Dataset Information

HLA-DR in Cytotoxic T Lymphocytes Predicts Breast Cancer Patients' Response to Neoadjuvant Chemotherapy.

ABSTRACT: Prediction of breast cancer response to Neoadjuvant Chemotherapy (NACT) is an urgent need to promptly direct non-responder patients to alternative therapies. Infiltrating T lymphocytes, namely cytotoxic T lymphocytes (CTLs) have been appointed as predictors of response. However, cancer cells have the ability to dampen CTLs' activity and thus, the prognostic value of the CTLs, per se, is debatable. Here, we disclose that more than the occurrence of CTLs, it is their activation state, revealed by HLA-DR expression, that can accurately predict response to NACT. Flow cytometry analysis of breast cancer biopsies showed that the frequency of CTLs and other lymphocytes were similar regardless disease stage and between NACT responders and non-responders. However, only breast cancer patients without axillary lymph node metastasis and NACT responders have HLA-DRhi CTLs. Interestingly, HLA-DR levels in tumor CTLs is correlated with HLA-DR levels in systemic CTLs. These HLA-DR+ CTLs produce IFN-? and Granzyme B, enlightening their effector and probable anti-tumor activity profile. Moreover, the level of HLA-DR in CTLs is negatively correlated with the level of HLA-DR in T regulatory lymphocytes and with immunosuppressive and pro-tumor molecules in the tumor microenvironment. Hence, HLA-DR levels in CTLs is a highly sensitive and specific potential predictive factor of NACT-response, which can be assessed in blood to guide therapeutic decisions.

SUBMITTER: Saraiva DP

PROVIDER: S-EPMC6282034 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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HLA-DR in Cytotoxic T Lymphocytes Predicts Breast Cancer Patients' Response to Neoadjuvant Chemotherapy.

Saraiva Diana P DP Jacinto António A Borralho Paula P Braga Sofia S Cabral M Guadalupe MG

Frontiers in immunology 20181113

Prediction of breast cancer response to Neoadjuvant Chemotherapy (NACT) is an urgent need to promptly direct non-responder patients to alternative therapies. Infiltrating T lymphocytes, namely cytotoxic T lymphocytes (CTLs) have been appointed as predictors of response. However, cancer cells have the ability to dampen CTLs' activity and thus, the prognostic value of the CTLs, <i>per se</i>, is debatable. Here, we disclose that more than the occurrence of CTLs, it is their activation state, revea ...[more]

PMID: 30555458

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Project description:Our goal was to determine the impact of pathologic response after neoadjuvant chemotherapy in triple negative breast cancer (TNBC) on the subsequent risk of locoregional recurrence (LRR) and disease-free survival (DFS) in the setting of adjuvant radiation therapy.This was an institutional review board-approved retrospective chart review of patients with clinical stage I-III breast cancer treated with neoadjuvant chemotherapy, local surgery (breast conservation or mastectomy), and adjuvant radiation therapy between 1997 and 2015. Medical records were reviewed for clinical stage, tumor grade and subtype, neoadjuvant chemotherapy regimen, type of surgery, pathologic stage, use of radiation therapy, date and location of recurrence, and date of death. Molecular subtypes were defined using immunohistochemistry and histologic grade. ypT0 and ypN0 were defined as no residual invasive disease in breast or nodes, respectively. LRR was defined as any failure within the breast, chest wall, or regional lymph nodes. Statistical analysis was performed; LRR and DFS rates over 30 months were determined from Kaplan-Meier plots.Ninety-four patients with TNBC were analyzed, of whom 72 received radiation therapy. This subgroup was isolated for further investigation. Median follow-up was 32.5 months in this group. The pathologic complete response (pCR) rate was 36%, and presence or absence of disease in breast and/or nodes was significantly predictive of LRR. In TNBC patients who received radiation therapy, 30-month LRR was 22% in 41 patients with ypT+ versus 0% in 31 patients with ypT0 (P = .003), 23% in 31 patients with ypN+ versus 5% in 41 patients with ypN0 (P = .016), and 20% in 46 patients with residual disease in breast or nodes versus 0% in 26 patients with pCR (P = .015). The difference in the rate of LRR between those who underwent lumpectomy versus mastectomy did not reach significance (8% vs 17%, respectively). Furthermore, patients with residual disease had a higher rate of DFS events (hazard ratio, 3.58; 95% confidence interval, 1.37-9.41; P = .006). The difference in DFS was not significantly associated with the type of surgery received.Patients with TNBC treated with neoadjuvant chemotherapy who have residual disease in the breast or lymph nodes at the time of surgery have significantly higher rates of locoregional failure and lower DFS compared with those with a pCR despite the use of adjuvant radiation therapy. Strategies to intensify therapy for patients with residual disease warrant further investigation.

Project description:BackgroundNeoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor's disease pathology. Developing genomic clinical assays that accurately categorize responders from non-responders can provide patients with the most effective therapy for their individual disease.MethodsWe applied our previously developed E2F4 genomic signature to predict neoadjuvant chemotherapy response in breast cancer. E2F4 individual regulatory activity scores were calculated for 1129 patient samples across 5 independent breast cancer neoadjuvant chemotherapy datasets. Accuracy of the E2F4 signature in predicting neoadjuvant chemotherapy response was compared to that of the Oncotype DX and MammaPrint predictive signatures.ResultsIn all datasets, E2F4 activity level was an accurate predictor of neoadjuvant chemotherapy response, with high E2F4 scores predictive of achieving pathologic complete response and low scores predictive of residual disease. These results remained significant even after stratifying patients by estrogen receptor (ER) status, tumor stage, and breast cancer molecular subtypes. Compared to the Oncotype DX and MammaPrint signatures, our E2F4 signature achieved similar performance in predicting neoadjuvant chemotherapy response, though all signatures performed better in ER+ tumors compared to ER- ones. The accuracy of our signature was reproducible across datasets and was maintained when refined from a 199-gene signature down to a clinic-friendly 33-gene panel.ConclusionOverall, we show that our E2F4 signature is accurate in predicting patient response to neoadjuvant chemotherapy. As this signature is more refined and comparable in performance to other clinically available gene expression assays in the prediction of neoadjuvant chemotherapy response, it should be considered when evaluating potential treatment options.

Dataset Information

HLA-DR in Cytotoxic T Lymphocytes Predicts Breast Cancer Patients' Response to Neoadjuvant Chemotherapy.

Publications

HLA-DR in Cytotoxic T Lymphocytes Predicts Breast Cancer Patients' Response to Neoadjuvant Chemotherapy.

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