T cell receptor sequencing of early-stage breast cancer tumors identifies altered clonal structure of the T cell repertoire

Beausang, John F.; Wheeler, Amanda; Chan, Natalie H.; Hanft, Violet R.; Dirbas, Frederick M.; Jeffrey, Stefanie S.; Quake, Stephen R.

doi:10.1073/pnas.1713863114

Cited by 57 publications

(46 citation statements)

References 55 publications

(71 reference statements)

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“…Because tumor tissues are removed by surgical excision, the prognostic benefit of CD8 + TRMs likely reflects a greater systemic immunity involving circulating CD8 + T cells with shared antigen specificity or at least tumor specificity with tumor CD8 + TRMs. Although tumor specificity of breast tumor TILs and TRMs has not been formally proved, T cell receptor repertoire analysis of matched patient samples has shown that certain clonotypes are enriched in the tumor and not in NCBT (42,43). TRMs may also develop in peripheral tissues independent of antigen presence because of the presence of various cytokines common in tumor microenvironments, such as TGF-β, TNF-α, IL-33, and IL-15 (44,45).…”

Section: Figure 6 Proximity Of Cd103 + Cd8 + Trms and Not Cd103 − CDmentioning

confidence: 99%

Resident memory CD8+ T cells within cancer islands mediate survival in breast cancer patients

Egelston¹,

Avalos²,

Tu³

et al. 2019

JCI Insight

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Section: Figure 6 Proximity Of Cd103 + Cd8 + Trms and Not Cd103 − CDmentioning

confidence: 99%

Resident memory CD8+ T cells within cancer islands mediate survival in breast cancer patients

Egelston¹,

Avalos²,

Tu³

et al. 2019

JCI Insight

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“…All four models were trained using 20 runs of 4-fold cross validation. To evaluate their performances, we applied each model to the treatment-naïve cancer patient cohorts, including melanoma, breast, ovarian, and pancreatic cancers (8)(9)(10)(11). We used the 176 age-matched healthy donors from the Emerson et al, 2017 cohort as control (3).…”

Section: Iv) Cnn With Pca Encodingmentioning

confidence: 99%

Related Topics of a Novel TCR-based Cancer Detection Approach

Beshnova

2020

Preprint

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AbstractWe developed a novel algorithm (DeepCAT) to perform de novo detection of cancer associated TCRs, which is based on a convolutional neural network (CNN) model. In this manuscript, we compared its performance with a similar non-deep learning approach, TCRboost, and demonstrated that DeepCAT achieved better prediction accuracy when used to distinguish cancer from non-cancer individuals. Further, although DeepCAT was trained for CDR3s with different lengths, we showed that the combined outcome does not bias the prediction accuracy. Finally, human immune repertoire is affected by many common inflammatory conditions, and our analysis demonstrated that DeepCAT predictions are minimally affected by these factors.

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“…To learn whether our observations in the mouse model might be relevant to human breast cancer, we compared the mouse TCR data to three, previously published human TCR datasets, each of which focused on a different aspect of breast cancer (Figure 3a) (Beausang et al, 2017;Page et al, 2016;Wang et al, 2017): Beausang et al (Beausang et al, 2017) studied T cell receptors in early-stage breast cancer and sampled the tumor tissue, the surrounding normal tissue and peripheral blood. Wang et al (Wang et al, 2017) sequenced the TCR repertoires of breast cancer tumors, lymph nodes and adjacent tissue.…”

Section: Fig 1 Experimental Procedurementioning

confidence: 99%

Mice developing mammary tumors evolve T cell sequences shared with human breast cancer patients

Gordin

Philip

Zilberberg

et al. 2018

Preprint

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† These authors contributed equally to this work.Cancer immunotherapy by checkpoint blockade proves that an effective immune response to a tumor can be induced clinically. However, little is known about the evolution of tumorassociated T-cell receptor (TCR) repertoires without intervention. Here we studied TCR repertoire evolution in mice spontaneously developing mammary tumors; we sequenced peripheral blood alpha and beta TCRs of CD4 + CD62L + CD44 -T cells monthly for 8 months in 10 FVB/NJ mice transgenic at the Erbb2 locus, all developing tumors; 5 FVB/NJ mice without the transgene were age-matched controls. Sequences were either private (restricted to one mouse) or public (shared among mice); public sequences were either exclusive to the tumor group or inclusive among different groups. We now report that 1), public AA sequences were each encoded by many different nucleotide sequences (NT) recombinations (convergent recombination; CR); 2) mice developing tumors evolved tumor-exclusive public sequences, derived initially from private or from inclusive public sequences; and 3) tumor-exclusive public sequences in mice were also present among published public TCR sequences from human breast cancer patients. These cross-species tumor-exclusive TCR sequences manifested high CR; but the AA sequences shared by mice and humans did not share NT sequences. Thus, tumor-exclusive TCR AA sequences across species are selected from different NT recombination events. The roles of tumor-exclusive TCR repertoires in advancing or inhibiting tumor development and the effects of tumor immunotherapy on these T cells remain to be seen.

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T cell receptor sequencing of early-stage breast cancer tumors identifies altered clonal structure of the T cell repertoire

Cited by 57 publications

References 55 publications

Resident memory CD8+ T cells within cancer islands mediate survival in breast cancer patients

Resident memory CD8+ T cells within cancer islands mediate survival in breast cancer patients

Related Topics of a Novel TCR-based Cancer Detection Approach

Mice developing mammary tumors evolve T cell sequences shared with human breast cancer patients

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