Digital genomic quantification of tumor-infiltrating lymphocytes. 2013

Harlan S Robins, and Nolan G Ericson, and Jamie Guenthoer, and Kathy C O'Briant, and Muneesh Tewari, and Charles W Drescher, and Jason H Bielas
Herbold Computational Biology Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.

Infiltrating T lymphocytes are frequently found in malignant tumors and are suggestive of a host cancer immune response. Multiple independent studies have documented that the presence and quantity of tumor-infiltrating lymphocytes (TILs) are strongly correlated with increased survival. However, because of methodological factors, the exact effect of TILs on prognosis has remained enigmatic, and inclusion of TILs in standard prognostic panels has been limited. For example, some reports enumerate all CD3(+) cells, some count only cytotoxic CD8(+) T cells, and the criteria used to score tumors as TIL-positive or TIL-negative are inconsistent among studies. To address this limitation, we introduce a robust digital DNA-based assay, termed QuanTILfy, to count TILs and assess T cell clonality in tissue samples, including tumors. We demonstrate the clonal specificity of this approach by the diagnosis of T cell acute lymphoblastic leukemia and the accurate, sensitive, and highly reproducible measurement of TILs in primary and metastatic ovarian cancer. Our experiments demonstrate an association between higher TIL counts and improved survival among women with ovarian cancer, and are consistent with previous observations that the immune response against ovarian cancer is a meaningful and independent prognostic factor. Surprisingly, the TIL repertoire is diverse for all tumors in the study with no notable oligoclonal expansions. Furthermore, because variability in the measurement and characterization of TILs has limited their clinical utility as biomarkers, these results highlight the significant translational potential of a robust, standardizable DNA-based assay to assess TILs in a variety of cancer types.

UI MeSH Term Description Entries
D007111 Immunity, Cellular Manifestations of the immune response which are mediated by antigen-sensitized T-lymphocytes via lymphokines or direct cytotoxicity. This takes place in the absence of circulating antibody or where antibody plays a subordinate role. Cell-Mediated Immunity,Cellular Immune Response,Cell Mediated Immunity,Cell-Mediated Immunities,Cellular Immune Responses,Cellular Immunities,Cellular Immunity,Immune Response, Cellular,Immune Responses, Cellular,Immunities, Cell-Mediated,Immunities, Cellular,Immunity, Cell-Mediated,Response, Cellular Immune
D010051 Ovarian Neoplasms Tumors or cancer of the OVARY. These neoplasms can be benign or malignant. They are classified according to the tissue of origin, such as the surface EPITHELIUM, the stromal endocrine cells, and the totipotent GERM CELLS. Cancer of Ovary,Ovarian Cancer,Cancer of the Ovary,Neoplasms, Ovarian,Ovary Cancer,Ovary Neoplasms,Cancer, Ovarian,Cancer, Ovary,Cancers, Ovarian,Cancers, Ovary,Neoplasm, Ovarian,Neoplasm, Ovary,Neoplasms, Ovary,Ovarian Cancers,Ovarian Neoplasm,Ovary Cancers,Ovary Neoplasm
D011237 Predictive Value of Tests In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test. Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D011379 Prognosis A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations. Prognostic Factor,Prognostic Factors,Factor, Prognostic,Factors, Prognostic,Prognoses
D002999 Clone Cells A group of genetically identical cells all descended from a single common ancestral cell by mitosis in eukaryotes or by binary fission in prokaryotes. Clone cells also include populations of recombinant DNA molecules all carrying the same inserted sequence. (From King & Stansfield, Dictionary of Genetics, 4th ed) Clones,Cell, Clone,Cells, Clone,Clone,Clone Cell
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D014408 Biomarkers, Tumor Molecular products metabolized and secreted by neoplastic tissue and characterized biochemically in cells or BODY FLUIDS. They are indicators of tumor stage and grade as well as useful for monitoring responses to treatment and predicting recurrence. Many chemical groups are represented including HORMONES; ANTIGENS; amino and NUCLEIC ACIDS; ENZYMES; POLYAMINES; and specific CELL MEMBRANE PROTEINS and LIPIDS. Biochemical Tumor Marker,Cancer Biomarker,Carcinogen Markers,Markers, Tumor,Metabolite Markers, Neoplasm,Tumor Biomarker,Tumor Marker,Tumor Markers, Biochemical,Tumor Markers, Biological,Biochemical Tumor Markers,Biological Tumor Marker,Biological Tumor Markers,Biomarkers, Cancer,Marker, Biochemical Tumor,Marker, Biologic Tumor,Marker, Biological Tumor,Marker, Neoplasm Metabolite,Marker, Tumor Metabolite,Markers, Biochemical Tumor,Markers, Biological Tumor,Markers, Neoplasm Metabolite,Markers, Tumor Metabolite,Metabolite Markers, Tumor,Neoplasm Metabolite Markers,Tumor Markers, Biologic,Tumor Metabolite Marker,Biologic Tumor Marker,Biologic Tumor Markers,Biomarker, Cancer,Biomarker, Tumor,Cancer Biomarkers,Marker, Tumor,Markers, Biologic Tumor,Markers, Carcinogen,Metabolite Marker, Neoplasm,Metabolite Marker, Tumor,Neoplasm Metabolite Marker,Tumor Biomarkers,Tumor Marker, Biochemical,Tumor Marker, Biologic,Tumor Marker, Biological,Tumor Markers,Tumor Metabolite Markers
D015972 Gene Expression Regulation, Neoplastic Any of the processes by which nuclear, cytoplasmic, or intercellular factors influence the differential control of gene action in neoplastic tissue. Neoplastic Gene Expression Regulation,Regulation of Gene Expression, Neoplastic,Regulation, Gene Expression, Neoplastic
D016019 Survival Analysis A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function. Analysis, Survival,Analyses, Survival,Survival Analyses

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