Predicting prognosis of breast cancer with gene signatures: are we lost in a sea of data?

A large number of prognostic and predictive signatures have been proposed for breast cancer and a few of these are now available in the clinic as new molecular diagnostic tests. However, several other signatures have not fared well in validation studies. Some investigators continue to be puzzled by the diversity of signatures that are being developed for the same purpose but that share few or no common genes. The history of empirical development of prognostic gene signatures and the unique association between molecular subsets and clinical phenotypes of breast cancer explain many of these apparent contradictions in the literature. Three features of breast cancer gene expression contribute to this: the large number of individually prognostic genes (differentially expressed between good and bad prognosis cases); the unstable rankings of differentially expressed genes between datasets; and the highly correlated expression of informative genes

Biomarkers of neoadjuvant/adjuvant chemotherapy for breast cancer

The improvement of tumor biomarkers prepared for clinical use is a long process. A good biomarker should predict not only prognosis but also the response to therapies. In this review, we describe the biomarkers of neoadjuvant/adjuvant chemotherapy for breast cancer, considering different breast cancer subtypes. In hormone receptor (HR)-positive/human epidermal growth factor 2 (HER2)-negative breast cancers, various genomic markers highly associated with proliferation have been tested. Among them, only two genomic signatures, the 21-gene recurrence score and 70-gene signature, have been reported in prospective randomized clinical trials and met the primary endpoint. However, these genomic markers did not suffice in HER2-positive and triple-negative (TN) breast cancers, which present only classical clinical and pathological information (tumor size, nodal or distant metastatic status) for decision making in the adjuvant setting in daily clinic. Recently, patients with residual invasive cancer after neoadjuvant chemotherapy are at a high-risk of recurrence for metastasis, which, in turn, make these patients best applicants for clinical trials. Two clinical trials have shown improved outcomes with post-operative capecitabine and ado-trastuzumab emtansine treatment in patients with either TN or HER2-positive breast cancer, respectively, who had residual disease after neoadjuvant chemotherapy. Furthermore, tumor-infiltrating lymphocytes (TILs) have been reported to have a predictive value for prognosis and response to chemotherapy from the retrospective analyses. So far, TILs have to not be used to either withhold or prescribe chemotherapy based on the absence of standardized evaluation guidelines and confirmed information. To overcome the low reproducibility of evaluations of TILs, gene signatures or digital image analysis and machine learning algorithms with artificial intelligence may be useful for standardization of assessment for TILs in the future

Simultaneous hot and cold thyroid nodules: Which is malignant?

Physicians should be aware of the risk of malignancy in patients with toxic multinodular goiter. Radionuclide scan cannot be used to predict the malignant potential of thyroid nodules. A comprehensive evaluation of imaging studies is needed

Correlation between 18F-fluorodeoxyglucose Positron Emission Tomography/computed Tomography and Clinicopathological Features in Invasive Ductal Carcinoma of the Breast

We evaluated the usefulness of preoperative 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) examinations to predict the pathological features in primary breast cancer. In particular, we evaluated the correlation between the maximum standardized uptake values (SUVmax) obtained by 18F-FDG PET/CT and the Ki67 expression in estrogen receptor (ER)-positive invasive ductal carcinoma (IDC). Primary IDC patients operated between March 2009 and July 2013 at Okayama University Hospital were enrolled. We evaluated the correlations between the SUVmax and age, postoperative pT, histological grade, lymph vascular invasion, status of hormone receptor, human epidermal growth factor receptor 2 (HER2), Ki67 expression and node status. The Ki67 expression was classified as high (>14%) versus low (<14%). We enrolled 138 patients with IDC. Their median SUVmax was 3.85 (range:0-52.57). In a univariate analysis, the SUVmax was significantly related to age, pT, histological grade, lymphovascular invasion, hormone receptor status, HER2 status, node status and Ki67. In the 113 patients with ER-positive IDC, there was a significant correlation between Ki67 and SUVmax (p=0.0030). The preoperative 18F-FDG PET/CT results of IDC patients had significant relationships with pathological status parameters. The determination of the preoperative SUVmax might help classify Luminal A and Luminal B patients among luminal-type breast cancer patients

Lack of sufficiently strong informative features limits the potential of gene expression analysis as predictive tool for many clinical classification problems

<p>Abstract</p> <p>Background</p> <p>Our goal was to examine how various aspects of a gene signature influence the success of developing multi-gene prediction models. We inserted gene signatures into three real data sets by altering the expression level of existing probe sets. We varied the number of probe sets perturbed (signature size), the fold increase of mean probe set expression in perturbed compared to unperturbed data (signature strength) and the number of samples perturbed. Prediction models were trained to identify which cases had been perturbed. Performance was estimated using Monte-Carlo cross validation.</p> <p>Results</p> <p>Signature strength had the greatest influence on predictor performance. It was possible to develop almost perfect predictors with as few as 10 features if the fold difference in mean expression values were > 2 even when the spiked samples represented 10% of all samples. We also assessed the gene signature set size and strength for 9 real clinical prediction problems in six different breast cancer data sets.</p> <p>Conclusions</p> <p>We found sufficiently large and strong predictive signatures only for distinguishing ER-positive from ER-negative cancers, there were no strong signatures for more subtle prediction problems. Current statistical methods efficiently identify highly informative features in gene expression data if such features exist and accurate models can be built with as few as 10 highly informative features. Features can be considered highly informative if at least 2-fold expression difference exists between comparison groups but such features do not appear to be common for many clinically relevant prediction problems in human data sets.</p

HaptiRead: Reading Braille as Mid-Air Haptic Information

Mid-air haptic interfaces have several advantages - the haptic information is delivered directly to the user, in a manner that is unobtrusive to the immediate environment. They operate at a distance, thus easier to discover; they are more hygienic and allow interaction in 3D. We validate, for the first time, in a preliminary study with sighted and a user study with blind participants, the use of mid-air haptics for conveying Braille. We tested three haptic stimulation methods, where the haptic feedback was either: a) aligned temporally, with haptic stimulation points presented simultaneously (Constant); b) not aligned temporally, presenting each point independently (Point-By-Point); or c) a combination of the previous methodologies, where feedback was presented Row-by-Row. The results show that mid-air haptics is a viable technology for presenting Braille characters, and the highest average accuracy (94% in the preliminary and 88% in the user study) was achieved with the Point-by-Point method.Comment: 8 pages, 8 figures, 2 tables, DIS'2

Differences in Attitudes and Practices of Cancer Pain Management between Medical Oncologists and Palliative Care Physicians

This study aimed to evaluate whether there are differences in the attitudes and practices of cancer pain manage-ment between medical oncologists and palliative care physicians. An online nationwide survey was used to collect responses from board-certified medical oncologists and palliative care physicians in Japan. The survey questionnaire comprised 30 questions. The differences in responses between medical oncologists and palliative care physicians were examined. Out of the 1,227 questionnaires sent, 522 (42.5%) were returned. After apply-ing the exclusion criteria, 445 questionnaires (medical oncologists: n = 283; palliative care physicians: n = 162) were retained for analysis. Among the questions about potential barriers to optimal cancer pain man-agement, both medical oncologists and palliative care physicians considered the reluctance of patients to take opioids due to fear of adverse effects as the greatest barrier. Significantly different ratings between medical oncologists and palliative care physicians were observed on 5 of the 8 questions in this area. Significantly differ-ent ratings were observed for all questions concerning pain specialists and their knowledge. For effective cancer pain management, it is important to account for differences in attitudes and practice between medical oncolo-gists and palliative care physicians

Gene Expression Profiling between Patient Groups with High and Low Ki67 Levels after Short-term Preoperative Aromatase Inhibitor Treatment for Breast Cancer

According to a recent report, a low Ki67 level after short-term preoperative hormone therapy (post-Ki67) might suggest a more favorable prognosis compared with a high post-Ki67 level in patients with hormone receptorpositive/human epidermal growth factor 2-negative (HR+/HER2−) breast cancer with high levels of Ki67. This study aimed to evaluate the pre-treatment genetic differences between these two patient groups. Forty-five luminal B-like patients were stratified into two groups, namely, a group with high (H→H) and one with low (H→L) Ki67 levels after short-term preoperative aromatase inhibitor (AI) treatment. We compared pre-treatmentgene expression profiles between the two groups. In gene level analysis, there was no significant difference between the two groups by the class comparison test. In pathway analysis, five metabolism-related gene sets were significantly upregulated in the H→L group (p≤0.05). In the search for novel targets, five genes (PARP, BRCA2, FLT4, CDK6, and PDCD1LG2) showed significantly higher expression in the H→H group (p≤0.05). Several metabolism-related pathways were associated with sensitivity to AI. In the future, it will be necessary to seek out new therapeutic strategies for the poor prognostic group with high post-Ki67

Neoadjuvant Chemotherapy with or without Concurrent Hormone Therapy in Estrogen Receptor-Positive Breast Cancer:NACED-Randomized Multicenter Phase II Trial

Although in the neoadjuvant setting for estrogen receptor (ER)-positive breast cancers, chemotherapy or hormone therapy alone does not result in satisfactory tumor response, it is unknown whether concurrent chemo-endocrine therapy is superior to chemotherapy alone in clinical outcomes. We conducted a randomized phase II trial to test the responses of ER-positive patients to concurrent administration of chemo-endocrine therapy in the neoadjuvant setting. Women with stage II-III, ER-positive, invasive breast cancer (n=28) received paclitaxel followed by fluorouracil, epirubicin, cyclophosphamide (T-FEC) and were randomized to receive concurrent chemo-endocrine therapy consisting of goserelin administered subcutaneously for premenopausal women or an aromatase inhibitor for postmenopausal women. The primary endpoint was the pathological complete response (pCR) rate after neoadjuvant therapy. Twenty-eight patients were randomized. There were no significant differences in pCR rate between the concurrent group (12.5%;2/16) and the chemotherapy alone group (8.3%;1/12). Tumor size after therapy was significantly reduced in the concurrent therapy group (p=0.035), but not in the chemotherapy-alone group (p=0.622). Neoadjuvant chemotherapy with concurrent hormone therapy provided no significant improvement in pCR rate in ER-positive breast cancers. These preliminary results should be followed up by further studies