Analytical Validation of an Immunohistochemical 7-Biomarker Prognostic Assay (immunoprint®) for Early-Stage Cutaneous Melanoma in Archival Tissue of Patients with AJCC v8 T2-T3 Disease.

Selected patients with early-stage melanoma have a "hidden high risk" of poor oncologic outcomes. They might benefit from clinical trials, and ultimately, if warranted by trial results, judicious everyday use of adjuvant therapy. A promising tool to identify these individuals is the immunoprint® assay. This immunohistochemical 7-biomarker prognostic test was clinically validated in three independent cohorts (N = 762) to classify early-stage patients as high-risk or low-risk regarding melanoma recurrence and mortality. Using College of American Pathologists (CAP) recommendations, we analytically validated this assay in primary melanoma specimens (N = 20 patients). We assessed assay precision by determining consistency of risk classification under repeated identical conditions (repeatability) or across varying conditions (reproducibility), involving separate assay runs, operators (laboratory scientists), and/or observers (e.g., dermatopathologists). Reference classification was followed by five analytical validation phases: intra-run/intra-operator, intra-observer, inter-run, inter-operator, and inter-observer. Concordance of classifications in each phase was assessed via Fleiss' kappa (primary endpoint) and percent agreement (secondary endpoint). Seven-marker signature classification demonstrated high consistency across validation categories (Fleiss' kappa 0.864-1.000; overall percent agreement 95-100%), in 9/10 cases, exceeding, and in 1/10 cases, closely approaching, CAP's recommended 0.9 level. The 7-marker assay has now been verified to provide excellent repeatability, reproducibility, and precision, besides having been clinically validated.

Protein expression of prognostic genes in primary melanoma and benign nevi.

PURPOSE: To evaluate the protein expression characteristics of genes employed in a recently introduced prognostic gene expression assay for patients with cutaneous melanoma (CM). METHODS: We studied 37 patients with CM and 10 with benign (melanocytic) nevi (BN). Immunohistochemistry of primary tumor tissue was performed for eight proteins: COL6A6, DCD, GBP4, KLHL41, KRT9, PIP, SCGB1D2, SCGB2A2. RESULTS: The protein expression of most markers investigated was relatively low (e.g., DCD, KRT9, SCGB1D2) and predominantly cytoplasmatic in melanocytes and keratinocytes. COL6A6, GBP4, and KLHL41 expression was significantly enhanced in CM when compared to BN. DCD protein expression was significantly correlated with COL6A6, GBP4, and KLHL41. GBP4 was positively correlated with KLHL41 and inversely correlated with SCGB2B2. The latter was also inversely correlated with serum S100B levels at time of initial diagnosis. The presence of SCGB1D2 expression was significantly associated with ulceration of the primary tumor. KRT9 protein expression was significantly more likely found in acral lentiginous melanoma. The presence of DCD expression was less likely associated with superficial spreading melanoma subtype but significantly associated with non-progressive disease. The absence of SCGB2A2 expression was significantly more often observed in patients who did not progress to stage III or IV. CONCLUSIONS: The expression levels observed were relatively low but differed in part with those found in BN. Even though we detected some significant correlations between the protein expression levels and clinical parameters (e.g., CM subtype, course of disease), there was no major concordance with the protective or risk-associated functions of the corresponding genes included in a recently introduced prognostic gene expression assay.

Comparison of the Prognostic Utility of the Cell Cycle Progression Score for Predicting Clinical Outcomes in African American and Non-African American Men with Localized Prostate Cancer.

BACKGROUND: Better prostate cancer risk stratification is necessary to inform medical management, especially for African American (AA) men, for whom outcomes are particularly uncertain. OBJECTIVE: To evaluate the utility of both a cell cycle progression (CCP) score and a clinical cell-cycle risk (CCR) score to predict clinical outcomes in a large cohort of men with prostate cancer highly enriched in an AA patient population. DESIGN, SETTING, AND PARTICIPANTS: Patients were diagnosed with clinically localized adenocarcinoma of the prostate and treated at The Ochsner Clinic (New Orleans, LA, USA) from January 2006 to December 2011. CCP scores were derived from archival formalin-fixed, paraffin-embedded biopsy tissue. CCR scores were calculated as the combination of molecular (CCP score) and clinical (Cancer of the Prostate Risk Assessment [CAPRA] score) components. INTERVENTION: Active treatment (radical prostatectomy, radiation therapy alone, or radiation and hormone therapy) or watchful waiting. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was progression to metastatic disease. Association with outcomes was evaluated via Cox proportional hazards survival analysis and likelihood ratio tests. RESULTS AND LIMITATIONS: The final cohort included 767 men, of whom 281 (36.6%) were AA. After accounting for ancestry, treatment, and CAPRA in multivariable analysis, the CCP score remained a significant predictor of metastatic disease (hazard ratio [HR] 2.04; p<0.001), and there was no interaction with ancestry (p=0.20) or treatment (p=0.09). The CCR score was highly prognostic (HR 3.86; p<0.001), and as with the CCP score, there was no interaction with ancestry (p=0.24) or treatment (p=0.32). Limitations include the retrospective study design and the use of self-reported ancestry information. CONCLUSIONS: A CCR score provided significant prognostic information regardless of ancestry. The findings demonstrate that AA men in this study cohort appear to have similar prostate cancer outcomes to non-AA patients after accounting for all available molecular and clinicopathologic variables. PATIENT SUMMARY: In this study we evaluated the ability of a combined molecular and clinical score to predict the progression of localized prostate cancer. We found that the combined molecular and clinical score predicted progression to metastasis regardless of patient ancestry or treatment. This suggests that the combined molecular and clinical score may be a valuable tool for determining the risk of metastasis in men with newly diagnosed prostate cancer in order to make appropriate treatment decisions.

Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

Quantitative assessment of a prognostic or predictive biomarker panel.

Methods for assessing whether a single biomarker is prognostic or predictive in the context of a control and experimental treatment are well known. With a panel of biomarkers, each component biomarker potentially measuring sensitivity to a different drug, it is not obvious how to extend these methods. We consider two situations, which lead to different ways of defining whether a biomarker panel is prognostic or predictive. In one, there are multiple experimental targeted treatments, each with an associated biomarker assay of the relevant target in the panel, along with a control treatment; the extension of the single-biomarker scenario to this situation is straightforward. In the other situation, there are many (nontargeted) treatments and a single assay that can be used to assess the sensitivity of the patient's tumor to the different treatments. In addition to evaluating previous approaches to this situation, we propose using regression models with varying assumptions to assess such panel biomarkers. Missing biomarker data can be problematic with the regression models, and, after demonstrating that a multiple imputation procedure does not work, we suggest a modified regression model that can accommodate some forms of missing data. We also address the notions of qualitative interactions in the biomarker panel setting.