathway analyses show the enhanced activation of the inflammatory and immune system in PM patients compared with the others. Nineteen proteins are selected to predict recurrence using a machine learning model with an accuracy of 88.24%. Our study generates a protein-based personalized prognostic prediction model that can stratify PPTC patients into high- or low-recurrence risk groups, providing a reference for clinical decision-making and individualized treatment.

Clinical and molecular features of progressive papillary thyroid microcarcinoma

In recent decades, the prevalence of thyroid cancer has risen substantially, with papillary thyroid microcarcinoma (PTMC) constituting over 50% of cases. Although most PTMCs exhibit indolent growth and a favorable prognosis, some present an increased risk of recurrence and an unfavorable prognosis due to high-risk characteristics such as lymph node metastasis, extrathyroidal extension, and distant metastasis. The early identification of clinically progressing PTMC remains elusive. In this review, the authors summarize findings from PTMC progression-related literature, highlighting that factors such as larger tumor size, cervical lymph node metastasis, extrathyroidal extension, younger age, higher preoperative serum thyroid-stimulating hormone levels, family history, and obesity positively correlate with PTMC progression. The role of multifocality in promoting PTMC progression; however, remains contentious. Furthermore, recent studies have shed light on the impact of mutations, such as BRAF and TERT mutations, on PTMC progression. Researchers have identified several mRNAs, noncoding RNAs, and proteins associated with various features of PTMC progression. Some studies propose that peripheral and tumor tissue-infiltrating immune cells could serve as biomarkers for the clinical progression of PTMC. Collectively, these clinical and molecular features offer a rationale for the early detection and the development of precision theranostic strategies of clinically progressive PTMC.

Revealing a Novel Methylated Integrin Alpha-8 Related to Extracellular Matrix and Anoikis Resistance Using Proteomic Analysis in the Immune Microenvironment of Lung Adenocarcinoma

Genomic epigenetics of extracellular matrix (ECM) play an important role in lung adenocarcinoma (LUAD). Our study identified a signature of potential prognostic genes associated with ECM and constructed immune risk-related prognosis model in LUAD. We downloaded mRNAs transcriptome data, miRNAs expression data, and clinical patient information for LUAD based on The Cancer Genome Atlas. "Limma, clusterProfiler, ggplot2" R packages and GSEA were used to analyze meaningful genes and explore potential biological function. A competing endogenous RNA network was constructed to reveal the mechanism of ECM-related genes. Combined with clinical LUAD patients' characteristics, univariate and multivariate Cox regression analyses were used to build prognostic immune risk model. Next, we calculated AUC value of ROC curve, and explored survival probability of different risk groups. A total of 2966 mRNAs were differently expressed in LUAD samples and normal samples. Function enrichment analyses proved mRNAs were associated with many tumor pathways, such as cell adhesion, vascular smooth muscle contraction, and cell cycle. There were 18 mRNAs related to ECM receptor signaling pathway, and 7 mRNAs expressions were correlated with EGFR expression, but only 5mRNAs were associated with the long-term prognosis. Based on Integrin alpha-8 (ITGA8) molecule, we identified potential 3 miRNAs from several databases. The promoter of ITGA8 was higher-methylated and lower-expressed in LUAD. And lower-expressed group has poor prognosis for patients. 66 immunomodulators related to ITGA8 were performed to construct immune correlation prediction model (p < 0.05). Comprehensive analyses of ITGA8 revealed it combined focal adhesion kinase to activate PI3K/AKT signaling pathway to influence the occurrence and development of LUAD. A novel immune prognostic model about ITGA8 was constructed and verified in LUAD patients. Combined with non-coding genes and genomic epigenetics, identification of potential biomarkers provided new light on therapeutic strategy for clinical patients.

Insight of novel biomarkers for papillary thyroid carcinoma through multiomics

Introduction

The overdiagnosing of papillary thyroid carcinoma (PTC) in China necessitates the development of an evidence-based diagnosis and prognosis strategy in line with precision medicine. A landscape of PTC in Chinese cohorts is needed to provide comprehensiveness.

Methods

6 paired PTC samples were employed for whole-exome sequencing, RNA sequencing, and data-dependent acquisition mass spectrum analysis. Weighted gene co-expression network analysis and protein-protein interactions networks were used to screen for hub genes. Moreover, we verified the hub genes' diagnostic and prognostic potential using online databases. Logistic regression was employed to construct a diagnostic model, and we evaluated its efficacy and specificity based on TCGA-THCA and GEO datasets.

Results

The basic multiomics landscape of PTC among local patients were drawn. The similarities and differences were compared between the Chinese cohort and TCGA-THCA cohorts, including the identification of PNPLA5 as a driver gene in addition to BRAF mutation. Besides, we found 572 differentially expressed genes and 79 differentially expressed proteins. Through integrative analysis, we identified 17 hub genes for prognosis and diagnosis of PTC. Four of these genes, ABR, AHNAK2, GPX1, and TPO, were used to construct a diagnostic model with high accuracy, explicitly targeting PTC (AUC=0.969/0.959 in training/test sets).

Discussion

Multiomics analysis of the Chinese cohort demonstrated significant distinctions compared to TCGA-THCA cohorts, highlighting the unique genetic characteristics of Chinese individuals with PTC. The novel biomarkers, holding potential for diagnosis and prognosis of PTC, were identified. Furthermore, these biomarkers provide a valuable tool for precise medicine, especially for immunotherapeutic or nanomedicine based cancer therapy.

The Structural Dynamics, Complexity of Interactions, and Functions in Cancer of Multi-SAM Containing Proteins

SAM domains are crucial mediators of diverse interactions, including those important for tumorigenesis or metastasis of cancers, and thus SAM domains can be attractive targets for developing cancer therapies. This review aims to explore the literature, especially on the recent findings of the structural dynamics, regulation, and functions of SAM domains in proteins containing more than one SAM (multi-SAM containing proteins, MSCPs). The topics here include how intrinsic disorder of some SAMs and an additional SAM domain in MSCPs increase the complexity of their interactions and oligomerization arrangements. Many similarities exist among these MSCPs, including their effects on cancer cell adhesion, migration, and metastasis. In addition, they are all involved in some types of receptor-mediated signaling and neurology-related functions or diseases, although the specific receptors and functions vary. This review also provides a simple outline of methods for studying protein domains, which may help non-structural biologists to reach out and build new collaborations to study their favorite protein domains/regions. Overall, this review aims to provide representative examples of various scenarios that may provide clues to better understand the roles of SAM domains and MSCPs in cancer in general.

Mutational Impacts on the N and C Terminal Domains of the MUC5B Protein: A Transcriptomics and Structural Biology Study

Cholangiocarcinoma (CCA) involves various epithelial tumors historically linked with poor prognosis because of its aggressive sickness course, delayed diagnosis, and limited efficacy of typical chemotherapy in its advanced stages. In-depth molecular profiling has exposed a varied scenery of genomic alterations as CCA's oncogenic drivers. Previous studies have mainly focused on commonly occurring TP53 and KRAS alterations, but there is limited research conducted to explore other vital genes involved in CCA. We retrieved data from The Cancer Genome Atlas (TCGA) to hunt for additional CCA targets and plotted a mutational landscape, identifying key genes and their frequently expressed variants. Next, we performed a survival analysis for all of the top genes to shortlist the ones with better significance. Among those genes, we observed that MUC5B has the most significant p-value of 0.0061. Finally, we chose two missense mutations at different positions in the vicinity of MUC5B N and C terminal domains. These mutations were further subjected to molecular dynamics (MD) simulation, which revealed noticeable impacts on the protein structure. Our study not only reveals one of the highly mutated genes with enhanced significance in CCA but also gives insights into the influence of its variants. We believe these findings are a good asset for understanding CCA from genomics and structural biology perspectives.

A Potential Nine-lncRNAs Signature Identification and Nomogram Diagnostic Model Establishment for Papillary Thyroid Cancer

The purpose of our current study was to establish a long non-coding RNA(lncRNA) signature and assess its prognostic and diagnostic power in papillary thyroid cancer (PTC). LncRNA expression profiles were obtained from the Cancer Genome Atlas (TCGA). The key module and hub lncRNAs related to PTC were determined by weighted gene co-expression network analysis (WGCNA) and LASSO Cox regression analyses, respectively. Functional enrichment analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis were implemented to analyze the possible biological processes and signaling pathways of hub lncRNAs. Associations between key lncRNA expressions and tumor-infiltrating immune cells were identified using the TIMER website, and proportions of immune cells in high/low risk score groups were compared. Kaplan-Meier Plotter was used to evaluate the prognostic significance of hub genes in PTC. A diagnostic model was conducted with logistic regression analysis, and its diagnostic performance was assessed by calibration/receiver operating characteristic curves and principal component analysis. A nine-lncRNAs signature (SLC12A5-AS1, LINC02028, KIZ-AS1, LINC02019, LINC01877, LINC01444, LINC01176, LINC01290, and LINC00581) was established in PTC, which has significant diagnostic and prognostic power. Functional enrichment analyses elucidated the regulatory mechanism of the nine-lncRNAs signature in the development of PTC. This signature and expressions of nine hub lncRNAs were correlated with the distributions of tumor infiltrating immune cells. A diagnostic nomogram was also established for PTC. By comparing with the published models with less than or equal to nine lncRNAs, our signature showed a preferable performace for prognosis prediction. In conclusion, our present research established an innovative nine-lncRNAs signature and a six-lncRNAs nomogram that might act as a potential indicator for PTC prognosis and diagnosis, which could be conducive to the PTC treatment.

Identification of key genes associated with papillary thyroid microcarcinoma characteristics by integrating transcriptome sequencing and weighted gene co-expression network analysis

OBJECTIVE

Papillary thyroid microcarcinoma (PTMC) is the most prevalent histological type of thyroid carcinoma. Despite the overall favorable prognosis of PTMC, some cases exhibit aggressive phenotypes. The identification of robust biomarkers may improve early PTMC diagnosis. In this study, we integrated high-throughput transcriptome sequencing, bioinformatic analyses and experimental validation to identify key genes associated with the malignant characteristics of PTMC.

METHODS

Total RNA was extracted from 24 PTMC samples and 7 non-malignant thyroid tissue samples, followed by RNA sequencing. The differentially expressed genes (DEGs) were identified and used to construct co-expression networks by weighted gene co-expression network analysis (WGCNA). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed, and protein-protein interaction networks were constructed. Key modules and hub genes showing a strong correlation with the malignant characteristics of PTMC were identified and validated.

RESULTS

The green-yellow and turquoise modules generated by WGCNA were strongly associated with the malignant characteristics of PTMC. Functional enrichment analysis revealed that genes in the green-yellow module participated in cell motility and metabolism, whereas those in the turquoise module participated in several oncogenic biological processes. Nine real hub genes (FHL1, NDRG2, NEXN, SYNM, COL1A1, FN1, LAMC2, POSTN, and TGFBI) were identified and validated at the transcriptional and translational levels. Our preliminary results indicated their diagnostic potentials in PTMC.

CONCLUSIONS

In this study, we identified key co-expression modules and nine malignancy-related genes with potential diagnostic value in PTMC.

Liprins in oncogenic signaling and cancer cell adhesion

Liprins are a multifunctional family of scaffold proteins, identified by their involvement in several important neuronal functions related to signaling and organization of synaptic structures. More recently, the knowledge on the liprin family has expanded from neuronal functions to processes relevant to cancer progression, including cell adhesion, cell motility, cancer cell invasion, and signaling. These proteins consist of regions, which by prediction are intrinsically disordered, and may be involved in the assembly of supramolecular structures relevant for their functions. This review summarizes the current understanding of the functions of liprins in different cellular processes, with special emphasis on liprins in tumor progression. The available data indicate that liprins may be potential biomarkers for cancer progression and may have therapeutic importance.

Assessing mPTC Progression during Active Surveillance: Volume or Diameter Increase?

Active surveillance (AS) is considered an alternative to immediate surgery in micropapillary thyroid carcinoma (mPTC). However, the definition of clinical mPTC progression during AS is controversial. We evaluated changes in tumor size using both tumor diameters and volume in 109 patients with mPTC followed in an AS protocol for a mean period of 31 ± 18 months. At the time of data lock, 19/109 (17.4%) mPTC reached and maintained a volume increase of ≥50%. However, only 3/19 (15.7%) showed progression, according to the diameter increase. The remaining 16 showed a slight diameter growth without reaching the original protocol progression criteria. The mean mPTC growth rate in stable cases was 0.37 mm³/month, while it was significantly greater in the mPTC, which achieved a volume change ≥50% with respect to the other. The two mPTC that developed a significant diameter increase had a growth rate of 41 and 18 mm³/month. Instead, the growth rates of the three mPTC that developed lymph node metastases were 0, 2.5 and 16 mm³/month. The ≥50% volume increase appears to be a too sensitive marker of disease progression, with a downstream higher surgery rate. The assessment of growth rate could distinguish mPTC with high and low growth rates, which would allow us to tailor the algorithm of the evaluations to a more appropriate timing.

Research trends for papillary thyroid carcinoma from 2010 to 2019: A systematic review and bibliometrics analysis

BACKGROUND

Thyroid carcinoma comprises the fastest rising incidence of carcinomas over the past decade. Papillary thyroid carcinoma (PTC) is the most predominant type of thyroid carcinoma. This study aimed to assess the research trends in the field of PTC.

METHODS

Publications from January 2010 to December 2019 were retrieved from the Web of Science Core Collection database using Thompson Reuters. Searching strategies were determined according to Medical Subject Heading terms. Different kinds of bibliometrics software, such as HistCite and VOSviewer, and online bibliometrics analysis platforms were utilized to evaluate and visualize the results.

RESULTS

A total of 8102 publications across 93 countries were identified, with the annual number of publications showing an increasing trend. The United States, China, and South Korea showed their dominant position in PTC publication outputs, H-index, total citations, and international collaborations. Thyroid was the most productive journal. Akira Miyauchi published the most articles, and the most productive institution was Yonsei University. The hotspots keywords proliferation, invasion and metastasis, diagnoses and prognoses, therapeutic resistance, recurrence, and microcarcinomas appeared earlier and were sustained over the last 3 years.

CONCLUSIONS

This bibliometric study provides a comprehensive analysis delineating the scientific productivity, collaboration, and research hotspots within the PTC field, which will be very helpful when focusing on the direction of research over the next few years.

Clinicopathological and Genomic Characterization of a Simmental Calf with Generalized Bovine Juvenile Angiomatosis

Simple Summary

Vascular anomalies represent a heterogeneous group of rare disorders encompassing both vascular malformations and tumors, which can be congenital or arise shortly after birth. They often pose a diagnostic challenge in human and veterinary medicine, and the referring nomenclature is equivocal. Bovine juvenile angiomatosis (BJA), a clinical condition belonging to this group of disorders, encompasses vascular malformations and tumors arising in calves. Usually, such vascular anomalies are not further investigated on a molecular genetic level, mainly because of a lack of resources and diagnostic tools, as well as the low value and short lifespan of the affected animals. Here we report the clinical, pathological, immunohistochemical, and genetic features of a Simmental calf that displayed multiple cutaneous, subcutaneous, and visceral vascular hamartomas compatible with a generalized form of BJA. Whole-genome sequencing identified six coding variants, including four heterozygous variants in the PREX1, UBE3B, PCDHGA2, and ZSWIM6 genes, which occurred only in the BJA-affected calf and were absent in the global control cohort of more than 4500 cattle. Assuming a germline mutation as etiology, one of these variants might be responsible for the vascular malformations identified in this calf.

Abstract

Bovine juvenile angiomatosis (BJA) comprises a group of single or multiple proliferative vascular anomalies in the skin and viscera of affected calves. The purpose of this study was to characterize the clinicopathological phenotype of a 1.5-month-old Simmental calf with multiple cutaneous, subcutaneous, and visceral vascular hamartomas, which were compatible with a generalized form of BJA, and to identify genetic cause for this phenotype by whole-genome sequencing (WGS). The calf was referred to the clinics as a result of its failure to thrive and the presence of multiple cutaneous and subcutaneous nodules, some of which bled abundantly following spontaneous rupture. Gross pathology revealed similar lesions at the inner thoracic wall, diaphragm, mediastinum, pericardium, inner abdominal wall, and mesentery. Histologically, variably sized cavities lined by a single layer of plump cells and supported by a loose stroma with occasional acute hemorrhage were observed. Determined by immunochemistry, the plump cells lining the cavities displayed a strong cytoplasmic signal for PECAM-1, von Willebrand factor, and vimentin. WGS revealed six private protein-changing variants affecting different genes present in the calf and absent in more than 4500 control genomes. Assuming a spontaneous de novo mutation event, one of the identified variants found in the PREX1, UBE3B, PCDHGA2, and ZSWIM6 genes may represent a possible candidate pathogenic variant for this rare form of vascular malformation.

Exploration and validation of the effects of robust co-expressed immune-related genes on immune infiltration patterns and prognosis in laryngeal cancer

OBJECTIVES

Laryngeal cancer is a common malignant tumor that originates from the larynx, yet its molecular mechanisms have not been thoroughly explored. The purpose of this study was to identify and evaluate immune-related genes in laryngeal cancer through gene co-expression networks, which may serve as biomarkers for its immunotherapy.

METHODS

We applied ESTIMATE to evaluate the immune-infiltration landscape of tumor microenvironment. The co-expression networks were constructed by weighted gene co expression network analysis (WGCNA) and compared with the existing human immune related genes (IRGs) to determine the co-expressed IRGs. GSVA combined with CIBERSORT and ssGSEA illustrated the correlation of hub genes and immune infiltration patterns. TIDE algorithm and Subclass mapping evaluated the function of hub genes in predicting immune function and immunotherapeutic sensitivity. The pRRophetic was employed in the sensitivity prediction of chemotherapeutic drugs.

RESULTS

A total of 23 co-expressed IRGs were identified and showed robust expression characteristics. These genes were significantly related to immune infiltration patterns, immune function and sensitivity prediction of immunotherapy and chemotherapeutic drugs for laryngeal cancer patients. Genetic alteration in somatic mutation level and related pathways were also revealed.

CONCLUSION

The 23 co-expressed IRGs may act as immunotherapeutic biomarkers and potential therapeutic targets for laryngeal cancer with certain expression robustness. The molecular mechanisms deserve further investigation, which will guide clinical treatment in the future.

Whole-exome mutational landscape of metastasis in patient-derived hepatocellular carcinoma cells

In order to explore the genomic basis for liver cancer metastasis, whole-exome sequencing (WES) was performed on patient-derived hepatocellular carcinoma (HCC) cell lines with differential metastatic potentials and analyzed their clonal evolution relationships. An evolutionary tree based on genomic single nucleotide polymorphism (SNP) was constructed in MegaX software. The WES data showed that the average percentage of heterogeneous mutations in each HCC cell lines was 16.55% (range, 15.38%–18.17%). C: G > T: A and T: A > C: G somatic transitions were the two most frequent substitutions. In these metastatic HCC cell lines, non-silent gene mutations were found in 21.88% of known driver genes and 10 classical signaling pathways. The protein interaction network was constructed by STRING, and hub genes were found in the shared trunk mutation genes and the heterogeneous branch mutations respectively. In cBioPortal database, some of the selected hub genes were found to be associated with poor overall survival (OS) of HCC patients. Among the mutated HCC driver genes, a novel KEAP1 mutation with a homozygous frameshift truncation at the c-terminal Nrf2 binding region was detected and verified in MHCC97-H and HCC97LM3 cells. In conclusion, WES data demonstrate that HCC cell lines from tumor biopsy specimens of the same patient have obtained different metastatic potentials through repeated selection in rodents in vivo, and they do indeed have a genetic relationship at the genomic level.

Clinical Analysis of Risk Factors for Cervical Lymph Node Metastasis in Papillary Thyroid Microcarcinoma: A Retrospective Study of 3686 Patients

Purpose

To investigate the risk factors for cervical lymph node metastasis (LNM) in papillary thyroid microcarcinoma (PTMC).

Patients and Methods

In total, 3686 patients with PTMC who underwent initial surgery in Shanghai Jiao Tong University affiliated Sixth People’s Hospital from January 2010 to December 2019 were retrospectively analyzed. Univariate and multivariate analyses were conducted to identify risk factors associated with cervical LNM.

Results

Male gender [odds ratio (OR) =1.420, P <0.001], age <55 years (OR =2.128, P <0.001), tumor size >6.5 mm (OR =2.112, P <0.001), lymphovascular invasion (LVI) (OR =2.110, P =0.016), multifocality (OR =1.358, P =0.022), extrathyroidal extension (ETE) (OR =1.598, P <0.001), and lateral LNM (LLNM) (OR =6.383, P <0.001) served as independent risk factors for central LNM (CLNM). Moreover, male gender (OR =1.668, P =0.001), tumor size >6.5 mm (OR =2.223, P <0.001), chronic lymphocytic thyroiditis (OR =1.402, P =0.021), LVI (OR =4.582, P <0.001), ETE (OR =1.393, P=0.023), and CLNM (OR =6.212, P <0.001) served as independent risk factors for LLNM. Furthermore, solitary PTMC with lesions in the upper third of the thyroid gland were more associated with LLNM than lesions in the other regions.

Conclusion

This study suggests that meticulous evaluation of risk factors associated with LNM is required in order to guide the surgical treatment of PTMC patients in clinical practice.

Whole Exome Sequencing of Highly Aggregated Lung Cancer Families Reveals Linked Loci for Increased Cancer Risk on Chromosomes 12q, 7p, and 4q

BACKGROUND

Lung cancer kills more people than any other cancer in the United States. In addition to environmental factors, lung cancer has genetic risk factors as well, though the genetic etiology is still not well understood. We have performed whole exome sequencing on 262 individuals from 28 extended families with a family history of lung cancer.

METHODS

Parametric genetic linkage analysis was performed on these samples using two distinct analyses-the lung cancer only (LCO) analysis, where only patients with lung cancer were coded as affected, and the all aggregated cancers (AAC) analysis, where other cancers seen in the pedigree were coded as affected.

RESULTS

The AAC analysis yielded a genome-wide significant result at rs61943670 in POLR3B at 12q23.3. POLR3B has been implicated somatically in lung cancer, but this germline finding is novel and is a significant expression quantitative trait locus in lung tissue. Interesting genome-wide suggestive haplotypes were also found within individual families, particularly near SSPO at 7p36.1 in one family and a large linked haplotype spanning 4q21.3-28.3 in a different family. The 4q haplotype contains potential causal rare variants in DSPP at 4q22.1 and PTPN13 at 4q21.3.

CONCLUSIONS

Regions on 12q, 7p, and 4q are linked to increased cancer risk in highly aggregated lung cancer families, 12q across families and 7p and 4q within a single family. POLR3B, SSPO, DSPP, and PTPN13 are currently the best candidate genes.

IMPACT

Functional work on these genes is planned for future studies and if confirmed would lead to potential biomarkers for risk in cancer.

Exploration of the immune-related signature and immune infiltration analysis for breast ductal and lobular carcinoma

Background

In this study, we aimed to explore the tumour associated immune signature of breast cancer (BC) and conduct integrative analyses with immune infiltrates in BC.

Methods

We downloaded the transcriptome profiling and clinical data of BC from The Cancer Genome Atlas (TCGA) database. The list of immune-related signatures was from the Innate database. The limma package was utilized to conduct the normalization, and we screened the differential immune signatures in BC. A univariate Cox regression model and the LASSO method were used to find the hub prognostic immune genes. The TAIG risk model was calculated based on the multivariate Cox regression results, and a receiver operating characteristic (ROC) curve was generated to assess the predictive power of TAIG. Moreover, we also conducted a correlation analysis between TAIG and the clinical characteristics. Additionally, we utilized the METABRIC cohort as the validation data set. The TIMER database is a comprehensive resource for performing systematic analyses of immune infiltrates across various malignancies. We evaluated the associations of immune signatures with several immune cells based on TIMER. Furthermore, we used the CIBERSORT algorithm to determine the fractions of immune cells in each sample and compared the differential distributions of immune infiltrates between two TAIG groups using the Wilcoxon rank-sum test.

Results

A total of 1,178 samples were obtained from the TCGA-BRCA database, but only 1,045 breast tumour samples were matched with complete transcriptome expression data. Meanwhile, we collected a total of 1,094 BC patients from the METABRIC cohort. We found a list of 1,399 differential immune signatures associated with survival, and functional analysis revealed that these genes participated in cytokine-cytokine receptor interactions, Th1 and Th2 cell differentiation and the JAK-STAT signalling pathway. The TAIG risk model was established from the multivariate Cox analysis, and we observed that high TAIG levels correlated with poor survival outcomes based on Kaplan-Meier analysis. The Kruskal-Wallis test suggested that high TAIG levels correlated with high AJCC-TNM stages and advanced pathological stages (P<0.01). We validated the well robustness of TAIG in METABRIC cohort and 5-year AUC reached up to 0.829. Moreover, we further uncovered the associations of hub immune signatures with immune cells and calculated the immune cell fractions in specific tumour samples based on gene signature expression. Last, we used the Wilcoxon rank-sum test to compare the differential immune density in the two groups and found that several immune cells had a significantly lower infiltrating density in the high TAIG groups, including CD8⁺ T cells (P=0.031), memory resting CD4⁺ T cells (P=0.026), M0 macrophages (P=0.023), and M2 macrophages (P=0.048).

Conclusions

In summary, we explored the immune signature of BC and constructed a TAIG risk model to predict prognosis. Moreover, we integrated the identified immune signature with tumour-infiltrating immune cells and found adverse associations between the TAIG levels and immune cell infiltrating density.