Activation in transformed cells of normal stem cells’ self-renewal pathways might contribute to the survival life cycle of cancer stem cells and promote tumor progression. The BMI-1 oncogene–driven gene expression pathway is essential for the self-renewal of hematopoietic and neural stem cells. We applied a mouse/human comparative translational genomics approach to identify an 11-gene signature that consistently displays a stem cell–resembling expression profile in distant metastatic lesions as revealed by the analysis of metastases and primary tumors from a transgenic mouse model of prostate cancer and cancer patients. To further validate these results, we examined the prognostic power of the 11-gene signature in several independent therapy-outcome sets of clinical samples obtained from 1,153 cancer patients diagnosed with 11 different types of cancer, including 5 epithelial malignancies (prostate, breast, lung, ovarian, and bladder cancers) and 5 nonepithelial malignancies (lymphoma, mesothelioma, medulloblastoma, glioma, and acute myeloid leukemia). Kaplan-Meier analysis demonstrated that a stem cell–like expression profile of the 11-gene signature in primary tumors is a consistent powerful predictor of a short interval to disease recurrence, distant metastasis, and death after therapy in cancer patients diagnosed with 11 distinct types of cancer. These data suggest the presence of a conserved BMI-1–driven pathway, which is similarly engaged in both normal stem cells and a highly malignant subset of human cancers diagnosed in a wide range of organs and uniformly exhibiting a marked propensity toward metastatic dissemination as well as a high probability of unfavorable therapy outcome.

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Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple types of cancer

Purpose The incidence of prostate cancer is frequent, occurring in almost one-third of men older than 45 years. Only a fraction of the cases reach the stages displaying clinical significance. Despite the advances in our understanding of prostate carcinogenesis and disease progression, our knowledge of this disease is still fragmented. Identification of the genes and patterns of gene expression will provide a more cohesive picture of prostate cancer biology. Patients and Methods In this study, we performed a comprehensive gene expression analysis on 152 human samples including prostate cancer tissues, prostate tissues adjacent to tumor, and organ donor prostate tissues, obtained from men of various ages, using the Affymetrix (Santa Clara, CA) U95a, U95b, and U95c chip sets (37,777 genes and expression sequence tags). Results Our results confirm an alteration of gene expression in prostate cancer when comparing with nontumor adjacent prostate tissues. However, our study also indicates that the gene expressi...

https://ascopubs.org/doi/pdf/10.1200/JCO.2004.05.158

Gene Expression Alterations in Prostate Cancer Predicting Tumor Aggression and Preceding Development of Malignancy

Prostate cancer has the highest prevalence of any nonskin cancer in the human body, with similar likelihood of neoplastic foci found within the prostates of men around the world regardless of diet, occupation, lifestyle, or other factors. Essentially all men with circulating androgens will develop microscopic prostate cancer if they live long enough. This review is a contemporary and comprehensive, literature-based analysis of the putative risk factors for human prostate cancer, and the results were presented at a multidisciplinary consensus conference held in Crystal City, Virginia, in the fall of 2002. The objectives were to evaluate known environmental factors and mechanisms of prostatic carcinogenesis and to identify existing data gaps and future research needs. The review is divided into four sections, including 1) epidemiology (endogenous factors [family history, hormones, race, aging and oxidative stress] and exogenous factors [diet, environmental agents, occupation and other factors, including lifestyle factors]); 2) animal and cell culture models for prediction of human risk (rodent models, transgenic models, mouse reconstitution models, severe combined immunodeficiency syndrome mouse models, canine models, xenograft models, and cell culture models); 3) biomarkers in prostate cancer, most of which have been tested only as predictive factors for patient outcome after treatment rather than as risk factors; and 4) genotoxic and nongenotoxic mechanisms of carcinogenesis. The authors conclude that most of the data regarding risk relies, of necessity, on epidemiologic studies, but animal and cell culture models offer promise in confirming some important findings. The current understanding of biomarkers of disease and risk factors is limited. An understanding of the risk factors for prostate cancer has practical importance for public health research and policy, genetic and nutritional education and chemoprevention, and prevention strategies.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cncr.20408

Human prostate cancer risk factors.

One of the major problems in management of prostate cancer is the lack of reliable genetic markers predicting the clinical course of the disease We analyzed expression profiles of 12,625 transcripts in prostate tumors from patients with distinct clinical outcomes after therapy as well as metastatic human prostate cancer xenografts in nude mice We identified small clusters of genes discriminating recurrent versus nonrecurrent disease with 90% and 75% accuracy in two independent cohorts of patients We examined one group of samples (21 tumors) to discover the recurrence predictor genes and then validated the predictive power of these genes in a different set (79 tumors) Kaplan-Meier analysis demonstrated that recurrence predictor signatures are highly informative (P < 00001) in stratification of patients into subgroups with distinct relapse-free survival after therapy A gene expression-based recurrence predictor algorithm was informative in predicting the outcome in patients with early-stage disease, with either high or low preoperative prostate-specific antigen levels and provided additional value to the outcome prediction based on Gleason sum or multiparameter nomogram Overall, 88% of patients with recurrence of prostate cancer within 1 year after therapy were correctly classified into the poor-prognosis group The identified algorithm provides additional predictive value over conventional markers of outcome and appears suitable for stratification of prostate cancer patients at the time of diagnosis into subgroups with distinct survival probability after therapy

/pdf/gene-expression-profiling-predicts-clinical-outcome-of-19snhednr8.pdf

Gene expression profiling predicts clinical outcome of prostate cancer.

Measurement of gene-expression profiles using microarray technology is becoming increasingly popular among the biomedical research community. Although there has been great progress in this field, investigators are still confronted with a difficult question after completing their experiments: how to validate the large data sets that are generated? This review summarizes current approaches to verifying global expression results, discusses the caveats that must be considered, and describes some methods that are being developed to address outstanding problems.

Post-analysis follow-up and validation of microarray experiments

Molecular genetic profiling of Gleason grade 4/5 prostate cancers compared to benign prostatic hyperplasia.

Hepsin and maspin are inversely expressed in laser capture microdissectioned prostate cancer.

Many genes are affected in prostate cancers which have not been previously identified. This includes genes that have been up-regulated or down-regulated. Monitoring the expression levels of these genes is useful to identify the existence of prostate cancer. Also, monitoring the expression levels of these genes is useful to predict the effectiveness of treatment, outcome, use of therapeutics, and screening drugs useful for the treatment of prostate cancer.

Molecular genetic profiling of gleason grades 3 and 4/5 prostate cancer

Genetic Profiling of Gleason Grade 4/5 Prostate Cancer: Which is the Best Prostatic Control Tissue?

Hepatocellular carcinoma (HCC) is one of the common malignant tumors. However, the detection of biomarkers can't meet the clinical needs for the diagnosis and prognosis of HCC now. Circulating tumor DNA (ctDNA) is a highly tumor-specific DNA molecule that exists in the blood circulation. It is part of Circulating cell free DNA (cfDNA) and originates from the primary tumor or metastasis of cancer patients. Now, with the developing of next-generation sequencing technology and a full understanding of HCC genetics or epigenetic changes, we can analyze ctDNA mutations and methylation more comprehensively. Through continuous exploration of ctDNA mutations and methylation and continuous innovation of detection methods, HCC diagnosis and prognosis can be greatly improved in terms of specificity and sensitivity.

Zhenbin Fan

Papers

Molecular genetic profiling of Gleason grade 4/5 prostate cancers compared to benign prostatic hyperplasia.

Hepsin and maspin are inversely expressed in laser capture microdissectioned prostate cancer.

Molecular genetic profiling of gleason grades 3 and 4/5 prostate cancer

Genetic Profiling of Gleason Grade 4/5 Prostate Cancer: Which is the Best Prostatic Control Tissue?

[The role of circulating tumor DNA in the diagnosis and prognosis of hepatocellular carcinoma].