Recomendaciones para la optimización del uso de marcadores tumorales de utilización frecuente. Recomendación (2018) / Recommendations for the optimization of the use of frequently used tumor markers. Recommendation 2018

Este documento describe las causas de error más frecuentes en la medición de marcadores tumorales séricos proteicos en sus diferentes fases: preanalítica, analítica y postanalítica y recomendaciones para detectar y solventar problemas, así como la interpretación de los resultados de los marcadores tumorales en la práctica clínica

This document describes the most frequent causes of error in the measurement of 13 serum protein tumour markers in their different phases: preanalytical, analytical and 14 postanalytic and recommendations to detect and solve problems, as well as the 15 interpretation of the results of the Tumor Markers in clinical practice

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

International Interlaboratory Digital PCR Study Demonstrating High Reproducibility for the Measurement of a Rare Sequence Variant.

This study tested the claim that digital PCR (dPCR) can offer highly reproducible quantitative measurements in disparate laboratories. Twenty-one laboratories measured four blinded samples containing different quantities of a KRAS fragment encoding G12D, an important genetic marker for guiding therapy of certain cancers. This marker is challenging to quantify reproducibly using quantitative PCR (qPCR) or next generation sequencing (NGS) due to the presence of competing wild type sequences and the need for calibration. Using dPCR, 18 laboratories were able to quantify the G12D marker within 12% of each other in all samples. Three laboratories appeared to measure consistently outlying results; however, proper application of a follow-up analysis recommendation rectified their data. Our findings show that dPCR has demonstrable reproducibility across a large number of laboratories without calibration. This could enable the reproducible application of molecular stratification to guide therapy and, potentially, for molecular diagnostics.

Linking two immuno-suppressive molecules: indoleamine 2,3 dioxygenase can modify HLA-G cell-surface expression.

Nonclassical human leukocyte antigen (HLA) class I molecule HLA-G and indoleamine 2,3 dioxygenase (INDO) in humans and mice, respectively, have been shown to play crucial immunosuppressive roles in fetal-maternal tolerance. HLA-G inhibits natural killer and T cell function by high-affinity interaction with inhibitory receptors, and INDO acts by depleting the surrounding microenvironment of the essential amino acid tryptophan, thus inhibiting T cell proliferation. We investigated whether HLA-G expression and INDO function were linked. Working with antigen-presenting cell (APC) lines and monocytes, we found that functional inhibition of INDO by 1-methyl-tryptophan induced cell surface expression of HLA-G1 by HLA-G1-negative APCs that were originally cell-surface negative, and that in reverse, the functional boost of INDO by high concentrations of tryptophan induced a complete loss of HLA-G1 cell surface expression by APCs that were originally cell-surface HLA-G1-positive. This mechanism was shown to be posttranslational because HLA-G protein cell contents remained unaffected by the treatments used. Furthermore, HLA-G cell surface expression regulation by INDO seems to relate to INDO function, but not to tryptophan catabolism itself. Potential implications in fetal-maternal tolerance are discussed.