Genomic biomarkers in prostate cancer.

Prostate cancer is the most common non-cutaneous cancer among men in the United States. In the last decade there has been a rapid expansion in the field of biomarker assays for diagnosis, prognosis, and treatment prediction in prostate cancer. The evidence base for these assays is rapidly evolving. With several commercial assays available at each stage of the disease, deciding which genomic assays are appropriate for which patients can be nuanced for physicians. In an effort to help guide these decisions in clinical practice, we aim to give an update on the current status of the biomarker field of prostate cancer

Cancer biomarker development from basic science to clinical practice

The amount of published literature on biomarkers has exponentially increased over the last two decades. Cancer biomarkers are molecules that are either part of tumour cells or secreted by tumour cells. Biomarkers can be used for diagnosing cancer (tumour versus normal and differentiation of subtypes), prognosticating patients (progression free survival and overall survival) and predicting response to therapy. However, very few biomarkers are currently used in clinical practice compared to the unprecedented discovery rate. Some of the examples are: carcino-embryonic antigen (CEA) for colon cancer; prostate specific antigen (PSA) for prostate; and estrogen receptor (ER), progesterone receptor (PR) and HER2 for breast cancer. Cancer biomarkers passes through a series of phases before they are used in clinical practice. First phase in biomarker development is identification of biomarkers which involve discovery, demonstration and qualification. This is followed by validation phase, which includes verification, prioritisation and initial validation. More large-scale and outcome-oriented validation studies expedite the clinical translation of biomarkers by providing a strong ‘evidence base’. The final phase in biomarker development is the routine clinical use of biomarker. In summary, careful identification of biomarkers and then validation in well-designed retrospective and prospective studies is a systematic strategy for developing clinically useful biomarkers

Validation of a Multivariate Serum Profile for Epithelial Ovarian Cancer Using a Prospective Multi-Site Collection

In previous studies we described the use of a retrospective collection of ovarian cancer and benign disease samples, in combination with a large set of multiplexed immunoassays and a multivariate pattern recognition algorithm, to develop an 11-biomarker classification profile that is predictive for the presence of epithelial ovarian cancer. In this study, customized, Luminex-based multiplexed immunoassay kits were GMP-manufactured and the classification profile was refined from 11 to 8 biomarkers (CA-125, epidermal growth factor receptor, CA 19-9, C-reactive protein, tenascin C, apolipoprotein AI, apolipoprotein CIII, and myoglobin). The customized kits and the 8-biomarker profile were then validated in a double-blinded manner using prospective samples collected from women scheduled for surgery, with a gynecologic oncologist, for suspicion of having ovarian cancer. The performance observed in model development held in validation, demonstrating 81.1% sensitivity (95% CI 72.6 – 87.9%) for invasive epithelial ovarian cancer and 85.4% specificity (95% CI 81.1 – 88.9%) for benign ovarian conditions. The specificity for normal healthy women was 95.6% (95% CI 83.6 – 99.2%). These results have encouraged us to undertake a second validation study arm, currently in progress, to examine the performance of the 8-biomarker profile on the population of women not under the surgical care of a gynecologic oncologist

Engineering a Molecular Missile for Pancreatic Cancer Detection: Vector Design

Pancreatic cancer, though rare, is expected to be the second-leading cause of cancer-related death by 2030 (Rahib et al., 2014). CA 19-9 is currently the most widely used biomarker for pancreatic cancer detection, but detection of CA 19-9 relies on the use of monoclonal antibodies, a technology that entails an expensive, lengthy, and ethically problematic manufacturing process. This paper presents the design of a DNA vector that can be used to program E. coli to produce a “molecular missile” that targets CA 19-9. Through the site-specific incorporation of an unnatural amino acid (L-DOPA), this peptide can be engineered to bind to a pancreatic cancer biomarker with strength comparable to a monoclonal antibody. By targeting a sugar molecule, this synthetic antibody will expand the potential diagnostic and therapeutic applications of its cost-effective, stable, and ethical modular design

HE4 in the differential diagnosis of ovarian masses

Ovarian masses, a common finding among pre- and post-menopausal women, can be benign or malignant. Ovarian cancer is the leading cause of death from gynecologic malignancy among women living in industrialized countries. According to the current guidelines, measurement of CA125 tumor marker remains the gold standard in the management of ovarian cancer. Recently, HE4 has been proposed as emerging biomarker in the differential diagnosis of adnexal masses and in the early diagnosis of ovarian cancer. Discrimination of benign and malignant ovarian tumors is very important for correct patient referral to institutions specializing in care and management of ovarian cancer. Tumor markers CA125 and HE4 are currently incorporated into the Risk of Ovarian Malignancy Algorithm” (ROMA) with menopausal status for discerning malignant from benign pelvic masses. The availability of a good biomarker such as HE4, closely associated with the differential and early diagnosis of ovarian cancer, could reduce medical costs related to more expensive diagnostic procedures. Finally, it is important to note that HE4 identifies platinum non-responders thus enabling a switch to second line chemotherapy and improved survival

Integrative DNA methylome analysis of pan-cancer biomarkers in cancer discordant monozygotic twin-pairs

BACKGROUND: A key focus in cancer research is the discovery of biomarkers that accurately diagnose early lesions in non-invasive tissues. Several studies have identified malignancy-associated DNA methylation changes in blood, yet no general cancer biomarker has been identified to date. Here, we explore the potential of blood DNA methylation as a biomarker of pan-cancer (cancer of multiple different origins) in 41 female cancer discordant monozygotic (MZ) twin-pairs sampled before or after diagnosis using the Illumina HumanMethylation450 BeadChip. RESULTS: We analysed epigenome-wide DNA methylation profiles in 41 cancer discordant MZ twin-pairs with affected individuals diagnosed with tumours at different single primary sites: the breast, cervix, colon, endometrium, thyroid gland, skin (melanoma), ovary, and pancreas. No significant global differences in whole blood DNA methylation profiles were observed. Epigenome-wide analyses identified one novel pan-cancer differentially methylated position at false discovery rate (FDR) threshold of 10 % (cg02444695, P = 1.8 × 10(-7)) in an intergenic region 70 kb upstream of the SASH1 tumour suppressor gene, and three suggestive signals in COL11A2, AXL, and LINC00340. Replication of the four top-ranked signals in an independent sample of nine cancer-discordant MZ twin-pairs showed a similar direction of association at COL11A2, AXL, and LINC00340, and significantly greater methylation discordance at AXL compared to 480 healthy concordant MZ twin-pairs. The effects at cg02444695 (near SASH1), COL11A2, and LINC00340 were the most promising in biomarker potential because the DNA methylation differences were found to pre-exist in samples obtained prior to diagnosis and were limited to a 5-year period before diagnosis. Gene expression follow-up at the top-ranked signals in 283 healthy individuals showed correlation between blood methylation and gene expression in lymphoblastoid cell lines at PRL, and in the skin tissue at AXL. A significant enrichment of differential DNA methylation was observed in enhancer regions (P = 0.03). CONCLUSIONS: We identified DNA methylation signatures in blood associated with pan-cancer, at or near SASH1, COL11A2, AXL, and LINC00340. Three of these signals were present up to 5 years prior to cancer diagnosis, highlighting the potential clinical utility of whole blood DNA methylation analysis in cancer surveillance

Biomarker and Translational Prostate Cancer Research

The existing clinical biomarkers for prostate cancer (PCa) are not ideal, since they cannot specifically differentiate between those patients who should be treated immediately and those who should avoid overtreatment. Current screening techniques lack specificity, and a decisive diagnosis of PCa is based on prostate biopsy. Although PCa screening is widely utilized nowadays, two-thirds of the biopsies performed are still unnecessary. Thus, the discovery of noninvasive PCa biomarkers remains an urgent unmet medical need. Once metastasized, there is still no curative therapy. A better understanding of sustained androgen receptor signalling in castration resistant prostate cancer (CRPC) has now led to the development of more effective therapies. We need a better understanding of the molecular and cellular aspects of prostate carcinogenesis and progression. Identification of cancer initiating cells and therapies against these populations is a promising way forward to fight this disease

DMXL2 drives epithelial to mesenchymal transition in hormonal therapy resistant breast cancer through Notch hyper-activation

The acquisition of endocrine therapy resistance in estrogen receptor a (ERa) breast cancer patients represents a major clinical problem. Notch signalling has been extensively linked to breast cancer especially in patients who fail to respond to endocrine therapy. Following activation, Notch intracellular domain is released and enters the nucleus where activates transcription of target genes. The numerous steps that cascade after activation of the receptor complicate using Notch as biomarker. Hence, this warrants the development of reliable indicators of Notch activity. DMXL2 is a novel regulator of Notch signalling not yet investigated in breast cancer. Here, we demonstrate that DMXL2 is overexpressed in a subset of endocrine therapy resistant breast cancer cell lines where it promotes epithelial to mesenchymal transition through hyper-activation of Notch signalling via V-ATPase dependent acidification. Following DMXL2 depletion or treatment with Bafilomycin A1, both EMT targets and Notch signalling pathway significantly decrease. We show for the first time that DMXL2 protein levels are significantly increased in ERa positive breast cancer patients that progress after endocrine therapy. Finally, we demonstrate that DMXL2 is a transmembrane protein with a potential extra-cellular domain. These findings identify DMXL2 as a novel, functional biomarker for ERa positive breast cancer

Computational modelling of the behaviour of biomarker particles of colorectal cancer in fecal matter

Colorectal adenocarcinoma is one of the carcinogenic diseases that is increasing the morbidity and mortality rates worldwide. The disease initially occurs through the segregation of biomarker substances in the human system without manifesting symptoms that affect the health of the carrier. Early detection would allow the application of more effective treatments, less invasive procedures and reduce the development of cancer. The purpose of this investigation was the elaboration of a mathematical model and the development of computational simulations to visualize the behavior of biomarker particles in transit through the colon. The flow conditions, properties of the viscous medium and biological regions of interest were established. Constitutive models, numerical conditions and solution strategies were determined. A numerical grid was used to represent the model of the colon and the human feces that carry the bioparticles (biomarkers). The results indicated the trajectories of the bioparticles in the fecal mass and the interactive movement with the natural contractions of the colon. The analysis of the movement of the biomarker particles can provide future less invasive alternatives for the detection in real time of the cancer by means of the implantation of biosensors in the walls of the colon

Hierarchy of Gene Expression Data is Predictive of Future Breast Cancer Outcome

We calculate measures of hierarchy in gene and tissue networks of breast cancer patients. We find that the likelihood of metastasis in the future is correlated with increased values of network hierarchy for expression networks of cancer-associated genes, due to correlated expression of cancer-specific pathways. Conversely, future metastasis and quick relapse times are negatively correlated with values of network hierarchy in the expression network of all genes, due to dedifferentiation of gene pathways and circuits. These results suggest that hierarchy of gene expression may be useful as an additional biomarker for breast cancer prognosis.Comment: 14 pages, 5 figure