Fig 2: Circulating hybrid cells (CHCs) in pancreatic cancer patients. (A) Two populations of fusion hybrid identified by ALICE: CHC-1 (DAPI+/CD45+/E-cadherin+/vimentin-) and CHC-2 (DAPI+/CD45+/E-cadherin+/vimentin+) embedded in an overwhelming population of WBCs (DAPI+/CD45+/E-cadherin-/vimentin-) in pancreatic cancer patients. Scale bar: 20 µm. (B) Frequency histogram of CHC-1 and CHC-2 counts in pancreatic cancer patients. (C-D) Size distribution of CHC-1 and CHC-2. (E-H) Correlation of CHC-1, CHC-2 and CTC-T with T stage (n=24), N stage (n=24), M stage (n=32) and recurrence (n=32). * - P < 0.05; ** - P < 0.01 from Mann-Whitney U test. (I) Receiver operating characteristic (ROC) curves for CHC-1 and CHC-T in differentiating N0 and N1 PDAC patients with their respective apparent area under the curve (AUC), optimism and optimism-adjusted AUC calculated over 10000 bootstrap iterations. Colored dots represent the selected cutoff of 1 CHC-1/2 ml of blood and 1 CHC-T/2 ml of blood. (J) Validity of CHC-1 and CHC-T as PDAC node-positive biomarker in terms of the sensitivity, specificity, positive predicted value (PPV), negative predicted value (NPV) and accuracy. The error bars denote the 95% CI.

Fig 3: Major operational challenges of a modern biomedical software for futurity. (A) Rare tumor cells bestrewed in dense and massive populations of non-tumor cells require accurate processing. 'E-CTC' denotes epithelial circulating tumor cell that expressed positive for the nucleus marker DAPI and epithelial tumor marker E-cadherin but negative for the mesenchymal tumor marker vimentin and leukocyte marker CD45. 'M-CTC' denotes mesenchymal CTC that expressed positive for DAPI and vimentin but negative for E-cadherin and CD45. 'H-CTC' denotes hybrid CTC that expressed positive for DAPI, E-cadherin and vimentin but negative for CD45. 'Unknown' denotes cell that expressed positive for all 4 markers. White blood cell (WBC) expressed positive for DAPI and CD45 but negative for E-cadherin. (B) Enhanced software connectivity to encourage participation from appurtenant user communities. Different communities will have different accessibility and functions.

Fig 4: Monitoring response to therapy with deep in situ immune phenotyping by mIHC(A) Primary tumor (PT) and Bx1–Bx4 were subjected to multiplex immunohistochemistry (mIHC) analyses measuring immune (CD45+) and epithelial (PanCK+) cells in tumor compartments as a percentage of total nucleated cells.(B) Representation of tissue composition, showing density (number of cells per square millimeter of tissue analyzed) of PanCK+ (cytokeratin), CD45+, and PanCK- CD45- (other) nucleated cells.(C) Immune composition of seven major leukocyte lineages, as a percentage of total CD45+ cells.(D) Deeper auditing of leukocyte lineages in Bx1 and Bx2, measuring 12 immune cell populations and functional states.(E) CD3+ T cell proportions of total CD45+ cell populations (orange, left), and CD4+ (blue) and CD8+ T cells (periwinkle) proportions within CD45+CD3+ T cells (right).(F) PD-1+ cells as a percentage of total CD3+T cells in the CD3+CD4+ (top) and CD3+CD8+ (bottom) T cell populations.(G) Differentiation state of CD3+CD4+ T cells, reflected by regulatory T (Treg), Th1, and Th2, Th17, and Th0/?d subsets (left) and CD3+CD8+ T cells, as reflected by expression of PD-1 and EOMES.(H) Differentiation state of CD3+CD4+ T cells reflected by Treg, Th17, Th1, Th2, and Th0/?d subsets in Bx1 and Bx2.See also Figure S4 and Table S2.