Publications by authors named "Salunga R"

Purpose: Patients with early-stage hormone receptor-positive (HR+) breast cancer face a prolonged risk of recurrence even after adjuvant endocrine therapy. The Breast Cancer Index (BCI) is significantly prognostic for overall (0-10 years) and late (5-10 years) distant recurrence (DR) risk in N0 and N1 patients. Here, BCI prognostic performance was evaluated in HR+ postmenopausal women from the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial.

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Background: Multiple clinical trials demonstrate consistent but modest benefit of adjuvant extended endocrine therapy (EET) in HR + breast cancer patients. Predictive biomarkers to identify patients that benefit from EET are critical to balance modest reductions in risk against potential side effects of EET. This study compares the performance of the Breast Cancer Index, BCI (HOXB13/IL17BR, H/I), with expression of estrogen (ER), progesterone (PR), and androgen receptors (AR), and Ki67, for prediction of EET benefit.

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Article Synopsis
  • * In a study of 2,445 patients, those with a high BCI (H/I) ratio showed significant improvement in recurrence-free interval with extended tamoxifen, while those with low ratios did not.
  • * The analysis revealed that BCI (H/I) serves as a crucial biomarker for determining treatment effectiveness, specifically for HR+ patients who are lymph node-positive and HER2-negative.
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Background: Extending the duration of adjuvant endocrine therapy reduces the risk of recurrence in a subset of women with early-stage hormone receptor-positive (HR+) breast cancer. Validated predictive biomarkers of endocrine response could significantly improve patient selection for extended therapy. Breast cancer index (BCI) [HOXB13/IL17BR ratio (H/I)] was evaluated for its ability to predict benefit from extended endocrine therapy in patients previously randomized in the Adjuvant Tamoxifen-To Offer More? (aTTom) trial.

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Molecular studies are part of standard care for cancer patients. Bone, a common and sometimes sole site of metastasis, requires decalcification for morphological examination. Many commonly used decalcification agents contain strong acids that degrade nucleic acids.

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The accurate determination of the risk of cancer recurrence is an important unmet need in the management of prostate cancer. Patients and physicians must weigh the benefits of currently available therapies against the potential morbidity of these treatments. Herein we describe the development of a gene expression-based continuous risk index and a validation of this test in an independent, blinded cohort of post-radical prostatectomy (RP) patients.

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Accurate determination of cancer origin is necessary to guide optimal treatment but remains a diagnostic challenge. Gene expression profiling technologies have aided the classification of tumors and, therefore, could be applied in conjunction with clinicopathologic correlates to improve accuracy. We report an expanded version of the previously described 92-gene assay to classify 30 main tumor types and 54 histological subtypes, with coverage of ≥95% of all solid tumors based on incidence.

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Background: A dichotomous index combining two gene expression assays, HOXB13:IL17BR (H:I) and molecular grade index (MGI), was developed to assess risk of recurrence in breast cancer patients. The study objective was to demonstrate the prognostic utility of the combined index in early-stage breast cancer.

Methods: In a blinded retrospective analysis of 588 ER-positive tamoxifen-treated and untreated breast cancer patients from the randomised prospective Stockholm trial, H:I and MGI were measured using real-time RT-PCR.

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Purpose: Histologic tumor grade is a well-established prognostic factor for breast cancer, and tumor grade-associated genes are the common denominator of many prognostic gene signatures. The objectives of this study are as follows: (a) to develop a simple gene expression index for tumor grade (molecular grade index or MGI), and (b) to determine whether MGI and our previously described HOXB13:IL17BR index together provide improved prognostic information.

Experimental Design: From our previously published list of genes whose expression correlates with both tumor grade and tumor stage progression, we selected five cell cycle-related genes to build MGI and evaluated MGI in two publicly available microarray data sets totaling 410 patients.

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Context: Correct diagnosis of the tissue origin of a metastatic cancer is the first step in disease management, but it is frequently difficult using standard pathologic methods. Microarray-based gene expression profiling has shown great promise as a new tool to address this challenge.

Objective: Adoption of microarray technologies in the clinic remains limited.

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Tamoxifen significantly reduces tumor recurrence in certain patients with early-stage estrogen receptor-positive breast cancer, but markers predictive of treatment failure have not been identified. Here, we generated gene expression profiles of hormone receptor-positive primary breast cancers in a set of 60 patients treated with adjuvant tamoxifen monotherapy. An expression signature predictive of disease-free survival was reduced to a two-gene ratio, HOXB13 versus IL17BR, which outperformed existing biomarkers.

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Laser capture microdissection in combination with microarrays allows for the expression analysis of thousands of genes in selected cells. Here we describe single-cell gene expression profiling of CA1 neurons in the rat hippocampus using a combination of laser capture, T7 RNA amplification, and cDNA microarray analysis. Subsequent cluster analysis of the microarray data identified two different cell types: pyramidal neurons and an interneuron.

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Although distinct pathological stages of breast cancer have been described, the molecular differences among these stages are largely unknown. Here, through the combined use of laser capture microdissection and DNA microarrays, we have generated in situ gene expression profiles of the premalignant, preinvasive, and invasive stages of human breast cancer. Our data reveal extensive similarities at the transcriptome level among the distinct stages of progression and suggest that gene expression alterations conferring the potential for invasive growth are already present in the preinvasive stages.

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Information on the neuroanatomical expression of a given gene is critical to understanding its function in the central nervous system. The integration of laser capture microdissection (LCM), T7-based RNA amplification and cDNA microarrays allows for this information to be simultaneously generated for thousands of genes. To validate this integrative approach, we catalogued the gene expression profiles of seven rat brain nuclei or subnuclei.

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