Validation of late recurrence prediction by gene expression profiles and clinicopathological factors in estrogen receptor-positive breast cancer.

BACKGROUND: The mechanism of late recurrence (LR) of estrogen receptor (ER)-positive breast cancer remains unclear, as previous studies have separately investigated "gene expression profiles" and "clinicopathological factors." Thus, this study aimed to evaluate the predictive capability of LR by combining the two independent factors of gene expression profiles (42-gene classifier: 42GC) and clinicopathological factors (Clinical Treatment Score post-5 years: CTS5) in multiple large cohorts. METHODS: We analyzed microarray CEL file data downloaded from public databases of 28 global cohorts. A total of 2,454 patients with ER-positive breast cancer were analyzed for 42GC, and 1,263 of these, with complete clinicopathological data were analyzed for CTS5. RESULTS: In the analysis of recurrent patients, the 42GC LR and CTS5 low-risk group tended to have LR. Notably, in the analysis of patients with and without recurrence, the highest LR rate beyond 5 years was observed in the CTS5 high-risk group. The combination of the 42GC and CTS5 high-risk groups showed the highest LR rate (16.9%), significantly exceeding that of the 42GC non-LR (NLR) and CTS5 low-risk combination (5.41%) (p = 0.038, odds ratio = 3.53). Furthermore, incorporating a third factor, 95GC, potentially reduced the number of patients prioritized for extended hormonal therapy for approximately one-quarter of patients. CONCLUSIONS: Results confirmed that the two factors, gene expression profiles and clinicopathological factors, affect the time of recurrence. It also showed that the biological predisposition for LR (CTS5 low-risk) differed from the high LR rate (CTS5 high-risk). In clinical practice, patients with the 42GC LR and CTS5 high-risk combination should be prioritized for extended hormonal therapy. The addition of CTS5 and 95GC to 42GC allows for better risk classification of LR.

Investigation of recurrence prediction ability of EndoPredict® using microarray data from fresh frozen tissues in ER-positive, HER2-negative breast cancer and indication expansion of EndoPredict® from microarray data from fresh-frozen to FFPE tissues.

BACKGROUND: EndoPredict® (EP) is a multigene assay to predict distant recurrence risk in luminal breast cancer. EP measures the expression of 12 genes in primary tumor by qRT-PCR from formalin-fixed paraffin-embedded (FFPE) tissues and calculates EP risk score that indicates the risk of distant recurrence. We evaluated the performance of EP in predicting distant recurrence risk using microarray data from fresh frozen (FF) tissues. We also examined the applicability of EP to microarray data from FFPE tissues. METHODS: We analyzed the publicly available data of 431 node-negative and 270 node-positive patients with luminal breast cancer who received endocrine therapy alone. We evaluated the prognostic value of EP using microarray data from FF tissues. Next, we created an algorithm to calculate EP risk score using microarray data from FFPE tissues. We examined the correlation coefficient of EP risk score and concordance rate of EP risk high/low using microarray data from FFPE/FF tissue pairs in a validation set of 39 patients. RESULTS: In 431 node-negative patients, the distant recurrence-free survival (DRFS) rate was significantly worse in those with high EP risk scores (P = 3.68 × 10-6, log-rank). The 5-year DRFS was 95.2% in those with low EP risk score. In the validation set, the correlation coefficient of EP risk score was 0.93 and the concordance rate of EP risk high/low was 91.7%. CONCLUSIONS: EP using microarray data from FF tissues was useful in predicting distant recurrence risk in luminal breast cancer, and EP might be utilized in microarray data from FFPE tissues.

Multi-gene assay 95- and 155-gene classifiers for prognosis prediction and chemotherapy omission in lymphnode positive luminal-type breast cancer.

BACKGROUND: The prognosis of lymphnode positive breast cancer is worse than that of lymph node negative breast cancer but some cases may not require chemotherapy. We investigated the ability of the new multi-gene assays, 95GC and 155GC, to identify patients with lymphnode positive Luminal-type breast cancer whose chemotherapy can be omitted relatively safely. PATIENTS AND METHODS: We extracted 1721 cases of lymphnode positive Luminal-type breast cancer from 22 public database Caucasoid cohorts and 3 Asian cohorts, and performed recurrence prognosis analysis with 95GC and 155GC. RESULTS: Using 95GC, the cases were stratified as the high (n = 917) and low (n = 202) groups according to the prognosis of lymphnode positive Luminal-type endocrine only breast cancer. The 5 years DRFS in the low risk group was relatively good at 90%, and no additional effect of chemotherapy was observed, suggesting omission of chemotherapy. The recurrence prognosis was also significantly dichotomized into the high and low risks by 95GC in 21GC RS 0-25 cases. Here, we found a group with poor prognosis even in post-menopause RS 0-25 and requiring chemotherapy. Additionally, a group in which the prognosis was good in pre-menopause RS 0-25, and the omission of chemotherapy could be considered. Patients in the high-risk group at 155GC had poor prognosis after chemotherapy. 155GC also showed a group that chemotherapy alone was not sufficient. CONCLUSION: In this study, we demonstrated the possibility of accurately selecting patient groups for which chemotherapy can be omitted from lymphnode positive Luminal-type breast cancer.

Low Eosinophil Percentages as a New Predictive Marker for Infusion Reactions Due to Trastuzumab.

BACKGROUND/AIM: Infusion reactions (IRs) often occur with trastuzumab. Although premedication by non-steroidal anti-inflammatory drugs can be effective to a certain extent, IRs are still common and infrequently severe. Therefore, a predictive marker that can select patients requiring further prophylaxis is useful for appropriate prevention, but remains unclear. PATIENTS AND METHODS: We conducted a retrospective analysis for 136 consecutive female inpatients aged 18 years and older who received 8 mg/kg of the initial trastuzumab administration for breast cancer with a 25-mg dose of rectal diclofenac before trastuzumab infusion between May 2007 and April 2019, in order to assess IRs. RESULTS: Overall, 57 patients were eligible for inclusion in the study. IRs were observed in 17.5% (10/57) of the patients. Univariate analysis showed that patients with a low eosinophil percentage (≤2%) were associated with IRs (p=0.016). CONCLUSION: A low eosinophil percentage can be a useful new predictive marker for trastuzumab-induced IRs in patients with breast cancer.

Defect Engineering of Earth-Abundant Solar Absorbers BiSI and BiSeI.

Bismuth-based solar absorbers have recently garnered attention due to their promise as cheap, nontoxic, and efficient photovoltaics. To date, however, most show poor efficiencies far below those seen in commercial technologies. In this work, we investigate two such promising materials, BiSI and BiSeI, using relativistic first-principles methods with the aim of identifying their suitability for photovoltaic applications. Both compounds show excellent optoelectronic properties with ideal band gaps and strong optical absorption, leading to high predicted device performance. Using defect analysis, we reveal the electronic and structural effects that can lead to the presence of deep trap states, which may help explain the prior poor performance of these materials. Crucially, detailed mapping of the range of experimentally accessible synthesis conditions allows us to provide strategies to avoid the formation of killer defects in the future.