Association Between Genomic Metrics and Immune Infiltration in Triple-Negative Breast Cancer

Karn, Thomas; Jiang, Tingting; Hatzis, Christos; Sänger, Nicole; El‐Balat, Ahmed; Rody, Achim; Holtrich, Uwe; Becker, Sven; Bianchini, Giampaolo; Pusztai, Lajos

doi:10.1001/jamaoncol.2017.2140

Cited by 129 publications

(137 citation statements)

References 15 publications

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“…However, in the case of the TCGA, not all those variables are measurable, but some might be included in further work. In this line of thought, earlier results exhibited correlation of ITH with other factors like CNA abundance, sample purity, immune infiltration [53,54,68,13]. Our results show that the strength (and even direction in the case of CNA abundance and mutation load) of correlation between those factors and ITH varies between the different tested ITH measures.…”

Section: Association With Survival Link With Other Variablessupporting

confidence: 69%

Section: Methods Quantifying Ith Exhibit Inconsistent Resultsmentioning

confidence: 59%

“…score and CNA abundance [53,22,54], or between purity and ITH, as ITH methods were initially designed to refine purity estimation [29], and we observe similar behaviors. Association with immune infiltration has also been considered [54], though it is worth noting that immune infiltration and tumor purity are not independent, as immune cells are not cancerous. Each group of ITH methods is highly correlated to distinct genomic metrics, mutation load and CNV abundance (perc non diploid) for the first group (MATH, Expands), and purity (and the opposite of immune cells infiltration (inv T cells)) for the latter (PyClone, SciClone, PhyloWGS CSR).…”

Section: Methods Quantifying Ith Exhibit Inconsistent Resultsmentioning

confidence: 59%

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Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data

Abecassis

Hamy

Laurent

et al. 2018

Preprint

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Tumors are made of evolving and heterogeneous populations of cells which arise from successive appearance and expansion of subclonal populations, following acquisition of mutations conferring them a selective advantage. Those subclonal populations can be sensitive or resistant to different treatments, and provide information about tumor aetiology and future evolution. Hence, it is important to be able to assess the level of heterogeneity of tumors with high reliability for clinical applications.In the past few years, a large number of methods have been proposed to estimate intra-tumor heterogeneity from whole exome sequencing (WES) data, but the accuracy and robustness of these methods on real data remains elusive. Here we systematically apply and compare 6 computational methods to estimate tumor heterogeneity on 1,697 WES samples from the cancer genome atlas (TCGA) covering 3 cancer types (breast invasive carcinoma, bladder urothelial carcinoma, and head and neck squamous cell carcinoma), and two distinct input mutation sets. We observe significant differences between the estimates produced by different methods, and identify several likely confounding factors in heterogeneity assessment for the different methods. We further show that the prognostic value of tumor heterogeneity for survival prediction is limited in those datasets, and find no evidence that it improves over prognosis based on other clinical variables.In conclusion, heterogeneity inference from WES data on a single sample, and its use in cancer prognosis, should be considered with caution. Other approaches to assess intra-tumoral heterogeneity such as those based on multiple samples may be preferable for clinical applications.

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Section: Association With Survival Link With Other Variablessupporting

confidence: 69%

Section: Methods Quantifying Ith Exhibit Inconsistent Resultsmentioning

confidence: 59%

Section: Methods Quantifying Ith Exhibit Inconsistent Resultsmentioning

confidence: 59%

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Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data

Abecassis

Hamy

Laurent

et al. 2018

Preprint

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“…In a recent report by Pusztai and colleagues, 39 a lymphocyte-rich tumor subgroup of TNBC with good prognosis was shown to associate with reduced clonal heterogeneity and a reduced distribution of mutation count (compared to a poor prognosis TNBC subgroup). This finding suggests the selective culling of immunogenic TNBC cells by immune surveillance.…”

Section: Discussionmentioning

confidence: 97%

“…al. 39 METABRIC : Normalized expression microarray and copy number data for 1,980 primary invasive breast cancer cases were obtained by Wake Forest IRB approval and controlled access from the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/studies/EGAS00000000083). Mutation counts and updated clinical data were obtained from Pereira and colleagues.…”

Section: Methodsmentioning

confidence: 99%

Tumor mutational burden is a determinant of immune-mediated survival in breast cancer

et al. 2018

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Mounting evidence supports a role for the immune system in breast cancer outcomes. The ability to distinguish highly immunogenic tumors susceptible to anti-tumor immunity from weakly immunogenic or inherently immune-resistant tumors would guide development of therapeutic strategies in breast cancer. Genomic, transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohorts were used to examine statistical associations between tumor mutational burden (TMB) and the survival of patients whose tumors were assigned to previously-described prognostic immune subclasses reflecting favorable, weak or poor immune-infiltrate dispositions (FID, WID or PID, respectively). Tumor immune subclasses were associated with survival in patients with high TMB (TMB-Hi, P < 0.001) but not in those with low TMB (TMB-Lo, P = 0.44). This statistical relationship was confirmed in the METABRIC cohort (TMB-Hi, P = 0.047; TMB-Lo, P = 0.39), and also found to hold true in the more-indolent Luminal A tumor subtype (TMB-Hi, P = 0.011; TMB-Lo, P = 0.91). In TMB-Hi tumors, the FID subclass was associated with prolonged survival independent of tumor stage, molecular subtype, age and treatment. Copy number analysis revealed the reproducible, preferential amplification of chromosome 1q immune-regulatory genes in the PID immune subclass. These findings demonstrate a previously unappreciated role for TMB as a determinant of immune-mediated survival of breast cancer patients and identify candidate immune-regulatory mechanisms associated with immunologically cold tumors. Immune subtyping of breast cancers may offer opportunities for therapeutic stratification.

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An immune relevant signature for predicting prognoses and immunotherapeutic responses in patients with muscle‐invasive bladder cancer (MIBC)

et al. 2020

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Immune checkpoint inhibitors (ICIs) are novel treatments that significantly improve the survival time of MIBC patients, but immunotherapeutic responses are different among MIBC patients. Therefore, it is urgent to find predictive biomarkers that can accurately identify MIBC patients who are sensitive to ICIs. In this study, we computed the relative abundances of 24 immune cells based on the expression profiles of MIBC patients using single-sample gene set enrichment analysis (ssGSEA).Unsupervised clustering analysis of the 24 immune cells was performed to classify MIBC patients into different immune-infiltrating groups. Genome (gene mutation and copy number variation), transcriptome (mRNA, lncRNA, and miRNA), and functional enrichment were found to be heterogeneous among different immune-infiltrating groups. We identified 282 differentially expressed genes (DEGs) associated with immune infiltration by comparing the expression profiles of patients with different immune infiltration profiles, and 20 core prognostic DEGs were identified by univariate Cox regression analysis. An immune-relevant gene signature (TIM signature) consisting of nine key prognostic DEGs (CCDC80, CD3D, CIITA, FN1, GBP4, GNLY, SPINK1, UBD, and VIM) was constructed using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Receiver operating characteristic (ROC) curves and subgroup analysis confirmed that the TIM signature was an ideal biomarker for predicting the prognosis of MIBC patients. Its value in predicting immunotherapeutic responses was also validated in The Cancer Genome Atlas (TCGA) cohort (AUC = 0.69, 95% CI = 0.63-0.74) and the IMvigor210 cohort (AUC = 0.64, 95% = 0.55-0.74). The TIM signature demonstrates a powerful ability to distinguish MIBC patients with different prognoses and immunotherapeutic responses, but more prospective studies are needed to assess its reliability in the future. K E Y W O R D S gene expression, immune infiltration, immunotherapeutic response, muscle-invasive bladder cancer (MIBC), prognosis | 2775 JIANG et Al.

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Association Between Genomic Metrics and Immune Infiltration in Triple-Negative Breast Cancer

Cited by 129 publications

References 15 publications

Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data

Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data

Tumor mutational burden is a determinant of immune-mediated survival in breast cancer

An immune relevant signature for predicting prognoses and immunotherapeutic responses in patients with muscle‐invasive bladder cancer (MIBC)

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