MTA1 drives malignant progression and bone metastasis in prostate cancer.

Prostate cancer often metastasizes to the bone, leading to morbidity and mortality. While metastasis-associated protein 1 (MTA1) is highly overexpressed in metastatic tumors and bone metastatic lesions, its exact role in the development of metastasis is unknown. Here, we report the role of MTA1 in prostate cancer progression and bone metastasis in vitro and in vivo. We found that MTA1 silencing diminished formation of bone metastases and impaired tumor growth in intracardiac and subcutaneous prostate cancer xenografts, respectively. This was attributed to reduced colony formation, invasion, and migration capabilities of MTA1 knockdown cells. Mechanistic studies revealed that MTA1 silencing led to a significant decrease in the expression of cathepsin B (CTSB), a cysteine protease critical for bone metastasis, with an expected increase in the levels of E-cadherin in both cells and xenograft tumors. Moreover, meta-analysis of clinical samples indicated a positive correlation between MTA1 and CTSB. Together, these results demonstrate the critical role of MTA1 as an upstream regulator of CTSB-mediated events associated with cell invasiveness and raise the possibility that targeting MTA1/CTSB signaling in the tumor may prevent the development of bone metastasis in prostate cancer.

Prediction of lung cancer histological types by RT-qPCR gene expression in FFPE specimens.

Lung cancer histologic diagnosis is clinically relevant because there are histology-specific treatment indications and contraindications. Histologic diagnosis can be challenging owing to tumor characteristics, and it has been shown to have less-than-ideal agreement among pathologists reviewing the same specimens. Microarray profiling studies using frozen specimens have shown that histologies exhibit different gene expression trends; however, frozen specimens are not amenable to routine clinical application. Herein, we developed a gene expression-based predictor of lung cancer histology for FFPE specimens, which are routinely available in clinical settings. Genes predictive of lung cancer histologies were derived from published cohorts that had been profiled by microarrays. Expression of these genes was measured by quantitative RT-PCR (RT-qPCR) in a cohort of patients with FFPE lung cancer. A histology expression predictor (HEP) was developed using RT-qPCR expression data for adenocarcinoma, carcinoid, small cell carcinoma, and squamous cell carcinoma. In cross-validation, the HEP exhibited mean accuracy of 84% and κ = 0.77. In separate independent validation sets, the HEP was compared with pathologist diagnoses on the same tumor block specimens, and the HEP yielded similar accuracy and precision as the pathologists. The HEP also exhibited good performance in specimens with low tumor cellularity. Therefore, RT-qPCR gene expression from FFPE specimens can be effectively used to predict lung cancer histology.