Metabolic classification of non-small cell lung cancer patient-derived xenografts by a digital pathology approach: A pilot study.

Introduction: Genetically characterized patient-derived tumor xenografts (PDX) are a valuable resource to understand the biological complexity of cancer and to investigate new therapeutic approaches. Previous studies, however, lack information about metabolic features of PDXs, which may limit testing of metabolism targeting drugs.

Methods: In this pilot study, we investigated by immunohistochemistry (IHC) expression of five essential metabolism-associated markers in a set of lung adenocarcinoma PDX samples previously established and characterized.

Quantification of Tumor and Angiogenesis-Related Markers in Ovarian Cancer Models by a Digital Pathology Approach.

Digital pathology has the potential to quantify tumor markers accurately and reproducibly with various cellular and subcellular localizations in tissues, thus filling a need in cancer research. As a case study, we quantified the percentage of necrosis, microvessels density, and monocarboxylate transporter 4 (MCT4) expression in two ovarian cancer patient-derived xenograft (PDX) models subcutaneously injected in NOD/SCID mice. PDX models were treated with bevacizumab, an antiangiogenic drug, that targets vascular endothelial growth factor A (VEGF-A).

Metabolic Profiling of Ovarian Cancer Tumor Xenografts: A Digital Pathology Approach.

Metabolic profiling of cancer is a rising interest in the field of biomarker development. One bottleneck of its clinical exploitation, however, is the lack of simple and quantitative techniques that enable to capture the key metabolic traits of tumor from archival samples. In fact, liquid chromatography associated with mass spectrometry is the gold-standard technique for the study of tumor metabolism because it has high levels of accuracy and precision.

Gene Copy Number and Mutant Allele Frequency Correlate with Time to Progression in Metastatic Melanoma Patients Treated with MAPK Inhibitors.

Metastatic melanoma is characterized by complex genomic alterations, including a high rate of mutations in driver genes and widespread deletions and amplifications encompassing various chromosome regions. Among them, chromosome 7 is frequently gained in -mutant melanoma, inducing a mutant allele-specific imbalance. Although amplification is a known mechanism of acquired resistance to therapy with MAPK inhibitors, it is still unclear if copy-number variation and mutant allele imbalance at baseline can be associated with response to treatment.