Evaluation of Tumor Development Using Hemoglobin Saturation Profile on Rodent Dorsal Window Chamber.

Tumor development can be indirectly evaluated using features of the tumor microenvironment (TME), such as hemoglobin saturation (HbSat), blood vessel dilation, and formation of new vessels. High values of HbSat and other features of the TME could indicate high metabolic activity and could precede the formation of angiogenic tumors; therefore, changes in HbSat profile can be used as a biomarker for tumor progression. One methodology to evaluate HbSat profile over time, and correlate it with tumor development in vivo in a preclinical model, is through a dorsal skin-fold window chamber. In this chapter, we provide a detailed description of this methodology to evaluate hemoglobin saturation profile and to predict tumor development. We will cover the surgical preparation of the mouse, the installation/maintenance of the dorsal window chamber, and the imaging processing and evaluation to the HbSat profile to predict new development of new tumor areas over time. We included, in this chapter, step by step examples of the imaging processing method to obtain pixel level HbSat values from raw pixels data, the computational method to determine the HbSat profile, and the steps for the classification of the areas into tumor and no-tumor.

Circulating Tumor DNA Assays in Clinical Cancer Research.

The importance of circulating free DNA (cfDNA) in cancer clinical research was recognized in 1994 when a mutated RAS gene fragment was detected in a patient's blood sample. Up to 1% of the total circulating DNA in patients with cancer is circulating tumor DNA (ctDNA) that originates from tumor cells. As ctDNA is rapidly cleared from the blood stream and can be obtained by minimally invasive methods, it can be used as a dynamic cancer biomarker for cancer early detection, diagnosis, and treatment monitoring. Despite the potential for clinical use, few ctDNA assays have been cleared or approved by the US Food and Drug Administration. As tools for clinical and translational research, current ctDNA assays face some challenges, and more research is needed to advance use of these assays. On September 29-30, 2016, the Division of Cancer Treatment and Diagnosis at the National Cancer Institute convened a workshop entitled "Circulating Tumor DNA Assays in Clinical Cancer Research" to garner input from industry experts, academia, and government research and regulatory agencies to understand and promote the translation of ctDNA assays to clinical research, with potential to advance to use in clinical practice. This Commentary presents the topics of the workshop covered in the presentations and points made in the discussions that followed: 1) background on ctDNA, 2) potential clinical utility of ctDNA assays, 3) assay technology, 4) assay clinical and analytical validation, and 5) industry perspectives. Additional relevant information that has come to light since the workshop has been included.

The Role of Affordable, Point-of-Care Technologies for Cancer Care in Low- and Middle-Income Countries: A Review and Commentary.

As the burden of non-communicable diseases such as cancer continues to rise in low- and middle-income countries (LMICs), it is essential to identify and invest in promising solutions for cancer control and treatment. Point-of-care technologies (POCTs) have played critical roles in curbing infectious disease epidemics in both high- and low-income settings, and their successes can serve as a model for transforming cancer care in LMICs, where access to traditional clinical resources is often limited. The versatility, cost-effectiveness, and simplicity of POCTs warrant attention for their potential to revolutionize cancer detection, diagnosis, and treatment. This paper reviews the landscape of affordable POCTs for cancer care in LMICs with a focus on imaging tools, in vitro diagnostics, and treatment technologies and aspires to encourage innovation and further investment in this space.

The National Institutes of Health Affordable Cancer Technologies Program: Improving Access to Resource-Appropriate Technologies for Cancer Detection, Diagnosis, Monitoring, and Treatment in Low- and Middle-Income Countries.

Point-of-care (POC) technologies have proved valuable in cancer detection, diagnosis, monitoring, and treatment in the developed world, and have shown promise in low-and-middle-income countries (LMIC) as well. Despite this promise, the unique design constraints presented in low-resource settings, coupled with the variety of country-specific regulatory and institutional dynamics, have made it difficult for investigators to translate successful POC cancer interventions to the LMIC markets. In response to this need, the National Cancer Institute has partnered with the National Institute of Biomedical Imaging and Bioengineering to create the National Institutes of Health Affordable Cancer Technologies (ACTs) program. This program seeks to simplify the pathway to market by funding multidisciplinary investigative teams to adapt and validate the existing technologies for cancer detection, diagnosis, and treatment in LMIC settings. The various projects under ACTs range from microfluidic cancer diagnostic tools to novel treatment devices, each geared for successful clinical adaptation to LMIC settings. Via progression through this program, each POC innovation will be uniquely leveraged for successful clinical translation to LMICs in a way not before seen in this arena.

Forecasting new development of tumor areas using spatial and temporal distribution profiles of hemoglobin saturation in a mouse model.

Features of the tumor microenvironment (TME), such as hemoglobin saturation (HbSat), can provide valuable information on early development and progression of tumors. HbSat correlates with high metabolism and precedes the formation of angiogenic tumors; therefore, changes in HbSat profile can be used as a biomarker for early cancer detection. In this project, we develop a methodology to evaluate HbSat for forecasting early tumor development in a mouse model. We built a delta ([Formula: see text]) cumulative feature that includes spatial and temporal distribution of HbSat for classifying tumor/normal areas. Using a two-class (normal and tumor) logistic regression, the [Formula: see text] feature successfully forecasts tumor areas in two window chamber mice ([Formula: see text] and 0.85). To assess the performance of the logistic regression-based classifier utilizing the [Formula: see text] feature of each region, we conduct a 10-fold cross-validation analysis (AUC of the [Formula: see text]). These results show that the TME features based on HbSat can be used to evaluate tumor progression and forecast new occurrences of tumor areas.