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Purpose: In spite of improvements of average benefit from adjuvant/neoadjuvant treatments, there are still individual patients with early breast cancer at high risk of relapse. We explored the association with outcome of robust gene cluster–based metagenes linked to proliferation, ER-related genes, and immune response to identify those high-risk patients. Experimental Design: A total of 3,847 publicly available gene-expression profiles were analyzed (untreated, N = 826; tamoxifen-treated, N = 685; chemotherapy-treated, N = 1,150). Genes poorly performing in formalin-fixed samples were removed. Outcomes of interest were pathologic-complete response (pCR) and distant metastasis-free survival (DMFS). In ER+HER2−, the proliferation and ER-related metagenes were combined to define three risk groups. In HER2+ and ER−HER2− risk groups were defined by tertiles of an immune-related metagene. Results: The high-proliferation/low-ER group of ER+HER2− breast cancer had significantly higher pCR rate [OR, 5.01 (1.76–17.99), P = 0.005], but poorer outcome [HR = 3.73 (1.63–8.51), P = 0.0018] than the low-proliferation/high-ER. A similar association with outcome applied to patients with residual disease (RD) after neoadjuvant chemotherapy (P = 0.01). In ER−HER2− and HER2+ breast cancer, immune metagene in the high tertile was linked to higher pCR [33.7% vs. 11.6% in high and low tertile, respectively; OR, 3.87 (1.79–8.95); P = 0.0009]. In ER−HER2−, after adjuvant/neoadjuvant chemotherapy, 5-year DMFS was 85.4% for high-tertile immune metagene, and 43.9% for low tertile. The outcome association was similar in patients with RD (P = 0.0055). In HER2+ breast cancer treated with chemotherapy the association with risk of relapse was not significant. Conclusions: We developed metagene-based predictors able to define low and high risk of relapse after adjuvant/neoadjuvant therapy. High-risk patients so defined should be preferably considered for trials with investigational agents. Clin Cancer Res; 22(2); 337–45. ©2015 AACR.

Purpose: The basaloid carcinoma (pure) and the (mixed) basaloid variant of lung squamous cell carcinoma (SCC) have a dismal prognosis but their underlying specific molecular characteristics remain obscure and no therapy has proven to be efficient. Experimental Design: To assess their molecular specificity among other lung SCCs we analyzed DNA copy number aberrations and mRNA expression pangenomic profiles of 93 SCCs, including 42 basaloid samples (24 pure, 18 mixed). Results: Supervised analyses reveal that pure basaloid tumors display a specific mRNA expression profile, encoding factors controlling the cell cycle, transcription, chromatin, and splicing, with prevalent expression in germline and stem cells, while genes related to squamous differentiation are underexpressed. From this signature, we derived a 2-genes (SOX4, IVL) immunohistochemistry-based predictor that discriminated basaloid tumors (pure and mixed) from non-basaloid tumors with 94% accuracy in an independent series. The pure basaloid tumors are also distinguished through unsupervised analyses. Using a centroid-based predictor, the corresponding molecular subtype was found in 8 independent public datasets (n = 58/533), and was shown to be associated with a very poor survival as compared with other SCCs (adjusted HR = 2.45; P = 0.000001). Conclusion: This study enlightens the heterogeneity of SCCs that can be subclassified in mRNA expression subtypes. This study demonstrates for the first time that basaloid SCCs constitute a distinct histomolecular entity, which justifies its recognition and distinction from non-basaloid SCCs. In addition, their characteristic molecular profile highlights their intrinsic resistance to cytotoxic chemotherapy and could serve as a guide for targeted therapies. Clin Cancer Res; 20(22); 5777–86. ©2014 AACR.

Purpose: Despite research efforts to develop more effective diagnostic and therapeutic approaches, malignant pleural mesothelioma (MPM) prognosis remains poor. The assessment of tumor response to therapy can be improved by a deeper phenotypical classification of the tumor, with emphasis on its clinico-biological heterogeneity. The identification of molecular profiles is a powerful approach to better define MPM subclasses and targeted therapies. Experimental Design: Molecular subclasses were defined by transcriptomic microarray on 38 primary MPM cultures. A three-gene predictor, identified by quantitative reverse transcription PCR, was used to classify an independent series of 108 frozen tumor samples. Gene mutations were determined in BAP1, CDKN2A, CDKN2B, NF2, and TP53. Epithelial-to-mesenchymal transition (EMT) markers were studied at the mRNA and protein levels. Results: Unsupervised hierarchical clustering on transcriptomic data defined two robust MPM subgroups (C1 and C2), closely related to prognosis and partly to histologic subtypes. All sarcomatoid/desmoplastic MPM were included in the C2 subgroup. Epithelioid MPM were found in both subgroups, with a worse survival prognosis in the C2 subgroup. This classification and its association with histologic subtypes and survival were validated in our independent series using the three-gene predictor. Similar subgroups were found after classification of other MPM series from transcriptomic public datasets. C1 subgroup exhibited more frequent BAP1 alterations. Pathway analysis revealed that EMT was differentially regulated between MPM subgroups. C2 subgroup is characterized by a mesenchymal phenotype. Conclusions: A robust classification of MPM that defines two subgroups of epithelioid MPM, characterized by different molecular profiles, gene alterations, and survival outcomes, was established. Clin Cancer Res; 20(5); 1323–34. ©2014 AACR.