SBIR-STTR Award

Ultra-high content analyses of circulating and solid tumor cells: A diagnostic reference system for disease burden
Award last edited on: 2/17/2024

Sponsored Program
SBIR
Awarding Agency
NIH : NCI
Total Award Amount
$1,913,568
Award Phase
2
Solicitation Topic Code
394
Principal Investigator
Michel Nederlof

Company Information

Quantitative Imaging Systems LLC (AKA: Qi)

2657 Monroeville Boulevard
Monroeville, PA 15146
   (412) 389-2083
   N/A
   www.qitissue.com
Location: Single
Congr. District: 12
County: Allegheny

Phase I

Contract Number: 1R44CA250861-01A1
Start Date: 8/16/2021    Completed: 7/31/2022
Phase I year
2021
Phase I Amount
$223,653
We propose to create a modular suite of products to facilitate highly multiplexed imaging and quantita- tive analyses of individual cells in intact tissue, and cells circulating in blood to be used to establish disease status. Our imaging software analyses platform supporting interactive data visualization will connect protein-based cellular features between tissue resident cells and disseminated cells to lever- age mechanisms of cancer cell dissemination to detect disease earlier, to identify risk for metastases, and to track response to treatment. Our goal is to develop an imaging software analyses platform, biomarker panels for highly multiplexed imaging using cyclic immunostaining and a newly discovered tumor cell population for translation to clinical assay development. Our suite of products will fill an unmet clinical need as no visual platforms exist that can link analyses of individual highly metastatic cells poised to escape the primary tumor with their disseminated counterparts in blood to inform disease status. Our technology has translational impact in developing a non-invasive biomarker for prognosti- cation and for monitoring treatment response in cancer patients. To ensure successful development of a visualization platform with translational potential, we will extend our close partnership with Oregon Health and Science University (OHSU) and strong collaborations at the Knight Cancer Institute for biologic analyses with translation to patient care. We will leverage a novel disseminated tumor popula- tion (i.e., circulating hybrid cells [CHCs]), discovered at OHSU, and a novel cyclic immunofluorescence (cyCIF) technology based on oligonucleotide conjugated antibodies. Currently, little functionality exists to optimally extract the wealth of phenotypic information from highly multiplexed cyCIF images of cells produced on ours or similar staining platforms. Herein, we introduce a novel tool to manage, process, and dynamically visualize such images, with superior single cell analytics even in complex tissue. The proposed labeling platform is the foundation for a new field of advanced multi-parametric analytics that can correlate architectural and functional aspects of intact tissue then apply these finding to corre- sponding cells from blood; a critical aspect of lethal tumor progression. In Phase I, a prototype imaging platform will be built and tested with an integral set of biomarkers for identification of CHC in blood and their corresponding hybrid cell in the primary tumor. Upon confirming feasibility, Phase II will focus on expansion of this technology to address three critical clinical questions: (1) Can cancer be reliably de- tected with a blood test? (2) Can occult metastatic disease be detected in early stage cancers? (3) Can a blood test aid in treatment monitoring to personalize cancer therapy? Successful completion of this work will result in biomarker panels and a software solution to answer these questions as demonstrated in pancreatic and colorectal cancers herein, that can be readily expanded to other cancer types.

Public Health Relevance Statement:
PROJECT SUMMARY We propose to create a modular suite of products to facilitate highly multiplexed imaging and quantita- tive analyses of individual cells in intact tissue, and cells circulating in blood to be used to establish disease status. Our imaging software analyses platform supporting interactive data visualization will connect protein-based cellular features between tissue resident cells and disseminated cells to lever- age mechanisms of cancer cell dissemination to detect disease earlier, to identify risk for metastases, and to track response to treatment.

Project Terms:
Age; ages; Antibodies; Architecture; Engineering / Architecture; Biology; Blood; Blood Reticuloendothelial System; Malignant Neoplasms; Cancers; Malignant Tumor; malignancy; neoplasm/cancer; Rectal Cancer; Rectal Carcinoma; Rectum Cancer; Rectum Carcinoma; Cataloging; Cations; Cells; Cell Body; Color; Data Analyses; Data Analysis; data interpretation; Disease; Disorder; Foundations; Patient Care; Patient Care Delivery; Goals; Gold; Blood Tests; Hematologic Tests; Hematological Tests; Hematology Testing; Hybrid Cells; Somatic Cell Hybrids; Institutes; Maps; Methodology; Neoplasm Metastasis; Metastasis; Metastasize; Metastatic Lesion; Metastatic Mass; Metastatic Neoplasm; Metastatic Tumor; Secondary Neoplasm; Secondary Tumor; cancer metastasis; tumor cell metastasis; Oligonucleotides; Oligo; oligos; Oregon; Patients; Periodicity; Cyclicity; Rhythmicity; Phenotype; Proteins; Research; Risk; Signal Pathway; Signal Transduction; Cell Communication and Signaling; Cell Signaling; Intracellular Communication and Signaling; Signal Transduction Systems; Signaling; biological signal transduction; Computer software; Software; Specificity; Stains; Staining method; Technology; Testing; Time; Tissues; Body Tissues; Translations; Universities; Work; Immunofluorescence Immunologic; Immunofluorescence; symposium; conference; convention; summit; symposia; base; tumor progression; cancer progression; neoplasm progression; neoplastic progression; Blood specimen; Blood Sample; Label; Image Analysis; Image Analyses; image evaluation; image interpretation; Clinical; Phase; Biological; Link; Ensure; Evaluation; peripheral blood; Visual; Individual; Disease Progression; Solid Neoplasm; Solid Tumor; Collaborations; Indirect Immunofluorescence; Malignant Cell; cancer cell; tool; Malignant Pancreatic Neoplasm; Pancreas Cancer; Pancreatic Cancer; pancreatic malignancy; Malignant neoplasm of pancreas; Diagnostic; Complex; cell type; Pattern; System; Tumor Tissue; Operative Procedures; Surgical; Surgical Interventions; Surgical Procedure; surgery; Operative Surgical Procedures; early detection; Early Diagnosis; Tumor Cell; neoplastic cell; success; antibody conjugate; cohort; Primary Tumor; Primary Neoplasm; novel; validation studies; Abscission; Extirpation; Removal; Surgical Removal; resection; Excision; Sampling; protein expression; Address; Detection; Health Sciences; predict therapeutic response; predict therapy response; predict treatment response; therapy prediction; treatment prediction; treatment response prediction; Prediction of Response to Therapy; Cancer Patient; Small Business Innovation Research Grant; SBIR; Small Business Innovation Research; Tissue Model; Validation; Pathologic; Monitor; Process; Derivation procedure; Derivation; Development; developmental; Colorectal Cancer; Colo-rectal Cancer; cellular imaging; cell imaging; Image; imaging; burden of illness; burden of disease; disease burden; years of life lost to disability; years of life lost to disease; Population; cancer type; Cell model; Cellular model; spatial relationship; prototype; tumor; high risk; treatment response; response to treatment; therapeutic response; Biological Markers; bio-markers; biologic marker; biomarker; clinical assay development; colon cancer patients; colo-rectal cancer patients; colorectal cancer patients; targeted treatment; targeted drug therapy; targeted drug treatments; targeted therapeutic; targeted therapeutic agents; targeted therapy; personalized cancer therapy; individualized cancer therapy; personalized cancer treatment; imaging software; imaging platform; data visualization; biomarker panel; marker panel; biomarker identification; marker identification; prognostic assays; prognostic test; translational impact; multiplexed imaging; Visualization

Phase II

Contract Number: 4R44CA250861-02
Start Date: 8/16/2021    Completed: 8/31/2024
Phase II year
2022
(last award dollars: 2023)
Phase II Amount
$1,689,915

We propose to create a modular suite of products to facilitate highly multiplexed imaging and quantita- tive analyses of individual cells in intact tissue, and cells circulating in blood to be used to establish disease status. Our imaging software analyses platform supporting interactive data visualization will connect protein-based cellular features between tissue resident cells and disseminated cells to lever- age mechanisms of cancer cell dissemination to detect disease earlier, to identify risk for metastases, and to track response to treatment. Our goal is to develop an imaging software analyses platform, biomarker panels for highly multiplexed imaging using cyclic immunostaining and a newly discovered tumor cell population for translation to clinical assay development. Our suite of products will fill an unmet clinical need as no visual platforms exist that can link analyses of individual highly metastatic cells poised to escape the primary tumor with their disseminated counterparts in blood to inform disease status. Our technology has translational impact in developing a non-invasive biomarker for prognosti- cation and for monitoring treatment response in cancer patients. To ensure successful development of a visualization platform with translational potential, we will extend our close partnership with Oregon Health and Science University (OHSU) and strong collaborations at the Knight Cancer Institute for biologic analyses with translation to patient care. We will leverage a novel disseminated tumor popula- tion (i.e., circulating hybrid cells [CHCs]), discovered at OHSU, and a novel cyclic immunofluorescence (cyCIF) technology based on oligonucleotide conjugated antibodies. Currently, little functionality exists to optimally extract the wealth of phenotypic information from highly multiplexed cyCIF images of cells produced on ours or similar staining platforms. Herein, we introduce a novel tool to manage, process, and dynamically visualize such images, with superior single cell analytics even in complex tissue. The proposed labeling platform is the foundation for a new field of advanced multi-parametric analytics that can correlate architectural and functional aspects of intact tissue then apply these finding to corre- sponding cells from blood; a critical aspect of lethal tumor progression. In Phase I, a prototype imaging platform will be built and tested with an integral set of biomarkers for identification of CHC in blood and their corresponding hybrid cell in the primary tumor. Upon confirming feasibility, Phase II will focus on expansion of this technology to address three critical clinical questions: (1) Can cancer be reliably de- tected with a blood test? (2) Can occult metastatic disease be detected in early stage cancers? (3) Can a blood test aid in treatment monitoring to personalize cancer therapy? Successful completion of this work will result in biomarker panels and a software solution to answer these questions as demonstrated in pancreatic and colorectal cancers herein, that can be readily expanded to other cancer types.

Public Health Relevance Statement:
PROJECT SUMMARY We propose to create a modular suite of products to facilitate highly multiplexed imaging and quantita- tive analyses of individual cells in intact tissue, and cells circulating in blood to be used to establish disease status. Our imaging software analyses platform supporting interactive data visualization will connect protein-based cellular features between tissue resident cells and disseminated cells to lever- age mechanisms of cancer cell dissemination to detect disease earlier, to identify risk for metastases, and to track response to treatment.

Project Terms:
Age; ages; Antibodies; Architecture; Engineering / Architecture; Biological Assay; Assay; Bioassay; Biologic Assays; Biology; Blood; Blood Reticuloendothelial System; Malignant Neoplasms; Cancers; Malignant Tumor; malignancy; neoplasm/cancer; Rectal Cancer; Rectal Carcinoma; Rectum Cancer; Rectum Carcinoma; Cataloging; Cells; Cell Body; Color; Data Analyses; Data Analysis; data interpretation; Disease; Disorder; Foundations; Patient Care; Patient Care Delivery; Goals; Gold; Blood Tests; Hematologic Tests; Hematological Tests; Hematology Testing; Hybrid Cells; Somatic Cell Hybrids; Institutes; Maps; Methodology; Metastasis; Metastasize; Metastatic Lesion; Metastatic Mass; Metastatic Neoplasm; Metastatic Tumor; Secondary Neoplasm; Secondary Tumor; cancer metastasis; tumor cell metastasis; Neoplasm Metastasis; Oligo; oligos; Oligonucleotides; Oregon; Patients; Cyclicity; Rhythmicity; Periodicity; Phenotype; Proteins; Research; Risk; Signal Pathway; Cell Communication and Signaling; Cell Signaling; Intracellular Communication and Signaling; Signal Transduction Systems; Signaling; biological signal transduction; Signal Transduction; Software; Computer software; Specificity; Staining method; Stains; Technology; Testing; Time; Tissues; Body Tissues; Translations; Universities; Work; Immunofluorescence Immunologic; Immunofluorescence; symposium; conference; convention; summit; symposia; base; tumor progression; cancer progression; neoplasm progression; neoplastic progression; Blood specimen; Blood Sample; Label; Image Analysis; Image Analyses; image evaluation; image interpretation; Clinical; Phase; Biological; biologic; Link; Ensure; Evaluation; peripheral blood; Visual; Individual; Disease Progression; Solid Tumor; Solid Neoplasm; Collaborations; Indirect Immunofluorescence; Malignant Cell; cancer cell; tool; Malignant Pancreatic Neoplasm; Pancreas Cancer; Pancreatic Cancer; pancreatic malignancy; Malignant neoplasm of pancreas; Diagnostic; Complex; cell type; Pattern; System; Tumor Tissue; Operative Procedures; Surgical; Surgical Interventions; Surgical Procedure; surgery; Operative Surgical Procedures; early detection; Early Diagnosis; Tumor Cell; neoplastic cell; success; antibody conjugate; cohort; Primary Tumor; Primary Neoplasm; novel; validation studies; Abscission; Extirpation; Removal; Surgical Removal; resection; Excision; Sampling; protein expression; Address; Detection; Health Sciences; predict therapeutic response; predict therapy response; predict treatment response; therapy prediction; treatment prediction; treatment response prediction; Prediction of Response to Therapy; Cancer Patient; Small Business Innovation Research Grant; SBIR; Small Business Innovation Research; Tissue Model; Validation; Pathologic; Monitor; Process; Derivation procedure; Derivation; Development; developmental; Colorectal Cancer; Colo-rectal Cancer; cellular imaging; cell imaging; Image; imaging; burden of illness; burden of disease; disease burden; years of life lost to disability; years of life lost to disease; Population; cancer type; Cell model; Cellular model; spatial relationship; prototype; tumor; high risk; treatment response; response to therapy; response to treatment; therapeutic response; therapy response; Biological Markers; bio-markers; biologic marker; biomarker; clinical assay development; colon cancer patients; colo-rectal cancer patients; colorectal cancer patients; targeted treatment; targeted drug therapy; targeted drug treatments; targeted therapeutic; targeted therapeutic agents; targeted therapy; personalized cancer therapy; individualized cancer therapy; personalized cancer treatment; imaging software; imaging platform; data visualization; biomarker panel; marker panel; biomarker identification; marker identification; translational impact; multiplexed imaging; Visualization; prognostication; translational potential