Immune DNA signature of T-cell infiltration in breast tumor exomes

Lévy, Eric; Marty, Rachel; Calderón, Valentina Gárate; Woo, Brian; Dow, Michelle; Armisén, Ricardo; Carter, Hannah; Harismendy, Olivier

doi:10.1038/srep30064

Cited by 31 publications

(21 citation statements)

References 55 publications

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“…In other two studies, the immune signature predicted benefit from trastuzumab in adjuvant (Perez et al 2015) or neoadjuvant (Varadan et al 2016) settings. Interestingly, in these and other studies (Levy et al 2016, Heimes et al 2017, Kim et al 2017, when immunological signature was associated with immune function and immune response, it directly correlated with a better clinical outcome. Moreover, epigenetic alterations, in addition to the genetic alterations, of immune genes with prognostic impact have been increasingly reported in different types of cancers, including breast cancer.…”

Section: Immune Signatures and Prognosismentioning

confidence: 49%

Tumour growth and immune evasion as targets for a new strategy in advanced cancer

Nicolini¹,

Rossi²,

Carpi³

2018

Endocrine-Related Cancer

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It has become clearer that advanced cancer, especially advanced breast cancer, is an entirely displayed pathological system that is much more complex than previously considered. However, the direct relationship between tumour growth and immune evasion can represent a general rule governing the pathological cancer system from the initial cancer cells to when the system is entirely displayed. Accordingly, a refined pathobiological model and a novel therapeutic strategy are proposed. The novel therapeutic strategy is based on therapeutically induced conditions (undetectable tumour burden and/or a prolonged tumour 'resting state'), which enable an efficacious immune response in advanced breast and other types of solid cancers.

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Section: Immune Signatures and Prognosismentioning

confidence: 49%

Tumour growth and immune evasion as targets for a new strategy in advanced cancer

Nicolini¹,

Rossi²,

Carpi³

2018

Endocrine-Related Cancer

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“…Finding biophysicochemical TCRb motifs that, within a cancer type, are shared across the TILs repertoires of all patients but are largely absent from healthy tissue repertoires is consistent with the hypothesis that we are detecting TCR with specificity for a tumorassociated antigen that is shared between patients. We are not the first to hypothesize that patients may have shared TCRs responding to a common antigen, nor are we the first to look for the corresponding TCRs in colorectal and breast cancer TILs (7,10,25,26,41,42). To address this hypothesis, other investigators have searched for CDR3 amino acid sequences that were shared between multiple patient TILs repertoires (7,10,25,26,41,42).…”

Section: Discussionmentioning

confidence: 99%

“…None of the studies found sequences shared across all patients in a study, and the degree of sharing varied tremendously. In the breast cancer studies, it was concluded that the shared TCRb CDR3 sequences most likely correspond to public clones rather than receptors responding to common cancer antigens, because the same TCRb CDR3 sequences were frequently found in databases of TCRb repertoires from presumed healthy individuals (7,25,41,42). In addition, Beausang and colleagues analyzed the sequence properties of the shared sequences and found that they had many features in common with the TCRb CDR3 sequences of public clones, such as being shorter in length and having few insertions (25).…”

Section: Discussionmentioning

confidence: 99%

Biophysicochemical Motifs in T-cell Receptor Sequences Distinguish Repertoires from Tumor-Infiltrating Lymphocyte and Adjacent Healthy Tissue

et al. 2019

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Immune repertoire deep sequencing allows comprehensive characterization of antigen receptor-encoding genes in a lymphocyte population. We hypothesized that this method could enable a novel approach to diagnose disease by identifying antigen receptor sequence patterns associated with clinical phenotypes. In this study, we developed statistical classifiers of T-cell receptor (TCR) repertoires that distinguish tumor tissue from patient-matched healthy tissue of the same organ. The basis of both classifiers was a biophysicochemical motif in the complementarity determining region 3 (CDR3) of TCRb chains. To develop each classifier, we extracted 4-mers from every TCRb CDR3 and represented each 4-mer using biophysicochemical features of its amino acid sequence combined with quantification of 4-mer (or receptor) abundance. This representation was scored using a logistic regression model. Unlike typical logistic regression, the classifier is fitted and validated under the requirement that at least 1 positively labeled 4-mer appears in every tumor repertoire and no positively labeled 4-mers appear in healthy tissue repertoires. We applied our method to publicly available data in which tumor and adjacent healthy tissue were collected from each patient. Using a patient-holdout cross-validation, our method achieved classification accuracy of 93% and 94% for colorectal and breast cancer, respectively. The parameter values for each classifier revealed distinct biophysicochemical properties for tumor-associated 4-mers within each cancer type. We propose that such motifs might be used to develop novel immune-based cancer screening assays.Significance: This study presents a novel computational approach to identify T-cell repertoire differences between normal and tumor tissue. 1 We treat TCRb sequences with identical CDR3 sequences as being the same TCRb sequence, ignoring differences upstream of CDR3.

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“…After capture of the whole-exome by hybrid selection, the DNA libraries were amplified and sequenced. The performance was evaluated in comparison to whole exome data generated from 200 ng of DNA extracted from a mirrored frozen tissue specimen [38]. Libraries generated from 200 or 50 ng FFPE DNA achieved reasonable coverage, with nearly all targeted bases covered at least 20-fold (referred to as Cov20).…”

Section: Evaluation Of Targeted Sequencing Approaches For Low Input Fmentioning

confidence: 99%

Mutational profiling of micro-dissected pre-malignant lesions from archived specimens

Nachmanson

Steward²,

Yao

et al. 2020

Preprint

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Background: Systematic cancer screening has led to the increased detection of pre-malignant lesions (PMLs). The absence of reliable prognostic markers can lead to inadequate treatment resulting in unnecessary stress or avoidable progression. Importantly, most mutational profiling studies have relied on PML synchronous to invasive cancer, or performed in patients without outcome information, hence limiting their utility for biomarker discovery. The limitations in comprehensive mutational profiling of PMLs are in large part due to the significant technical and methodological challenges: most PML specimens are small, fixed in formalin and paraffin embedded (FFPE) and lack matching normal DNA. Methods:Using test DNA from a highly degraded FFPE specimen, multiple targeted sequencing approaches were evaluated, varying DNA input amount (3-200 ng), library preparation strategy (BE: Blunt-End, SS: Single-Strand, AT: A-Tailing) and target size (whole exome vs cancer gene panel). Variants in high-input DNA from FFPE and mirrored frozen specimens were used for PML-specific variant calling training and testing, respectively. The resulting approach was applied to profile and compare multiple regions micro-dissected (mean area 5 mm 2 ) from 3 breast ductal carcinoma in situ (DCIS). Results:Using low-input FFPE DNA, BE and SS libraries resulted in 4.9 and 3.7 increase over AT libraries in the fraction of whole exome covered at 20x (BE:87%, SS:63%, AT:17%).Compared to high-confidence somatic mutations from frozen specimens, PML-specific variant filtering increased recall (BE:79%, SS:74%, AT:62%) and precision (BE:87%, SS:88%, AT:80%) to levels expected from sampling variation. Copy number alterations were consistent across all tested approaches and only impacted by the design of the capture probe-set. Applied to DNA extracted from 9 micro-dissected regions (8 PML, 1 normal epithelium), the approach achieved comparable performance, identified candidate driver events (gains of ERBB2 or FGFR1, loss of TP53) and illustrated the adequacy of the data to identify candidate driver mutations and measure intra-lesion genetic heterogeneity. Conclusion:The approach presented enables mutational profiling from archived microdissected PML regions, supporting the identification of pre-malignant drivers, and the characterization of PML molecular heterogeneity and evolution, all critical milestones the development of biology-informed prognostic markers and precision chemo-prevention strategies.

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Immune DNA signature of T-cell infiltration in breast tumor exomes

Cited by 31 publications

References 55 publications

Tumour growth and immune evasion as targets for a new strategy in advanced cancer

Tumour growth and immune evasion as targets for a new strategy in advanced cancer

Biophysicochemical Motifs in T-cell Receptor Sequences Distinguish Repertoires from Tumor-Infiltrating Lymphocyte and Adjacent Healthy Tissue

Mutational profiling of micro-dissected pre-malignant lesions from archived specimens

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