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May 15, 2013 (Vol. 33, No. 10)

Cancer Diagnostics, Pushing the Boundaries

  • Molecular techniques and technologies to probe alterations in gene and protein expression that may contribute to the development, progression, prognosis, heterogeneity, therapeutic options, and drug-resistance of cancers and tumor types are an increasingly important part of the clinician’s diagnostic toolbox.

    Researchers and clinicians alike are relying on sequencing technology and genomic, proteomic, and metabolomic strategies to identify biomarkers with the potential for use in diagnostics, drug discovery and development, and patient stratification for clinical drug testing.

    Commenting on the recent AACR meeting, analysts from Mizuho Securities observed that molecular diagnostics are “clearly an essential part of oncology,” with “a lot of optimism around cancer genome sequencing, even if most attendees do not think it will replace existing diagnostics in the near future.” They report “significant need for better biomarkers and companion diagnostics,” with biomarkers and diagnostics “being used earlier in development, but still under-utilized.” Additionally, “genomics is clearly driving many aspects of oncology R&D,” the Mizuho analysts explained.

    Several presentations at the AACR meeting highlighted the application of molecular diagnostic tools in cancer R&D and product development for the oncology diagnostics market.

    Mirza Peljto and co-authors from Flagship Biosciences and Affymetrix/Panomics described a method for the quantitative in situ assessment of oncogene RNA and protein expression in human clinical tumor tissue for use in biomarker and diagnostics development. In breast cancer, the Her2 oncogene is amplified or overexpressed in about 30% of breast cancers, but the correlation between Her2 gene expression and protein expression in these tumors is not well understood.

    The researchers used chromogenic RNA in situ hybridization (CISH) and immunohistochemistry (IHC) to develop a quantitative image analysis-based assay in which the levels of Her2 protein and RNA can be compared in situ within tissue context. This approach allows for the measurement and correlation of Her2 RNA and membrane protein expression across an entire tissue section. “It improves diagnostic concordance by relying on an automated method and also improves confidence in interpretation by assessing every tumor cell across the whole slide,” said Peljto.

    The authors were able to distinguish high- from low-expressing biopsy samples using the CellMap™ algorithm to analyze the digital images produced, to differentiate tumor cells from the normal surrounding tissue, and to transform the images into cell and biomarker maps and quantify the levels of RNA and protein biomarkers.

    The authors reported 79% concordance between Her2 RNA and Her2 protein expression. The study results “suggest the potential use of RNA CISH in assessment of Her2 status in conjunction and/or parallel to IHC.” The authors drew the following conclusions: “We demonstrated practical feasibility of combined molecular and image analysis for analyzing clinical tumor samples. The inclusion of automated, whole-slide IHC and CISH interpretation for molecular assessment for companion diagnostics may help solve the long-standing problem of manual pathologist assessments and improve concordance with the inclusion of an RNA-based readout simultaneous to an IHC-based readout.”

  • Click Image To Enlarge +
    CellMap in action. [Flagship Biosciences]

    A visual representation of how CellMap distinguishes and quantifies Her2 membrane staining and Her2 RNA CISH in whole slides of clinical tissue TMAs: CellMap defines and quantifies membranes even with relatively high cytoplasmic background staining. (A) original IHC image; (B) CellMap algorithm- generated markup for IHC analysis (red colored membranes indicate cells with high expression of Her2 while orange colored membranes indicate medium levels of Her2 expression). Using algorithm-based imaging it is possible to quantify RNA CISH for Her2. CellMap identifies individual cells as well as dots containing Her2 RNA from CISH signals based on the size of individual dots as well as their signal intensity. (C) Original CISH image; (D) CellMap algorithm-generated markup image of CISH analysis. The cells are binned into high expressing (red; >7 dots), medium expressing (orange; 5–7 dots), low expressing (yellow; 3–5 dots), negative (blue; <3 dots).

  • DNA and Protein Biomarker Analysis

    Click Image To Enlarge +
    Multi-analyte diagnostic readout (MADR): The use of quantitative markers, such as protein markers, can result in very high sensitivity, but often low specificity (blue dotted line). The addition of binary DNA mutation markers that have very high specificity provide a boost in sensitivity, such that quantitative marker cutoffs can be adjusted to increase specificity (black dashed lines). [Predictive Biosciences]

    Predictive Biosciences has developed commercial cancer diagnostic tests based on its Clinical Intervention Determining Diagnostic (CIDD)™ approach. The CIDD method uses a multi-analyte diagnostic readout based on measures of both DNA and protein markers. The dual cutoffs allow for >90% assay sensitivity and specificity.

    At AACR, company representatives spoke about the detection of bladder cancer-associated mutations and epigenetic changes.

    Instead of yielding a positive/negative result, the approach enables the stratification of symptomatic populations into three groups based on the likelihood of cancer: high likelihood of cancer, which identifies candidates for maximum, accelerated therapeutic intervention; possibility of cancer, a middle group of patients who should receive the standard of care; and high likelihood to be disease-free, or patients that do not require further evaluation or treatment.

    “The addition of DNA biomarkers that have high specificity, to protein biomarker-based diagnostic testing, essentially shifts the DNA marker-positive samples to the high-risk group, targeting those patients for intervention,” said Cecilia Fernandez, director of applied science. “The increased sensitivity of the multi-analyte assay allows for a higher protein marker cutoff to be set and a larger proportion of patients to be characterized as disease-free based on urine testing, sparing them further evaluation and invasive tissue sampling.”

    This concept was also described by John Millholland from Predictive Biosciences. His presentation focused on research aimed at applying a next-gen, deep amplicon sequencing method that can achieve quantitative gene mutation detection when mutations are present at levels as low as 0.02% of the normal DNA, as might be the case if testing were performed using urine instead of a bladder tissue sample.

    The authors show that compared to qPCR, deep amplicon sequencing of the FGFR3 gene yielded significantly greater concordance in mutation detection in tissue vs. urine—90% concordance with sequencing vs. about 50% with qPCR. “The additional mutations detected in urine using deep sequencing vs. in tissue samples (15 of 19 urine samples vs. 11 of 19 urine samples with qPCR) suggest that urine might be more representative of the entire organ versus tissue sections that might have stochastic sampling of the tumor,” Millholland and his co-authors reported.

    When the researchers added a second set of bladder cancer-associated mutations to the assay, these in the TP53 gene—associated with invasive bladder cancer, as opposed to the link between FGFR3 mutations and noninvasive disease—assay performance improved. They reported no overlap between samples positive for FGFR3 and TP53 mutations. The mutations in the two genes complement each other in the assay, and the combinations increases the sensitivity of the assay. “By combining TP53 with our current FGFR3 assay, we can provide excellent detection of all stages and grades of bladder cancer,” said Anthony P. Shuber, CTO.


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