SBIR-STTR Award

Pathmap NSCLC: a Functional Companion Diagnostic Test to Predict Optimal Therapy for Patients with Non-Small Cell Lung Cancer.
Award last edited on: 1/17/2018

Sponsored Program
SBIR
Awarding Agency
NIH : NCI
Total Award Amount
$2,282,049
Award Phase
2
Solicitation Topic Code
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Principal Investigator
Greg Bertenshaw

Company Information

BioMarker Strategies LLC

15601 Crabbs Branch Way
Rockville, MD 20855
Location: Single
Congr. District: 06
County: Montgomery

Phase I

Contract Number: 1R44CA203068-01
Start Date: 9/23/2015    Completed: 2/29/2016
Phase I year
2015
Phase I Amount
$299,876
Lung cancer (LC) is the leading cause of cancer death in the US with an estimated 158,040 deaths in 2015. Non- small cell LC is the predominant category of the disease (NSCLC; 83%). Molecular characterization of tumors has shifted the paradigm of one drug fits all. Currently, molecularly-targeted agents (MTAs) and companion diagnostics (CDx) are being developed to target oncogenic drivers in signaling pathways, and select patients most likely to respond, respectively. This personalized approach was successful in increasing response rates (RR) to erlotinib by enriching for patients with EGFR activating mutations (68% RR versus 9% in unselected patients). Unfortunately, within a year for most patients, emergence of resistance mechanisms results in disease progression with little insight into appropriate follow-up therapy. In addition, many patients have no clinicaly- actionable biomarkers and are considered poor candidates for MTAs. However, many of these individuals can benefit from MTAs. Five-year survival rates are only 4% in patients with distant metastatic disease, when the disease is typically diagnosed. Therefore, there is an urgent medical need for improved predictive tests. Here, we propose to develop PathMAP(r) NSCLC, an innovative CDx test to predict the optimal therapeutic approach for patients with advanced NSCLC. This will be achieved by comparing the pharmacodynamic responses of signal transduction pathways upon exposure to four MTAs (erlotinib, crizotinib, trametinib and sorafenib) which target aberrantly activated proteins in these pathways. PathMAP NSCLC will be commerciality enabled using the SnapPath(r) Cancer Diagnostics System, the first and only user-friendly clinic-ready method, which automates and standardizes the interrogation of a patient's live tumor cells. Phase I Segment: Specific Aim #1: Optimize dispersion of NSCLC biopsies on the SnapPath instrument to prepare live cells for ex vivo modulation. 20 biopsies will be used to determine optimal SnapPath processing conditions. Flow rates and total cycles will be varied to enable equal distribution to multiple testing chambers without perturbing signaling and cell death. Specific Aim #2: Evoke Functional Signaling Profiles in NSCLC clinical samples against erlotinib. 30 biopsies will be profiled using the SnapPath Process. Milestones for transitioning to Phase II: 1. Effectively disperse and distribute clinical NSCLC biopsies on the SnapPath instrument. 2. Successfully generate functional profiles in >75% of the clinical samples. Phase II Segment: Specific Aim #3: Optimize ex vivo conditions and response profile to predict sensitivity to MTAs. 60 NSCLC cell lines will be categorized into sensitive or resistant groups and functionally profiled to create the PathMAP NSCLC model. Specific Aim #4: Test predictive ex vivo cut-off values using TumorGrafts and clinical NSCLC samples. The PathMAP NSCLC model will be used to predict MTA efficacy in 10 TumorGraft models and 200 human clinical samples from patients with metastatic NSCLC. These results are intended to be a proof-of-principle in humans.

Public Health Relevance Statement:


Public Health Relevance:
Lung cancer is the leading cause of cancer-related deaths worldwide and 83% of all lung cancers are classified as NSCLC. The overall goal of our proposal is to develop a companion diagnostic test to help clinicians predict the optimal therapeutic approach for patients with metastatic NSCLC. The test will use an individual's functional response to four highly prominent molecularly-targeted agents (MTAs).

NIH Spending Category:
Cancer; Clinical Research; Lung; Lung Cancer

Project Terms:
BAY 54-9085; Biological Markers; Biopsy; Cancer Diagnostics; Cancer Etiology; Categories; Cell Death Signaling Process; Cell Line; Cell Survival; Cells; Cessation of life; Classification; Clinic; Clinical; clinically actionable; Collection; companion diagnostics; Conditioned Reflex; Diagnosis; Diagnostic tests; Disease; Disease Progression; Distant; Epidermal Growth Factor Receptor; Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor; Erlotinib; Exposure to; follow-up; Goals; Human; improved; in vivo; Individual; innovation; insight; instrument; Life; Malignant neoplasm of lung; Medical; Methods; Modeling; Molecular; Mutation; neoplastic cell; Non-Small-Cell Lung Carcinoma; Oncogenic; Outcome; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacodynamics; Phase; Phosphoproteins; Process; Proteins; public health relevance; Resistance; resistance mechanism; response; Sampling; Signal Pathway; Signal Transduction; Signal Transduction Pathway; Solid Neoplasm; Survival Rate; System; Testing; Therapeutic; tumor; user-friendly

Phase II

Contract Number: 4R44CA203068-02
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
2017
(last award dollars: 2018)
Phase II Amount
$1,982,173

Lung cancer (LC) is the leading cause of cancer death in the US with an estimated 158,040 deaths in 2015. Nonsmall cell LC is the predominant category of the disease (NSCLC; 83%). Molecular characterization of tumors has shifted the paradigm of one drug fits all. Currently, molecularly-targeted agents (MTAs) and companion diagnostics (CDx) are being developed to target oncogenic drivers in signaling pathways, and select patients most likely to respond, respectively. This personalized approach was successful in increasing response rates (RR) to erlotinib by enriching for patients with EGFR activating mutations (68% RR versus 9% in unselected patients). Unfortunately, within a year for most patients, emergence of resistance mechanisms results in disease progression with little insight into appropriate follow-up therapy. In addition, many patients have no clinicallyactionable biomarkers and are considered poor candidates for MTAs. However, many of these individuals can benefit from MTAs. Five-year survival rates are only 4% in patients with distant metastatic disease, when the disease is typically diagnosed. Therefore, there is an urgent medical need for improved predictive tests. Here, we propose to develop PathMAP® NSCLC, an innovative CDx test to predict the optimal therapeutic approach for patients with advanced NSCLC. This will be achieved by comparing the pharmacodynamic responses of signal transduction pathways upon exposure to four MTAs (erlotinib, crizotinib, trametinib and sorafenib) which target aberrantly activated proteins in these pathways. PathMAP NSCLC will be commerciality enabled using the SnapPath® Cancer Diagnostics System, the first and only user-friendly clinic-ready method, which automates and standardizes the interrogation of a patient’s live tumor cells. Phase I Segment: Specific Aim #1: Optimize dispersion of NSCLC biopsies on the SnapPath instrument to prepare live cells for ex vivo modulation. 20 biopsies will be used to determine optimal SnapPath processing conditions. Flow rates and total cycles will be varied to enable equal distribution to multiple testing chambers without perturbing signaling and cell death. Specific Aim #2: Evoke Functional Signaling Profiles in NSCLC clinical samples against erlotinib. 30 biopsies will be profiled using the SnapPath Process. Milestones for transitioning to Phase II: 1. Effectively disperse and distribute clinical NSCLC biopsies on the SnapPath instrument. 2. Successfully generate functional profiles in >75% of the clinical samples. Phase II Segment: Specific Aim #3: Optimize ex vivo conditions and response profile to predict sensitivity to MTAs. 60 NSCLC cell lines will be categorized into sensitive or resistant groups and functionally profiled to create the PathMAP NSCLC model. Specific Aim #4: Test predictive ex vivo cut-off values using TumorGrafts and clinical NSCLC samples. The PathMAP NSCLC model will be used to predict MTA efficacy in 10 TumorGraft models and 200 human clinical samples from patients with metastatic NSCLC. These results are intended to be a proof-of-principle in humans.

Public Health Relevance Statement:
Lung cancer is the leading cause of cancer-related deaths worldwide and 83% of all lung cancers are classified as NSCLC. The overall goal of our proposal is to develop a companion diagnostic test to help clinicians predict the optimal therapeutic approach for patients with metastatic NSCLC. The test will use an individual’s functional response to four highly prominent molecularly-targeted agents (MTAs).

Project Terms:
BAY 54-9085; Biological Markers; Biopsy; Cancer Diagnostics; Cancer Etiology; Categories; Cell Death; Cell Line; Cell Survival; Cells; Cessation of life; Classification; Clinic; Clinical; clinically actionable; Collection; companion diagnostics; Conditioned Reflex; crizotinib; Diagnosis; Diagnostic tests; Disease; Disease Progression; Distant; Epidermal Growth Factor Receptor; Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor; Erlotinib; Exposure to; follow-up; Goals; Human; improved; in vivo; Individual; innovation; insight; instrument; Malignant neoplasm of lung; Medical; Methods; Modeling; Molecular; Molecular Target; Mutation; neoplastic cell; Non-Small-Cell Lung Carcinoma; Oncogenic; Outcome; Pathway interactions; Patients; personalized approach; Pharmaceutical Preparations; Pharmacodynamics; Phase; Phosphoproteins; Process; Proteins; Resistance; resistance mechanism; response; Sampling; Signal Pathway; Signal Transduction; Signal Transduction Pathway; Solid Neoplasm; Standardization; Survival Rate; System; targeted agent; Testing; Therapeutic; therapy outcome; tumor; user-friendly