Construction of novel immune-related signature for prediction of pathological complete response to neoadjuvant chemotherapy in human breast cancer

Sota, Yoshiaki; Naoi, Yasuto; Tsunashima, Ryo; Kagara, Naofumi; Shimazu, Kenzo; Maruyama, Naomi; Shimomura, Atsushi; Shimoda, Masafumi; Kishi, Kazuki; Baba, Yosuke; Kim, S.J.; Noguchi, Shinzaburo

doi:10.1093/annonc/mdt427

Cited by 36 publications

(31 citation statements)

References 25 publications

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“…Consistent with previous reports [13,15,16], we found that the Immunity metagene was predictive of the response to NAC in HER2 -positive BC. However, despite the similar gene module identification methods used and the strong correlation between the Immunity metagene and the Immunity2 metagene previously described by our team for TNBC [3], the Immunity metagene was predictive of the response to chemotherapy in HER2- positive BC, whereas the Immunity2 metagene was not predictive of the response to chemotherapy in TNBC.…”

Section: Discussionsupporting

confidence: 93%

“…The prognostic value of HDDP was demonstrated in both subgroups (11), but its value for predicting the response to NAC was not evaluated as a function of ER status. Conversely, the IRSN-23 [15] was not predictive in the ER-positive subpopulation. However, few authors determined the predictive [18] or prognostic value of their metagene or signature as a function of ER status within HER2 -positive breast cancers [5,13,14,19–21].…”

Section: Discussionmentioning

confidence: 99%

“…Thus, the prognostic impact of TILs on survival remains a matter of debate in HER2- positive BC. A few authors have reported a correlation between TIL and stromal lymphocyte levels and gene expression in HER2 -positive breast cancers [13,15,21]. If this correlation is further validated, TIL levels could be used as a surrogate marker for the Immunity metagene, as TIL assessment is carried out in routine practice and is currently undergoing standardization [54].…”

Section: Discussionmentioning

confidence: 99%

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A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2-Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways

et al. 2016

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IntroductionHER2-positive breast cancer (BC) is a heterogeneous group of aggressive breast cancers, the prognosis of which has greatly improved since the introduction of treatments targeting HER2. However, these tumors may display intrinsic or acquired resistance to treatment, and classifiers of HER2-positive tumors are required to improve the prediction of prognosis and to develop novel therapeutic interventions.MethodsWe analyzed 2893 primary human breast cancer samples from 21 publicly available datasets and developed a six-metagene signature on a training set of 448 HER2-positive BC. We then used external public datasets to assess the ability of these metagenes to predict the response to chemotherapy (Ignatiadis dataset), and prognosis (METABRIC dataset).ResultsWe identified a six-metagene signature (138 genes) containing metagenes enriched in different gene ontologies. The gene clusters were named as follows: Immunity, Tumor suppressors/proliferation, Interferon, Signal transduction, Hormone/survival and Matrix clusters. In all datasets, the Immunity metagene was less strongly expressed in ER-positive than in ER-negative tumors, and was inversely correlated with the Hormonal/survival metagene. Within the signature, multivariate analyses showed that strong expression of the “Immunity” metagene was associated with higher pCR rates after NAC (OR = 3.71[1.28–11.91], p = 0.019) than weak expression, and with a better prognosis in HER2-positive/ER-negative breast cancers (HR = 0.58 [0.36–0.94], p = 0.026). Immunity metagene expression was associated with the presence of tumor-infiltrating lymphocytes (TILs).ConclusionThe identification of a predictive and prognostic immune module in HER2-positive BC confirms the need for clinical testing for immune checkpoint modulators and vaccines for this specific subtype. The inverse correlation between Immunity and hormone pathways opens research perspectives and deserves further investigation.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2-Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways

et al. 2016

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“…The multigene classifier has been attracting major attention as a pCR predictor because it has been very successful in improving prediction for patient prognosis [3][4][5][6][7]. From the practical point of view, the aim of these predictors is to identify patients who are very unlikely to respond to NAC and thus to avoid unnecessary NAC in the same manner as ER for hormonal therapy and human epidermal growth factor receptor 2 (HER2) for anti-HER2 therapies [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Although such prediction models can increase the positive predictive value (PPV) of pCR up to around 30-40%, the negative predictive value (NPV) remains around 80-90% [10], indicating that 10-20% of breast tumors can still attain pCR in spite of the negative prediction. From the practical point of view, NPV of 10-20% is too high for NAC to be avoided.…”

Section: Introductionmentioning

confidence: 99%

Construction of multi-gene classifier for prediction of response to and prognosis after neoadjuvant chemotherapy for estrogen receptor positive breast cancers

et al. 2015

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A four‐gene signature predicts the efficacy of paclitaxel‐based neoadjuvant therapy in human epidermal growth factor receptor 2–negative breast cancer

Zhang

et al. 2018

J of Cellular Biochemistry

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Neoadjuvant chemotherapy (NAC) is the major preoperative treatment of breast cancer (BC) with negative human epidermal growth factor receptor 2 (HER2), and the efficacy of NAC and the optimization of regimen are under intensive research. The current study aimed to define the predictive biomarkers for paclitaxel (PTX) response in NAC of HER2‐negative BC. Data from GSE25065, GSE26065, GSE41998, as well as drug sensitivity data of breast and ovarian cancer cell line from NCI60, were used. Through logistic regression, COX regression, and correlation analysis with bootstrapping, we found that four genes (CDK8, FAM64A, MARC2, and OCEL1) were associated with drug sensitivity of PTX. The four gene “≥3” model had the best classification accuracy. Subgroup analysis found that the model performed well in the hormone receptor positive, HER2‐negative subgroup and did not perform well in the triple‐negative subgroup. Decision curve analysis showed that the model could enhance the predictive effect of clinical features. Subsequent gene set enrichment analysis, network analysis showed that these genes may be related to the cell cycle, mitosis and other pathways. The current study demonstrated the promising potential of the novel four‐gene signature as a predictive biomarker for pathological complete response of HER2‐negative BC patients and indicated the drug sensitivity of PTX.

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Construction of novel immune-related signature for prediction of pathological complete response to neoadjuvant chemotherapy in human breast cancer

Cited by 36 publications

References 25 publications

A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2-Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways

A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2-Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways

Construction of multi-gene classifier for prediction of response to and prognosis after neoadjuvant chemotherapy for estrogen receptor positive breast cancers

A four‐gene signature predicts the efficacy of paclitaxel‐based neoadjuvant therapy in human epidermal growth factor receptor 2–negative breast cancer

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