Methods for predicting risk of heart transplant rejection are disclosed.

The present invention relates to the prediction of responsiveness to cancer immunotherapy of a subject based on the T-cell composition of the subject, and a therapeutic method using cancer immunotherapy based on the prediction. The present invention also provides a method for improving or maintaining responsiveness to cancer immunotherapy of a subject. Responsiveness to cancer immunotherapy is predict by determining a relative value of a CD4.sup.+ T-cell subpopulation, dendritic cell subpopulation, and/or CD8.sup.+ T-cell subpopulation correlated with a dendritic cell stimulation in an anti-tumor immune response in a sample derived from a subject. A composition for treating or preventing cancer comprising cells such as CD62L.sup.lowCD4.sup.+ T-cells is also provided.

Disclosed are synthetic nanocarrier compositions, and related methods, comprising MHC Class II-restricted epitopes and immunosuppressants that provide tolerogenic immune responses, such as a reduction in CD4+ T cell help specific to an antigen.

The present invention provides methods of classifying cluster of differentiation (CD) marker phenotype for hematopoietic cancer cells using multiple circulating cell-free CD markers in bodily fluid. In other aspects, treatment and disease progression of particular hematopoietic cancers can be monitored by measuring the levels of CD and other markers in bodily fluids of a patient.

The invention provides methods of isolating CD127.sup.lo/− immunosuppressive regulatory T cells which can be greatly enriched for FoxP3, methods of expanding the isolated cells, pharmaceutical compositions of such cells, and methods of their use in the treatment of autoimmune and other immune system mediated disorders.

A method for the detection of impaired responsiveness of CD4+ T-cells to regulatory T-cells (Treg), Treg resistance, by measuring the expression levels of peroxisome proliferator-activated receptor gamma coactivator 1-alpha, PPARGC1A (PGC-1α) in activated CD4+ T-cells, in particular in patients suffering from relapsing remitting multiple sclerosis. The invention relates to an in vitro screening method for the detection of an autoimmune disease or a condition, comprising the steps of generating a functional gene expression profile by measuring the expression levels of peroxisome proliferator-activated receptor gamma coactivator 1-alpha, PPARGC1A (PGC-1α) in Treg-resistant CD4+ T-cells from patients suffering of an autoimmune disease or condition, and comparing the obtained gene expression profile with the expression profile from Treg-sensitive CD4+ T-cells from healthy controls. PCG-1α or an upstream regulator of Treg-resistant T-cells HNF4A, Hdac, RORA, ESRRA, LPIN1 can be used in a screening system for the detection of impaired responsiveness of CD4+ T-cells to Treg.

The present disclosure relates in some aspects to methods, cells, and compositions for preparing cells and compositions for genetic engineering and cell therapy. Provided in some embodiments are streamlined cell preparation methods, e.g., for isolation, processing, incubation, and genetic engineering of cells and populations of cells. Also provided are cells and compositions produced by the methods and methods of their use. The cells can include immune cells, such as T cells, and generally include a plurality of isolated T cell populations or types. In some aspects, the methods are capable of preparing of a plurality of different cell populations for adoptive therapy using fewer steps and/or resources and/or reduced handling compared with other methods.

The present invention relates to the prediction of responsiveness to cancer immunotherapy of a subject based on the T-cell composition of the subject, and a therapeutic method using cancer immunotherapy based on the prediction. The present invention also provides a method for improving or maintaining responsiveness to cancer immunotherapy of a subject. Responsiveness to cancer immunotherapy is predict by determining a relative value of a CD4.sup.+ T-cell subpopulation, dendritic cell subpopulation, and/or CD8.sup.+ T-cell subpopulation correlated with a dendritic cell stimulation in an anti-tumor immune response in a sample derived from a subject. A composition for treating or preventing cancer comprising cells such as CD62L.sup.lowCD4.sup.+ T-cells is also provided.

The present invention relates to the prediction of responsiveness to cancer immunotherapy of a subject based on the T-cell composition of the subject, and a therapeutic method using cancer immunotherapy based on the prediction. The present invention also provides a method for improving or maintaining responsiveness to cancer immunotherapy of a subject. Responsiveness to cancer immunotherapy is predict by determining a relative value of a CD4.sup.+ T-cell subpopulation, dendritic cell subpopulation, and/or CD8.sup.+ T-cell subpopulation correlated with a dendritic cell stimulation in an anti-tumor immune response in a sample derived from a subject. A composition for treating or preventing cancer comprising cells such as CD62L.sup.lowCD4.sup.+ T-cells is also provided.

Systems and methods to tag cells in a tissue sample with spatial identifiers, so that spatial reconstruction of cell locations within a tissue can be achieved after tissue disaggregation are described. The systems and methods allow the control or directing of specific spatial identifiers spatially within or throughout a tissue to individual cells or to a small population of cells so that cell position can be determined by computational deconvolution of the spatial identifiers after tissue disaggregation. The systems and methods can be combined with single cell expression analysis to correlate cell types with cell location within a structure, such as a tumor.