From gene to clinic: TMA-based clinical validation of molecular markers in prostate cancer

Annexin A3, a Calcium-Dependent Phospholipid-Binding Protein: Implication in Cancer

Annexin A3 (ANXA3), also known as lipocortin III and placental anticoagulant protein III, has been reported to be dysregulated in tumor tissues and cancer cell lines, and harbors pronounced diagnostic and prognostic value for certain malignancies, such as breast, prostate, colorectal, lung and liver cancer. Aberrant expression of ANXA3 promotes tumor cell proliferation, invasion, metastasis, angiogenesis, and therapy resistance to multiple chemotherapeutic drugs including platinum-based agents, fluoropyrimidines, cyclophosphamide, doxorubicin, and docetaxel. Genetic alterations on the ANXA3 gene have also been reported to be associated with the propensity to form certain inherited, familial tumors. These diverse functions of ANXA3 in tumors collectively indicate that ANXA3 may serve as an attractive target for novel anticancer therapies and a powerful diagnostic and prognostic biomarker for early tumor detection and population risk screening. In this review, we dissect the role of ANXA3 in cancer in detail.

Emerging proteomics biomarkers and prostate cancer burden in Africa

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

CD57 expression in incidental, clinically manifest, and metastatic carcinoma of the prostate

OBJECTIVES

CD57 is normally found on NK-cells, but little is known about its expression in prostatic tissue.

METHODS

We investigated CD57 expression by immunohistochemistry using tissue microarrays containing 3262 prostate cancers (PCa), lymph node metastases, and benign prostatic tissue. The results were compared with clinical and pathological parameters.

RESULTS

Overall, 87% of PCa showed a moderate or strong expression of CD57. There was no significant difference to corresponding benign prostatic tissue. CD57 was increasingly lost from incidental over clinically manifest cancers to metastases. It correlated significantly with Gleason grade and pT-category, but not with PSA tissue expression. Loss of CD57 expression was an independent risk factor for PSA recurrence after prostatectomy in a multivariate Cox regression analysis. In standard sections, CD57 expression was heterogeneous, especially in large, high-grade PCa.

CONCLUSIONS

There is a peculiar expression of CD57 in PCa and benign prostatic tissue. CD57 loss is associated with tumor dedifferentiation and tumor size. However, the use of this marker for prognostic purposes is hampered by its heterogeneous expression.

Tissue microarrays: leaping the gap between research and clinical adoption

The use of tissue microarrays (TMAs) in the preclinical and translational research settings has become ubiquitous as they allow for high-throughput in situ biomarker analysis of hundreds of patient samples, with time and cost efficiency. Coupled with advanced imaging and image-analysis technologies that allow for objective and standardized biomarker expression assessment, TMAs have become critical tools for the development and validation of clinically meaningful biomarker diagnostic assays. However, their diagnostic use in the clinical laboratory setting is limited due to the need for conventional whole-section tissue assessment used for routine diagnostic purposes. In this article, after reviewing TMA basics and their translational and clinical research applications, we will focus on the use of TMAs for robust assay development and quality control in the clinical laboratory setting, as well as provide insights into how TMAs may serve well in the clinical setting as assay performance and quantification controls.

An alternative high output tissue microarray technique

Background

Tissue microarray (TMA) is a high throughput research tool, which has greatly facilitated and accelerated in situ tissue analyses. However, its productivity has been restricted due to the confined thickness of traditional donor block. Here, we introduce an improved high output TMA method that is applicable to a broader range of tissue samples.

Methods

In this method, a 3.6 cm long and 2.7 cm wide recipient block with 88 square lattices (3 mm in width) was first prepared using several commercial instruments. A 2 mm wide and 6 mm long tissue rod was then prepared using a self-made blade-shaped knife from each paraffin embedded donor block of gastrointestinal stromal tumors. These rods were manually arrayed one by one into the corresponding lattices of the 60°C pre-softened recipient block with the guide of holes drilled with a steel needle. A 70-rod TMA was made to testify this method.

Results

The prepared TMA had well defined array configurations, good tissue morphology and fully preserved proteins and DNA. A total of 500–1000 TMA sections could be easily obtained from a TMA block.

Conclusion

This low-cost and time-saving method provides an alternative sampling tool for high output TMA.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1979605867857990

Computational oncology

Oncology research has traditionally been conducted using techniques from the biological sciences. The new field of computational oncology has forged a new relationship between the physical sciences and oncology to further advance research. By applying physics and mathematics to oncologic problems, new insights will emerge into the pathogenesis and treatment of malignancies. One major area of investigation in computational oncology centers around the acquisition and analysis of data, using improved computing hardware and software. Large databases of cellular pathways are being analyzed to understand the interrelationship among complex biological processes. Computer-aided detection is being applied to the analysis of routine imaging data including mammography and chest imaging to improve the accuracy and detection rate for population screening. The second major area of investigation uses computers to construct sophisticated mathematical models of individual cancer cells as well as larger systems using partial differential equations. These models are further refined with clinically available information to more accurately reflect living systems. One of the major obstacles in the partnership between physical scientists and the oncology community is communications. Standard ways to convey information must be developed. Future progress in computational oncology will depend on close collaboration between clinicians and investigators to further the understanding of cancer using these new approaches.