Project Grant R01CA280981
- This Project Grant award from the National Cancer Institute (CFDA 93.395 Cancer Treatment Research) provides funding to the Beckman Research Institute of the City of Hope to conduct research on tumor-selective radiosensitization by targeting hypoxia in rectal cancer. The $662,096 award, active from February 1, 2025 to January 31, 2030, aims to characterize the biology driving the response of locally advanced rectal cancer to standard-of-care treatment and determine if an FDA-approved...
- This Project Grant award from the National Cancer Institute (CFDA 93.398 Cancer Research Manpower) provides $147,486 to Case Western Reserve University to develop a "Pathologically Interpretable Computational Imaging Predictor for Response to Total Neoadjuvant Treatment in Rectal Cancers". The project aims to apply deep learning techniques to routinely acquired MRI scans to accurately identify rectal cancer patients who exhibit a complete clinical response to neoadjuvant therapy,...
- This Project Grant award from the National Cancer Institute (CFDA 93.395 - Cancer Treatment Research) provides $730,398 to the Sloan-Kettering Institute for Cancer Research to conduct research on leveraging radiation-induced senescence and PTPN2 inhibition to enhance immune-mediated tumor control in rectal cancer. The research aims to develop non-surgical treatment strategies that prioritize organ preservation and minimize lifelong morbidities for rectal cancer patients. Key aspects of the...
- This $1,686,258 Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) to Onc.ai, Inc. aims to further develop and validate a deep learning radiomics biomarker for improved early response assessment in metastatic cancer therapy trials. The proposed approach uses deep learning models on CT scans at baseline and follow-up time points to generate a continuous "Serial CT Response Score" that can more accurately predict overall...
- This federal Project Grant award from the National Center for Advancing Translational Sciences (NCATS), with CFDA Number 93.350, provides $163,310 to evaluate a multimodality platform of tissue, blood, and advanced imaging-based biomarkers to predict response to neoadjuvant immunotherapy and radiotherapy in melanoma patients. The key products and services to be delivered under this 2-year award (Sep 2025 - Sep 2027) include longitudinal evaluation of tumor tissue using multiplex...
- This Project Grant award, provided by the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research), supports a transformative research project aimed at enhancing prostate cancer (PCA) prognostication through the integration of epithelial-to-mesenchymal transition (EMT) signature markers with advanced imaging and machine learning techniques. The $399,954 award to Metastx LLC will enable analysis of PCA tissue samples to develop a novel predictive model for metastatic...
- This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) provides $405,973 to Intus Biosciences LLC (DBA Shoreline Biome LLC) to develop and validate a novel non-invasive, high-throughput fecal microbiome-based screening platform for the detection of colorectal cancer (CRC) and advanced adenoma (AA) precancerous lesions. The platform, called TITAN-1, utilizes machine learning to analyze fecal samples collected at home, with the goal of...
- This Project Grant award from the National Cancer Institute's (CFDA 93.394 - Cancer Detection and Diagnosis Research) will fund a research project titled "Innovative Scan Protocols with Combined Long Axial FOV PET and Spectral CT for Improved Quantification in Oncology". The $666,670 award, effective January 15, 2025, aims to develop advanced imaging protocols and processing techniques that utilize both positron emission tomography (PET) and spectral computed tomography (CT) to enhance...
- This Project Grant award of $306,798 from the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394) aims to develop an artificial intelligence-based system to accurately identify malignant lymph nodes. The key objectives are to: Create a lymph node segmentation model to enable extraction of radiomic features critical for malignancy classification. Develop both cloud-based and standalone desktop deployment options for the classification model to...
- This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) provides $2,491,138 to Oregon Health & Science University to develop a fluorescence-guided nerve sparing technique for colorectal cancer surgery. The project aims to enable real-time visualization of nerves during surgery using a near-infrared fluorescent contrast agent. This approach seeks to improve surgical outcomes by reducing positive margins and nerve damage, which can...
NOVEL RADIOMIC SIGNATURES FOR TREATMENT RESPONSE TO NEOADJUVANT THERAPY IN RECTAL CANCERS - ABSTRACT: WITH NEARLY 45,000 RECTAL CANCERS TO BE DIAGNOSED IN 2023, THE MAJOR CLINICAL QUESTION OF INTEREST IS THE IDENTIFICATION OF THOSE PATIENTS WHO WILL ACHIEVE SUSTAINED CLINICAL COMPLETE RESPONSE (CCR, NO DETECTABLE MACROSCOPIC TUMOR) OR TRUE PCR (PATHOLOGIC COMPLETE RESPONSE, WITH VERY FEW/NO TUMOR CELLS). WITH THE RECENT INCORPORATION OF OPTIONS SUCH AS TOTAL NEOADJUVANT THERAPY (NEOADJUVANT CHEMOTHERAPY AND CHEMORADIATION), THESE COMPLETE RESPONDER PATIENTS CAN COMPRISE UP TO ~50% OF THE POPULATION. IF THESE "TRUE" COMPLETE RESPONSE PATIENTS COULD BE RELIABLY IDENTIFIED, THEY COULD AVOID THE MAJOR COMPLICATIONS OF RECTAL RESECTION (ANASTOMOTIC LEAKAGE, PELVIC SEPSIS, URETERIC INJURY) AND QUALITY-OF-LIFE ISSUES (PERMANENT OSTOMY, FECAL INCONTINENCE), WITH NO IMPACT ON THEIR OVERALL SURVIVAL. HOWEVER, THERE ARE NO VALIDATED OBJECTIVE DIAGNOSTIC CRITERIA (USING ENDOSCOPY, MRI, AND DIGITAL RECTAL EXAMS) OR SERUM/BLOOD-BASED MARKERS (E.G., CARCINOEMBRYONIC ANTIGEN, CEA) THAT CAN DEFINITIVELY IDENTIFY TRUE COMPLETE RESPONDERS FOR ORGAN-PRESERVING STRATEGIES AND NON-OPERATIVE MANAGEMENT IN RECTAL CANCERS. QUANTITATIVE NON-INVASIVE IMAGING MARKERS THAT ACCURATELY CHARACTERIZE PATHOLOGIC TUMOR REGRESSION IN RECTAL CANCERS AFTER NEOADJUVANT THERAPY COULD BE HUGELY IMPACTFUL IN SELECTING COMPLETE RESPONSE PATIENTS WHO CAN BE SAFELY RECOMMENDED ORGAN-PRESERVATION VS PARTIAL/NON-RESPONDERS WHO REQUIRE SURGERY. TO SPECIFICALLY CAPTURE SUBTLE PATHOLOGIC CUES ON MRI RESULTING FROM THE DESMOPLASTIC FIBROSIS AND TUMOR RESPONSE AFTER CHEMORADIATION/TNT, WE HAVE IDENTIFIED UNIQUE COMPUTER-EXTRACTED IMAGE FEATURES OF GRADIENT RESPONSE AND MORPHOLOGICAL DISRUPTIONS WITHIN THE LESION (WALL, TUMOR) AND PERI-LESION ENVIRONMENT (LUMEN, PERITUMORAL FAT). THIS R01 WILL BUILD ON THESE EXCITING FINDINGS TO DEVELOP AND VALIDATE A RADIOMIC TUMOR RESPONSE (RADTR) CLASSIFIER TO ACCURATELY IDENTIFY COMPLETE RESPONDERS AFTER NEOADJUVANT THERAPY IN RECTAL CANCERS, VIA ROUTINE MRI. THE RADTR CLASSIFIER WILL ADDITIONALLY INCORPORATE A NOVEL "SPATIAL DIVERSITY" DESCRIPTOR THAT CAPTURES MACRO-SCALE TISSUE ORGANIZATION AND STROMAL COMPOSITION THAT ARE BIOLOGICAL HALLMARKS OF COMPLETE RESPONSE. USING A MULTI-INSTITUTIONAL COHORT OF ~900 PATIENTS, OUR VALIDATION OF THE RADTR CLASSIFIER WILL FOCUS ON THREE KEY CRITERIA. (I) TO ENABLE CLINICAL INTERPRETABILITY, WE WILL CONDUCT DETAILED HISTOMORPHOLOGICAL EVALUATION OF RADTR FEATURES VIA SPATIALLY MAPPED MRI AND WHOLE-MOUNT RECTAL PATHOLOGY SPECIMENS. (II) FOR CONFIRMING DIAGNOSTIC RELIABILITY, THE RADTR CLASSIFIER WILL BE COMPREHENSIVELY COMPARED AGAINST CLINICAL EVALUATION CRITERIA (ENDOSCOPY, MRI, DIGITAL RECTAL EXAM) AS WELL AS WITHIN A MULTI-READER STUDY; TO CONFIRM PERFORMANCE IMPROVEMENTS IN IDENTIFYING CR VIA MRI. (III) TOWARDS ENSURING EQUITY IN POPULATION PERFORMANCE FOR FUTURE CLINICAL DEPLOYMENT, THE RADTR CLASSIFIER WILL BE VALIDATED ACROSS MULTIPLE INSTITUTIONS AND POPULATIONS USING A NATIONAL CLINICAL TRIAL COHORT OF TNT IN RECTAL CANCERS (NRG GI-002). TO BE CLINICALLY ACTIONABLE FOR RECOMMENDING ORGAN- PRESERVING TREATMENT IN RECTAL CANCERS, RADTR MODEL WILL TARGET A 50% IMPROVEMENT IN SENSITIVITY FOR IDENTIFYING COMPLETE RESPONSE AS WELL AS ENSURING 95% SPECIFICITY IN IDENTIFYING PARTIAL/NON-PCR PATIENTS NEEDING SURGERY.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $60.9k | 5/23/25 | ||
| Not listed | $548.4k | 4/10/25 | ||
| Not listed | $548.4k | 4/10/25 | ||
| Not listed | $601.4k | 5/15/24 | ||
| Not listed | $601.4k | 5/15/24 |