Establishing the Evidence Bar for Molecular Diagnostics in Personalised Cancer Care

Prognostic Value of Tumor Budding for Early Breast Cancer

BACKGROUND

Tumor budding (TB) is a dynamic process associated with the epithelial-mesenchymal transition and a well-established prognostic biomarker for colorectal cancer. As part of the tumor microenvironment, tumor buds demonstrate increased cell motility and invasiveness. Current evidence demonstrates that high levels of TB correlate with disease progression and worst outcomes across different solid tumors. Our work aims to demonstrate the clinical applicability of TB analysis and its utility as a prognostic factor for patients with early breast cancer (EBC).

METHODS

Retrospective, single-center, observational study, enrolling patients with EBC diagnosed in a Portuguese hospital between 2014 and 2015. TB classification was performed according to the International Tumor Budding Conference 2016 guidelines.

RESULTS

A statistically significant relation was found between higher TB score and aggressive clinicopathological features (angiolymphatic/perineural invasion-p < 0.001; tumor size-p = 0.012; nuclear grading-p < 0.001; and Ki-67 index-p = 0.011), higher number of relapses (p < 0.001), and short disease-free survival (DFS) (p < 0.001).

CONCLUSION

We demonstrate that high TB correlates with shorter DFS and aggressive clinicopathological features used in daily practice to decide on the benefit of chemotherapy for EBC. TB represents a needed prognostic biomarker for EBC, comprising a new factor to be considered in the adjuvant decision-making process by identifying patients at a high risk of relapse and with higher benefit on treatment intensification. Clinical trials incorporating TB are needed to validate its prognostic impact.

Comparative analysis of molecular signatures reveals a hybrid approach in breast cancer: Combining the Nottingham Prognostic Index with gene expressions into a hybrid signature

The diagnosis of breast cancer—including determination of prognosis and prediction—has been traditionally based on clinical and pathological characteristics such as tumor size, nodal status, and tumor grade. The decision-making process has been expanded by the recent introduction of molecular signatures. These signatures, however, have not reached the highest levels of evidence thus far. Yet they have been brought to clinical practice based on statistical significance in prospective as well as retrospective studies. Intriguingly, it has also been reported that most random sets of genes are significantly associated with disease outcome. These facts raise two highly relevant questions: What information gain do these signatures procure? How can one find a signature that is substantially better than a random set of genes? Our study addresses these questions. To address the latter question, we present a hybrid signature that joins the traditional approach with the molecular one by combining the Nottingham Prognostic Index with gene expressions in a data-driven fashion. To address the issue of information gain, we perform careful statistical analysis and comparison of the hybrid signature, gene expression lists of two commercially available tests as well as signatures selected at random, and introduce the Signature Skill Score—a simple measure to assess improvement on random signatures. Despite being based on in silico data, our research is designed to be useful for the decision-making process of oncologists and strongly supports association of random signatures with outcome. Although our study shows that none of these signatures can be considered as the main candidate for providing prognostic information, it also demonstrates that both the hybrid signature and the gene expression list of the OncotypeDx signature identify patients who may not require adjuvant chemotherapy. More importantly, we show that combining signatures substantially improves the identification of patients who do not need adjuvant chemotherapy.

Cancer Biomarkers in the era of precision oncology: Addressing the needs of patients and health systems

Cancer Biomarkers are the key to unlocking the promise of precision oncology, selecting which patients will respond to a more personalised treatment while sparing non-responders the therapy-related toxicity. In this paper, we highlight the primacy of cancer biomarkers, but focus on their importance to patients and to health systems. We also highlight how cancer biomarkers represent value for money. We emphasise the need for cancer biomarkers infrastructure to be embedded into European health systems. We also highlight the need to deploy multiple biomarker testing to deliver the optimal benefit for patients and health systems and consider cancer biomarkers from the perspective of cost, value and regulation. Cancer biomarkers must also be situated in the context of the upcoming In Vitro Diagnostics Regulation, which may pose certain challenges (e.g. non-compliance of laboratory developed tests, leading to cancer biomarker shortages and increased costs) that need to be overcome. Cancer biomarkers must be embedded in the real world of oncology delivery and testing must be implemented across Europe, with the intended aim of narrowing, not widening the inequity gap for patients. Cancer patients must be placed firmly at the centre of a cancer biomarker informed precision oncology care agenda.

Health economic impact of liquid biopsies in cancer management

INTRODUCTION

Liquid biopsies (LBs) are referred to as the sampling and analysis of non-solid tissue, primarily blood, as a diagnostic and monitoring tool for cancer. Because LBs are largely non-invasive, they are a less-costly alternative for serial analysis of tumor progression and heterogeneity to facilitate clinical management. Although a variety of tumor markers are proposed (e.g., free-circulating DNA), the clinical evidence for Circulating Tumor Cells (CTCs) is currently the most developed. Areas covered: This paper presents a health economic perspective of LBs in cancer management. We first briefly introduce the requirements in biomarker development and validation, illustrated for CTCs. Second, we discuss the state-of-art on the clinical utility of LBs in breast cancer in more detail. We conclude with a future perspective on the clinical use and reimbursement of LBs Expert commentary: A significant increase in clinical research on LBs can be observed and the results suggest a rapid change of cancer management. In addition to studies evaluating clinical utility of LBs, a smooth translation into clinical practice requires systematic assessment of the health economic benefits. This paper argues that (early stage) health economic research is required to facilitate its clinical use and to prioritize further evidence development.

Statistical controversies in clinical research: prognostic gene signatures are not (yet) useful in clinical practice

With the genomic revolution and the era of targeted therapy, prognostic and predictive gene signatures are becoming increasingly important in clinical research. They are expected to assist prognosis assessment and therapeutic decision making. Notwithstanding, an evidence-based approach is needed to bring gene signatures from the laboratory to clinical practice. In early breast cancer, multiple prognostic gene signatures are commercially available without having formally reached the highest levels of evidence-based criteria. We discuss specific concepts for developing and validating a prognostic signature and illustrate them with contemporary examples in breast cancer. When a prognostic signature has not been developed for predicting the magnitude of relative treatment benefit through an interaction effect, it may be wishful thinking to test its predictive value. We propose that new gene signatures be built specifically for predicting treatment effects for future patients and outline an approach for this using a cross-validation scheme in a standard phase III trial. Replication in an independent trial remains essential.

Immune-Derived PD-L1 Gene Expression Defines a Subgroup of Stage II/III Colorectal Cancer Patients with Favorable Prognosis Who May Be Harmed by Adjuvant Chemotherapy

A recent phase II study of patients with metastatic colorectal carcinoma showed that mismatch repair gene status was predictive of clinical response to PD-1-targeting immune checkpoint blockade. Further examination revealed strong correlation between PD-L1 protein expression and microsatellite instability (MSI) in stage IV colorectal carcinoma, suggesting that the amount of PD-L1 protein expression could identify late-stage patients who might benefit from immunotherapy. To assess whether the clinical associations between PD-L1 gene expression and MSI identified in metastatic colorectal carcinoma are also present in stage II/III colorectal carcinoma, we used in silico analysis to elucidate the cell types expressing the PD-L1 gene. We found a statistically significant association of PD-L1 gene expression with MSI in early-stage colorectal carcinoma (P < 0.001) and show that, unlike in non-colorectal carcinoma tumors, PD-L1 is derived predominantly from the immune infiltrate. We demonstrate that PD-L1 gene expression has positive prognostic value in the adjuvant disease setting (PD-L1(low) vs. PD-L1(high) HR = 9.09; CI, 2.11-39.10). PD-L1 gene expression had predictive value, as patients with high PD-L1 expression appear to be harmed by standard-of-care treatment (HR = 4.95; CI, 1.10-22.35). Building on the promising results from the metastatic colorectal carcinoma PD-1-targeting trial, we provide compelling evidence that patients with PD-L1(high)/MSI/immune(high) stage II/III colorectal carcinoma should not receive standard chemotherapy. This conclusion supports the rationale to clinically evaluate this patient subgroup for PD-1 blockade treatment. Cancer Immunol Res; 4(7); 582-91. ©2016 AACR.

Stratified analysis reveals chemokine-like factor (CKLF) as a potential prognostic marker in the MSI-immune consensus molecular subtype CMS1 of colorectal cancer

The Colorectal Cancer (CRC) Subtyping Consortium (CRCSC) recently published four consensus molecular subtypes (CMS's) representing the underlying biology in CRC. The Microsatellite Instable (MSI) immune group, CMS1, has a favorable prognosis in early stage disease, but paradoxically has the worst prognosis following relapse, suggesting the presence of factors enabling neoplastic cells to circumvent this immune response. To identify the genes influencing subsequent poor prognosis in CMS1, we analyzed this subtype, centered on risk of relapse. In a cohort of early stage colon cancer (n=460), we examined, in silico, changes in gene expression within the CMS1 subtype and demonstrated for the first time the favorable prognostic value of chemokine-like factor (CKLF) gene expression in the adjuvant disease setting [HR=0.18, CI=0.04-0.89]. In addition, using transcription profiles originating from cell sorted CRC tumors, we delineated the source of CKLF transcription within the colorectal tumor microenvironment to the leukocyte component of these tumors. Further to this, we confirmed that CKLF gene expression is confined to distinct immune subsets in whole blood samples and primary cell lines, highlighting CKLF as a potential immune cell-derived factor promoting tumor immune-surveillance of nascent neoplastic cells, particularly in CMS1 tumors. Building on the recently reported CRCSC data, we provide compelling evidence that leukocyte-infiltrate derived CKLF expression is a candidate biomarker of favorable prognosis, specifically in MSI-immune stage II/III disease.