PubMed Health⌕ Search

Biomedical subjects

Lajos Pusztai

Publications and source records attributed to Lajos Pusztai.

At least 19 recordsLinked to original sources
PubMed2026

Pembrolizumab plus chemotherapy followed by pembrolizumab in participants in Asia with early triple-negative breast cancer: An updated subgroup analysis of the KEYNOTE-522 randomized clinical trial.

BACKGROUND: In KEYNOTE-522 (NCT03036488), addition of perioperative pembrolizumab to neoadjuvant chemotherapy significantly improved pathological complete response (pCR), event-free survival (EFS), and overall survival (OS) in early-stage triple-negative breast cancer (TNBC). pCR and EFS results in participants enrolled in Asia were consistent with those in the overall population. We report OS, updated EFS, and safety outcomes in participants enrolled in Asia. METHODS: Participants with newly diagnosed, high-risk, early-stage TNBC (T1c [N1‒N2] or T2‒T4 [N0‒N2] per AJCC 7th edition) were randomized 2:1 to 8 cycles of neoadjuvant pembrolizumab 200 mg Q3W or placebo plus chemotherapy. After definitive surgery, participants received adjuvant pembrolizumab 200 mg Q3W or placebo for ≤9 cycles. Primary endpoints were pCR (ypT0/Tis ypN0) and EFS. OS was a secondary endpoint. RESULTS: Of 1174 randomized participants, 216 were enrolled in Asia. At data cutoff (March 22, 2024), EFS events occurred in 18/136 participants (13.2%) in the pembrolizumab + chemotherapy group versus 22/80 (27.5%) in the placebo + chemotherapy group (HR, 0.43 [95% CI, 0.23‒0.81]); 60-month EFS rates (95% CIs) were 87.4% (80.6%‒92.0%) and 72.1% (60.7%‒80.6%), respectively. In the respective groups, 12/136 (8.8%) and 16/80 participants (20.0%) died (HR, 0.41 [95% CI, 0.19‒0.86]); 60-month OS rates (95% CIs) were 91.9% (85.8%‒95.4%) and 81.1% (70.5%‒88.1%). Treatment-related AEs led to treatment discontinuation in 19/136 participants (14.0%) with pembrolizumab + chemotherapy and 7/79 (8.9%) with placebo + chemotherapy. CONCLUSIONS: OS and updated EFS outcomes in KEYNOTE-522 participants enrolled in Asia were consistent with those in the overall population and support use of perioperative pembrolizumab + neoadjuvant chemotherapy as a standard-of-care treatment in this setting.

Adjuvant↗
PubMed2026

Development and Validation of a Multimodal Clinical, Pathologic, and Genomic Model for Breast Cancer Recurrence.

PURPOSE: To develop and validate a multimodal recurrence-risk model integrating histology, genomic testing, and clinical variables. METHODS: We developed AI-Path, a whole-slide image biomarker for recurrence prediction trained in CALGB 9344, and validated it in three independent cohorts: TAILORx, a multi-site Chicago cohort, and the MDX-BRCA cohort. We then integrated AI-Path with Oncotype DX Recurrence Score (RS), tumor size, and nodal status into a Cox model, PathClinRS, fit using 60% of cases from TAILORx, with the remaining 40% held out for validation. The primary end point was distant recurrence-free interval. Performance was assessed using Harrell's concordance index (C-index) and Kaplan-Meier analyses. RESULTS: A total of 12,418 patients were included. In TAILORx, AI-Path outperformed RS for distant recurrence (C-index, 0.682 vs 0.647; P = .038), driven by superior prediction of late recurrence (0.656 vs 0.567; P < .001). In node-negative disease, PathClinRS outperformed RSClin in the TAILORx fitting (0.72 vs 0.70; P = .016) and validation sets (0.74 vs 0.70; P = .004). In node-positive disease, PathClinRS outperformed RSClinN+ in Chicago (0.94 vs 0.74; P < .001) and MDX-BRCA (0.71 vs 0.66; P = .004) cohorts. Compared with NATALEE eligibility, PathClinRS identified nearly twice as many high-risk node-negative patients while maintaining a comparable 10-year distant recurrence risk (16.7% vs 16.6% per NATALEE eligibility in TAILORx fitting; 21.0% vs 19.4% in TAILORx validation). PathClinRS identified 68% of intermediate risk premenopausal patients as low-risk with no evidence of chemotherapy benefit, compared to only 36% identified as low risk by standard clinicopathologic criteria. CONCLUSION: Digital histopathology provides prognostic information complementary to genomic assays and has the potential to personalize therapy beyond existing clinicogenomic tools.

Journal Article↗
PubMed2026

Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study.

BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are a robust prognostic marker in patients with triple-negative breast cancer. Artificial intelligence (AI)-derived computational tools assessing TILs could improve efficiency, but require independent validation against clinical outcomes. We aimed to compare the prognostic performance of AI-derived TIL scores with pathologist-scored TILs in a large, prospectively collected dataset pooled from randomised controlled trials. METHODS: CATALINA was an independent, external validation study using prospectively collected long-term clinical outcome data pooled from seven randomised clinical trials conducted at multiple sites. We independently evaluated two previously validated AI pipelines that generate five computationally assessed tumour-infiltrating lymphocyte (cTIL) scores by masked, independent deployment of locked models. cTIL scores were correlated with the mean of the pathologist-scored stromal TILs (sTILs) in 220 digitised haematoxylin and eosin whole slide images in a cohort of patients with early-stage triple-negative or HER-2 positive breast cancer, previously scored by trained pathologists in a TIL-reproducibility study. Prognostic performance was assessed in a separate cohort of patients with early triple-negative breast cancer pooled from seven prospective, randomised adjuvant trials. Multivariable Cox regression models adjusted for clinicopathological factors and study heterogeneity assessed associations of cTIL score and sTIL score with invasive disease-free survival, distant disease-free survival, and overall survival. 5-year discrimination was estimated using time-dependent area under the receiver operating characteristic curve (AUC). FINDINGS: Individual data were collated from 1759 patients, of whom 1356 had complete clinicopathological data, pathologist sTIL scores, and cTIL scores available. Modest correlation (r 0&#xb7;375-0&#xb7;473) was observed between cTIL scores and the mean pathologist sTIL score. Both sTIL and cTIL were independently associated with 5-year invasive disease-free survival, distant disease-free survival, and overall survival after adjustment for clinicopathological factors (hazard ratio for invasive disease-free survival was 0&#xb7;73 [95% CI 0&#xb7;66-0&#xb7;82]; q<0&#xb7;0001, distant disease-free survival was 0&#xb7;70 [0&#xb7;61-0&#xb7;79]; q<0&#xb7;0001, and overall survival was 0&#xb7;72 [0&#xb7;63-0&#xb7;82]; q<0&#xb7;0001 for sTIL scores and 0&#xb7;80 [0&#xb7;73-0&#xb7;89]; q<0&#xb7;0001, 0&#xb7;77 [0&#xb7;69-0&#xb7;86]; q<0&#xb7;0001, and 0&#xb7;79 [0&#xb7;70-0&#xb7;88]; q=0&#xb7;0002, respectively, for percentage_lymphocyte scores). In models adjusted for clinicopathological variables and sTIL score, cTIL score did not maintain a statistically significant prognostic association. Both sTIL and cTIL scores improved the 5-year AUC over clinicopathological variables alone, while cTIL score did not significantly further improve AUC when combined with clinicopathological variables and sTIL score. INTERPRETATION: Two cTIL models deployed entirely without retraining or modification provided statistically significant prognostic information and improved risk discrimination compared with clinicopathological variables alone in this large, platform-based, independent validation study. Although cTIL score did not incrementally improve prognostication compared with models combining clinicopathological variables with sTIL score, these findings support the application of cTILs as a reproducible prognostic biomarker, particularly in settings where routine or widespread pathologist assessment is unavailable. FUNDING: Breast Cancer Research Foundation (USA).

Humans↗
PubMed2025

Integration of Gene Expression and Digital Histology to Predict Treatment-Specific Responses in Breast Cancer.

Deep learning models applied to digital histology can predict gene expression signatures (GES) and offer a low-cost, rapidly available alternative to molecular testing at the time of diagnosis. We optimized transformer-based models to infer GES results and applied this approach to pre-treatment H&E-stained biopsies from 1,940 breast cancer patients treated with neoadjuvant chemotherapy in clinical trial and real-world cohorts. The most predictive histology-derived GES for pathologic complete response (pCR) in the I-SPY2 trial was validated in four external cohorts: CALGB 40601, CALGB 40603, a trial of durvalumab plus CT, and standard-of-care CT-treated patients from the University of Chicago. Among HER2-negative patients, a transformer-based model trained using a signature composed of estrogen-regulated genes, proliferation, apoptosis, and interferon response genes predicted pCR with an AUC of 0.794, outperforming models based on clinical features alone (AUC 0.704, p = 0.001), pathologist TIL assessment, and a model trained directly to predict response from I-SPY2 cases. Tertiles of this signature stratify patients into clinically relevant groups with increasing likelihood of complete response, with pCR rates &#x2265;50% in the top tertile regardless of treatment or hormone receptor status. Additional transformer-based signature models predicted response to specific therapies (but not chemotherapy alone), including a HER2 signaling signature in IO-treated patients, and a claudin-low signature in bevacizumab treated patients. In HER2- cohorts with available gene expression data and histology, models trained on expression data performed similarly to digital histology predictions, but the combination of gene expression and histology outperformed histology alone. These findings suggest that histology-based GES provides additive information to RNA sequencing data and can inform precision treatment selection across breast cancer subtypes.

Journal Article↗
PubMed2025

Dynamic clustering of genomics cohorts beyond race, ethnicity-and ancestry.

BACKGROUND: Recent decades have witnessed a steady decrease in the use of race categories in genomic studies. While studies that still include race categories vary in goal and type, these categories already build on a history during which racial color lines have been enforced and adjusted in the service of social and political systems of power and disenfranchisement. For early modern classification systems, data collection was also considerably arbitrary and limited. Fixed, discrete classifications have limited the study of human genomic variation and disrupted widely spread genetic and phenotypic continuums across geographic scales. Relatedly, the use of broad and predefined classification schemes-e.g. continent-based-across traits can risk missing important trait-specific genomic signals. METHODS: To address these issues, we introduce a dynamic approach to clustering human genomics cohorts based on genomic variation in trait-specific loci and without using a set of predefined categories. We tested the approach on whole-exome sequencing datasets in ten cancer types and partitioned them based on germline variants in cancer-relevant genes that could confer cancer type-specific disease predisposition. RESULTS: Results demonstrate clustering patterns that transcend discrete continent-based categories across cancer types. Functional analysis based on cancer type-specific clusterings also captures the fundamental biological processes underlying cancer, differentiates between dynamic clusters on a functional level, and identifies novel potential drivers overlooked by a predefined continent-based clustering. CONCLUSIONS: Through a trait-based lens, the dynamic clustering approach reveals genomic patterns that transcend predefined classification categories. We propose that coupled with diverse data collection, new clustering approaches have the potential to draw a more complete portrait of genomic variation and to address, in parallel, technical and social aspects of its study.

Humans↗
PubMed2007

Kinetics of serum HER-2/neu changes in patients with HER-2-positive primary breast cancer after initiation of primary chemotherapy.

BACKGROUND: The purpose of the study was to determine the utility of quantitation of the extracellular domain (ECD) of the HER-2/neu receptor in the serum for predicting response to treatment in patients with primary breast cancer receiving neoadjuvant therapy. METHODS: HER-2/neu ECD was measured in sera obtained from 39 patients with HER-2-amplified stage II-III primary breast cancer undergoing neoadjuvant chemotherapy. Patients were randomly assigned to either 4 cycles of paclitaxel followed by 4 cycles of fluorouracil, epirubicin, and cyclophosphamide (FEC) (n = 10) or to the same chemotherapy with simultaneous weekly trastuzumab for 24 weeks (n = 29). Changes in HER-2 ECD were monitored with the Bayer HER-2/neu assay over 6 months and correlated with pathological response to treatment. RESULTS: Before initiation of chemotherapy, 28.2% of patients had elevated concentration of the HER-2 ECD (>15 ng/mL). The median baseline serum HER-2 ECD concentration was 13.6 ng/mL (mean +/- SD, 20.3 +/- 35.5 ng/mL). A decrease in the median HER-2 ECD levels from baseline to Week 3 and from baseline to Week 6 of chemotherapy was seen regardless of treatment regimen. No significant difference in baseline HER-2 ECD levels was observed between the groups who achieved pathological complete response (pCR) and the group with residual disease (P = .41). However, a 9% drop from Week 3 to Week 6 after initial chemotherapy was predictive of pCR (P = .04). CONCLUSION: A decrease in serum HER-2 ECD levels early during treatment was associated with pathological response in patients receiving primary chemotherapy, particularly trastuzumab-based regimens. Serum HER-2 ECD levels may serve to monitor neoadjuvant therapy in HER-2-positive primary breast cancer.

Adult↗
PubMed2007

Neoadjuvant therapy with paclitaxel followed by 5-fluorouracil, epirubicin, and cyclophosphamide chemotherapy and concurrent trastuzumab in human epidermal growth factor receptor 2-positive operable breast cancer: an update of the initial randomized study population and data of additional patients treated with the same regimen.

PURPOSE: Findings from our previously published phase III randomized trial showed a high pathologic complete remission (CR) rate in patients with human epidermal growth factor receptor 2-positive breast cancer after the concurrent administration of trastuzumab and paclitaxel, followed by concurrent trastuzumab and 5-fluorouracil, epirubicin, and cyclophosphamide (FEC) preoperative chemotherapy. The safety and efficacy data of initial population were updated, with inclusion of additional experience with the same therapy. STUDY DESIGN: The initial randomized study population of 42 patients were randomly assigned to either four cycles of paclitaxel followed by four cycles of FEC or to the same chemotherapy with simultaneous weekly trastuzumab for 24 weeks. All data were updated through November 2005. RESULTS: Pretreatment characteristics of the initial patients and of the second cohort were similar. In the second cohort, pathologic CR rate was 54.5% (95% confidence interval, 32.2-75.6%) and the pathologic CR rate among all patients treated with chemotherapy plus trastuzumab was 60% (95% confidence interval, 44.3-74.3%). Three patients in the chemotherapy only group have recurred, and one has died. There has been no recurrences in the patients randomized to chemotherapy plus trastuzumab, and the estimated disease-free survival at 1 and 3 years was 100% (P = 0.041). In additional cohort treated with chemotherapy and trastuzumab at the median follow-up of 16.3 months, no patients had recurred. No new safety concerns were observed in this study. CONCLUSION: Our expanded cardiac safety data and the updated efficacy data showed that the natural history of this subset of breast cancer patients can be substantially modified by this treatment approach.

Adult↗
PubMed2007

Primary systemic chemotherapy of invasive lobular carcinoma of the breast.

Invasive lobular carcinoma is the second most frequent histological type of breast cancer and its incidence is increasing. It has unique clinical, biological, and molecular features. Invasive lobular carcinoma is almost invariably positive for the oestrogen receptor and, when compared with invasive ductal carcinoma, it is typically of a lower grade. Even though invasive lobular carcinoma represents a distinct clinical entity, the same criteria used for invasive ductal carcinoma are currently applied to establish the need for primary or adjuvant systemic chemotherapy. We reviewed randomised trials of neoadjuvant and adjuvant chemotherapy and noted that insufficient evidence is available to support or withhold use of chemotherapy in patients with invasive lobular carcinoma. Thus, the benefit from systemic chemotherapy for individuals with this form of breast disease is unclear. Invasive lobular carcinoma deserves to be investigated separately in prospective clinical trials to define the best treatment and prevention strategies.

Antineoplastic Agents↗
PubMed2006

Development and validation of nomograms for predicting residual tumor size and the probability of successful conservative surgery with neoadjuvant chemotherapy for breast cancer.

BACKGROUND: Neoadjuvant chemotherapy (NACT) increases the likelihood that breast conservation therapy for breast cancer patients will be successful. There is no available nomogram to predict breast conservation after NACT. The aim of the current study was to develop and validate nomograms for predicting residual tumor size and probability of a patient becoming eligible for breast conservation surgery after NACT. METHODS: A total of 1147 patients treated at M. D. Anderson Cancer Center (Houston, TX) and the Institut Gustave Roussy (Villejuif, France) who received anthracycline with or without paclitaxel NACT were included in the analysis. Clinicopathologic data from 1 series were used to construct logistic regression models for breast conservation and residual tumor size < 3 cm after NACT and were validated on an independent series. RESULTS: The discrimination and the calibration of the nomogram for predicting the probability of residual tumor size < 3 cm after anthracycline-based NACT were good when applied to the validation set (concordance index = 0.79; U-index = 10(-3)). The discrimination of the nomogram for predicting eligibility for breast conservation therapy was also good (concordance index = 0.67). However, the calibration had to be adjusted to take into account global rates of breast conservation surgery. A second nomogram adapted to preoperative chemotherapy regimens containing paclitaxel was established. The concordance index of the nomogram for predicting breast conservation was 0.71 (P < 10(-6)) for the independent dataset and the calibration was also good. The confrontation of both nomograms showed that predictions were highly correlated (r = 0.97), suggesting that eligibility for breast conservation therapy was independent of the preoperative chemotherapy regimen used. CONCLUSIONS: Nomograms were developed for breast cancer patients who received NACT to predict residual tumor size and whether the patient would thus become eligible for breast conservation therapy. These tools may be useful when counseling patients about treatment options, and a web-based interface is now available to help guide patients and physicians in these decisions.

Anthracyclines↗
PubMed2006

Heterogeneity of breast cancer among patients and implications for patient selection for adjuvant chemotherapy.

Although the benefits of adjuvant chemotherapy are not controversial, the absolute effect of such therapy is small. Therefore, there is a need to identify biomarkers that can help select patients with localized breast cancer for treatment. Despite intense research in this field, no biomarker has been shown to be useful to predict benefit of adjuvant chemotherapy in daily practice. This can partially be explained by the fact that breast cancer is composed of several distinct subclasses, as shown by large-scale genomic analyses. In this review, we discuss why the current research approach based on a single biomarker is limited by the heterogeneity of cancer among patients. We then propose three solutions to improve the research strategies in this field: investigate one biomarker in a single homogeneous subclass to improve its predictive value; study the predictive value of multibiomarker assays in larger populations; and use functional pathways to predict the efficacy of a given drug.

Antineoplastic Agents↗
PubMed2006

DNA arrays as predictors of efficacy of adjuvant/neoadjuvant chemotherapy in breast cancer patients: current data and issues on study design.

Chemotherapy provides variable benefit to patients with breast cancer, with usually modest but occasionally severe side effects. Hence, there is a need to identify predictive biomarkers for its efficacy. DNA arrays have been used in this setting as potential novel predictive diagnostic tools. Several gene signatures and single gene markers were proposed to predict response to chemotherapy. Although this technology offers interesting perspectives through large-scale analysis of the transcriptome, its ability to identify clinically relevant predictors is highly dependent on study design. In the present manuscript, we will review currently available results of breast cancer pharmacogenomics and focus on aspects of study design that are critical to reliably identify predictive biomarkers using DNA array technology. We will discuss whether studies should be done in the overall, unselected breast cancer population or in specific homogeneous molecular subclasses. Next, we will compare advantages and limitations of cohort-based and case-control studies. The choice of end-point to discriminate between sensitive and resistant patients will also be examined.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2006

Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer.

PURPOSE: We developed a multigene predictor of pathologic complete response (pCR) to preoperative weekly paclitaxel and fluorouracil-doxorubicin-cyclophosphamide (T/FAC) chemotherapy and assessed its predictive accuracy on independent cases. PATIENTS AND METHODS: One hundred thirty-three patients with stage I-III breast cancer were included. Pretreatment gene expression profiling was performed with oligonecleotide microarrays on fine-needle aspiration specimens. We developed predictors of pCR from 82 cases and assessed accuracy on 51 independent cases. RESULTS: Overall pCR rate was 26% in both cohorts. In the training set, 56 probes were identified as differentially expressed between pCR versus residual disease, at a false discovery rate of 1%. We examined the performance of 780 distinct classifiers (set of genes + prediction algorithm) in full cross-validation. Many predictors performed equally well. A nominally best 30-probe set Diagonal Linear Discriminant Analysis classifier was selected for independent validation. It showed significantly higher sensitivity (92% v 61%) than a clinical predictor including age, grade, and estrogen receptor status. The negative predictive value (96% v 86%) and area under the curve (0.877 v 0.811) were nominally better but not statistically significant. The combination of genomic and clinical information yielded a predictor not significantly different from the genomic predictor alone. In 31 samples, RNA was hybridized in replicate with resulting predictions that were 97% concordant. CONCLUSION: A 30-probe set pharmacogenomic predictor predicted pCR to T/FAC chemotherapy with high sensitivity and negative predictive value. This test correctly identified all but one of the patients who achieved pCR (12 of 13 patients) and all but one of those who were predicted to have residual disease had residual cancer (27 of 28 patients).

Adult↗
PubMed2006

Reproducibility of gene expression signature-based predictions in replicate experiments.

PURPOSE: The goals of this analysis were to (a) determine concordance of gene expression results from replicate experiments, (b) examine prediction agreement of multigene predictors on replicate data, and (c) assess the robustness of prediction results in the face of noise. PATIENTS AND METHODS: Affymetrix U133A gene chips were used for gene expression profiling of 97 fine-needle aspiration biopsies from breast cancer. Thirty-five cases were profiled in replicates: 17 within the same laboratory, 11 in two different laboratories, and 15 to assess manual and robotic labeling. We used data from 62 cases to develop 111 distinct pharmacogenomic predictors of response to therapy. These were tested on cases profiled in duplicates to determine prediction agreement and accuracy. To evaluate the robustness of the pharmacogenomic predictors, we also introduced random noise into the informative genes in one half of the replicates. RESULTS: The average concordance correlation coefficient was 0.978 (range, 0.96-0.99) for intralaboratory replicates, 0.962 (range, 0.94-0.98) for between-laboratory replicates, and 0.971 (range, 0.93-0.99) for manual versus robotic labeling. The mean % prediction agreement on replicate data was 97% (95% CI, 0.96-0.98; SD, 0.006), 92% (95% CI, 0.90-0.93; SD, 0.009), and 94% (95% CI, 0.92-0.95; SD, 0.008) for support vector machines, diagonal linear discriminant analysis, and k-nearest neighbor prediction methods, respectively. Mean accuracy in the test set was 77% (95% CI, 0.74-0.79; SD, 0.014), 66% (95% CI, 0.63-0.73; SD, 0.015), and 64% (95% CI, 0.60-0.67; SD, 0.016), respectively. CONCLUSION: Gene expression results obtained with Affymetrix U133A chips are highly reproducible within and across two high-volume laboratories. Pharmacogenomic predictions yielded >90% agreement in replicate data.

Biopsy, Needle↗
PubMed2006

Impact of concurrent proliferative high-risk lesions on the risk of ipsilateral breast carcinoma recurrence and contralateral breast carcinoma development in patients with ductal carcinoma in situ treated with breast-conserving therapy.

BACKGROUND: The purpose of the study was to determine the risk of ipsilateral breast carcinoma recurrence (IBCR) and contralateral breast carcinoma (CBC) development in patients with a concurrent diagnosis of ductal carcinoma in situ (DCIS) with atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), or lobular carcinoma in situ (LCIS). METHODS: Records of all 307 patients with DCIS treated with breast-conserving treatment (BCT) from 1968 to 1998 were analyzed. Initial pathology reports and all slides available were re-reviewed for evidence of ADH, ALH, or LCIS. Actuarial local recurrence rates were calculated. RESULTS: Fifty-five cases of DCIS were associated with ADH, 11 with ALH or LCIS, and 14 with both ADH and ALH or LCIS. Overall, IBCR occurred in 14% and no significant difference in the IBCR rate was identified for patients with proliferative lesions compared with patients without these lesions (P = 0.38). Development of CBC in patients with concurrent DCIS and ADH was 4.4 times (95% confidence interval [CI], 1.44-13.63) that in patients with DCIS alone (P < 0.01). The 15-year cumulative rate of CBC development was 22.7% in patients with ALH or LCIS compared with 6.5% in patients without these lesions (P = 0.30) and 19% in patients with ADH compared with 4.1% in patients with DCIS alone (P < 0.01). CONCLUSION: The risk of CBC development is higher with concurrent ADH than in patients with DCIS alone, and these patients may therefore be appropriate candidates for additional chemoprevention strategies. Concurrent ADH, ALH, or LCIS with DCIS is not a contraindication to BCT.

Breast Neoplasms↗
PubMed2006

Molecular classification of breast cancer: implications for selection of adjuvant chemotherapy.

Adjuvant chemotherapy improves survival of patients with stage I-III breast cancer but it is being increasingly recognized that the benefit is not equal for all patients. Molecular characteristics of the cancer affect sensitivity to chemotherapy. In general, estrogen-receptor-negative disease is more sensitive to chemotherapy than estrogren-receptor-positive disease. Large-scale genomic analyses of breast cancer suggest that further molecular subsets may exist within the categories defined by hormone receptor status. It is hoped that the new molecular classification schemes might improve patient selection for therapy. Before any new molecular classification (or predictive test) is adopted for routine clinical use, however, several criteria need to be met. There must be an agreed and reproducible method by which to assign molecular class to a new case. Cancers that belong to different molecular classes must show differences in disease outcome and treatment efficacy that affect management and treatment selection. Also desirable are results from prospective clinical trials that demonstrate improved patient outcome when the new test is used in decision-making, compared with the current standard of care. This Review describes the current limitations and future promises of gene-expression-based molecular classification of breast cancer and how it might impact on selection of adjuvant therapy for individual patients.

Biomarkers, Tumor↗
PubMed2006

Continued use of trastuzumab (herceptin) after progression on prior trastuzumab therapy in HER-2-positive metastatic breast cancer.

Whether to continue trastuzumab after objective evidence of disease progression or not is an important unanswered clinical question for women with metastatic disease. This question is also relevant for those who relapse after adjuvant trastuzumab-containing therapy. Unfortunately, there is little evidence to guide decision-making. The modest toxicity and the possible, but unproven, benefit from the continued use of trastuzumab may account for the currently wide spread practice of continued administration of this drug after progression. However, there is no convincing evidence to support the use of extended trastuzumab therapy after progression. At least two randomized trials with no trastuzumab in the control arms were attempted but failed to accrue patients. In the absence of results from a randomized clinical trial, a central registry program that collects information longitudinally from a large number of patients with HER-2 positive breast cancer during the course of their disease was initiated (RegistHER, www.registher.com) to learn about the long term side effects and benefits of prolonged trastuzumab therapy. The anticipated introduction of second generation HER2-targeted agents into the clinic also raises a new question; will switching to these agents be more effective than continuation of trastuzumab? Clinical trials are currently planned to address question prospectively.

Antibodies, Monoclonal↗