Biomarker discovery for colon cancer using a 761 gene RT-PCR assay

<p>Abstract</p> <p>Background</p> <p>Reverse transcription PCR (RT-PCR) is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan^®RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE) clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco <it>type</it>DX™ assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis) and the likelihood of tumor response to standard chemotherapy regimens (prediction). We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application.</p> <p>Results</p> <p>RNA was extracted from formalin fixed paraffin embedded (FPE) tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan^®reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery.</p> <p>Conclusion</p> <p>We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of genes analyzed while maintaining the high specificity, sensitivity and reproducibility that are characteristics of RT-PCR. Biomarkers discovered using this approach can be transferred to a clinical reference laboratory setting without having to re-validate the assay on a second technology platform.</p

Gene‐level dissection of chromosome 3q locus amplification in squamous cell carcinoma of the lung using the nCounter assay

Abstract Background Amplification of the 3q region has been identified as a useful biomarker for the diagnosis and treatment of squamous cell carcinoma (SqCC). This region contains genes such as PIK3CA and YEATS2, which have been linked to the prognosis of SqCC. Methods The NanoString nCounter assay is a powerful tool for identifying genetic alterations that affect the progression and prognosis of SqCC. The NanoString nCounter assay was used to identify a subgroup of patients with gene level gain in the 3q region. Results Gene level gain in the 3q region was more frequent in SqCC than in adenocarcinoma. We found that genes such as PIK3CA and YEATS2 in the 3q region were associated with the prognosis of SqCC. Therefore, identifying a subgroup of patients with gene level gain in the 3q region using the NanoString nCounter assay can aid in selecting appropriate treatment options and improving prognostic predictions for SqCC patients. Conclusion Amplification of the 3q region in SqCC of lung cancer is a useful biomarker for diagnosis and treatment. The NanoString nCounter assay is a powerful tool for identifying specific genetic alterations that affect the progression and prognosis of SqCC. Our study highlights the importance 3q amplification and its associated genes in lung cancer

Adrenal Collision Tumor: Coexistence of Pigmented Adrenal Cortical Oncocytoma and Ganglioneuroma

Background. Adrenal collision tumors (ACTs), in which distinct tumors coexist without intermingling in the same adrenal gland, are rare and their actual prevalence is unknown. ACTs commonly consist of adrenal cortical adenoma, pheochromocytoma, or metastatic malignant tumor. Case Report. A 32-year-old woman who had been experiencing gastric discomfort for one month was referred to our hospital with abnormal imaging findings. The physical examination and the laboratory data including endocrine studies were unremarkable. Abdomen computed tomography (CT) and magnetic resonance imaging (MRI) showed two adjacent masses in the left suprarenal fossa, and a laparoscopic left adrenalectomy was done. Histological and immunohistochemical (IHC) examinations revealed two distinct tumors: a pigmented adrenal cortical oncocytoma (ACO) and a ganglioneuroma, respectively. Conclusion. Both tumors are rare in the adrenal gland and exist as ACTs only exceptionally rarely. This is the first reported case of coexisting oncocytoma and ganglioneuroma in the same adrenal gland to our knowledge

MurSS: A Multi-Resolution Selective Segmentation Model for Breast Cancer

Accurately segmenting cancer lesions is essential for effective personalized treatment and enhanced patient outcomes. We propose a multi-resolution selective segmentation (MurSS) model to accurately segment breast cancer lesions from hematoxylin and eosin (H&E) stained whole-slide images (WSIs). We used The Cancer Genome Atlas breast invasive carcinoma (BRCA) public dataset for training and validation. We used the Korea University Medical Center, Guro Hospital, BRCA dataset for the final test evaluation. MurSS utilizes both low- and high-resolution patches to leverage multi-resolution features using adaptive instance normalization. This enhances segmentation performance while employing a selective segmentation method to automatically reject ambiguous tissue regions, ensuring stable training. MurSS rejects 5% of WSI regions and achieves a pixel-level accuracy of 96.88% (95% confidence interval (CI): 95.97–97.62%) and mean Intersection over Union of 0.7283 (95% CI: 0.6865–0.7640). In our study, MurSS exhibits superior performance over other deep learning models, showcasing its ability to reject ambiguous areas identified by expert annotations while using multi-resolution inputs

Cytoplasmic Estrogen Receptor in Breast Cancer

Purpose: In addition to genomic signaling, it is accepted that estrogen receptor-alpha (ER alpha) has nonnuclear signaling functions, which correlate with tamoxifen resistance in preclinical models. However, evidence for cytoplasmic ER localization in human breast tumors is less established. We sought to determine the presence and implications of nonnuclear ER in clinical specimens. Experimental Design: A panel of ER alpha-specific antibodies (SP1, MC20, F10, 60c, and 1D5) was validated by Western blot and quantitative immunofluorescent (QIF) analysis of cell lines and patient controls. Then eight retrospective cohorts collected on tissue microarrays were assessed for cytoplasmic ER. Four cohorts were from Yale (YTMA 49, 107, 130, and 128) and four others (NCI YTMA 99, South Swedish Breast Cancer Group SBII, NSABP B14, and a Vietnamese Cohort) from other sites around the world. Results: Four of the antibodies specifically recognized ER by Western and QIF analysis, showed linear increases in amounts of ER in cell line series with progressively increasing ER, and the antibodies were reproducible on YTMA 49 with Pearson correlations (r(2) values) ranging from 0.87 to 0.94. One antibody with striking cytoplasmic staining (MC20) failed validation. We found evidence for specific cytoplasmic staining with the other four antibodies across eight cohorts. The average incidence was 1.5%, ranging from 0 to 3.2%. Conclusions: Our data show ER alpha is present in the cytoplasm in a number of cases using multiple antibodies while reinforcing the importance of antibody validation. In nearly 3,200 cases, cytoplasmic ER is present at very low incidence, suggesting its measurement is unlikely to be of routine clinical value. Clin Cancer Res; 18(1); 118-26. (C) 2011 AACR