Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation.

We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing, computational modeling, and an expanding repertoire of observational data across multiple scales and modalities. In 2020, the US National Cancer Institute, and the US Department of Energy, through a trans-disciplinary research community at the intersection of advanced computing and cancer research, initiated team science collaborative projects to explore the development and implementation of predictive Cancer Patient Digital Twins. Several diverse pilot projects were launched to provide key insights into important features of this emerging landscape and to determine the requirements for the development and adoption of cancer patient digital twins. Projects included exploring approaches to using a large cohort of digital twins to perform deep phenotyping and plan treatments at the individual level, prototyping self-learning digital twin platforms, using adaptive digital twin approaches to monitor treatment response and resistance, developing methods to integrate and fuse data and observations across multiple scales, and personalizing treatment based on cancer type. Collectively these efforts have yielded increased insights into the opportunities and challenges facing cancer patient digital twin approaches and helped define a path forward. Given the rapidly growing interest in patient digital twins, this manuscript provides a valuable early progress report of several CPDT pilot projects commenced in common, their overall aims, early progress, lessons learned and future directions that will increasingly involve the broader research community.

Predictive Radiation Oncology - A New NCI-DOE Scientific Space and Community.

With a widely attended virtual kickoff event on January 29, 2021, the National Cancer Institute (NCI) and the Department of Energy (DOE) launched a series of 4 interactive, interdisciplinary workshops-and a final concluding "World Café" on March 29, 2021-focused on advancing computational approaches for predictive oncology in the clinical and research domains of radiation oncology. These events reflect 3,870 human hours of virtual engagement with representation from 8 DOE national laboratories and the Frederick National Laboratory for Cancer Research (FNL), 4 research institutes, 5 cancer centers, 17 medical schools and teaching hospitals, 5 companies, 5 federal agencies, 3 research centers, and 27 universities. Here we summarize the workshops by first describing the background for the workshops. Participants identified twelve key questions-and collaborative parallel ideas-as the focus of work going forward to advance the field. These were then used to define short-term and longer-term "Blue Sky" goals. In addition, the group determined key success factors for predictive oncology in the context of radiation oncology, if not the future of all of medicine. These are: cross-discipline collaboration, targeted talent development, development of mechanistic mathematical and computational models and tools, and access to high-quality multiscale data that bridges mechanisms to phenotype. The workshop participants reported feeling energized and highly motivated to pursue next steps together to address the unmet needs in radiation oncology specifically and in cancer research generally and that NCI and DOE project goals align at the convergence of radiation therapy and advanced computing.

Preanalytical Variables for the Genomic Assessment of the Cellular and Acellular Fractions of the Liquid Biopsy in a Cohort of Breast Cancer Patients.

Liquid biopsy allows assessment of multiple analytes, providing temporal information with potential for improving understanding of cancer evolution and clinical management of patients. Although liquid biopsies are intensely investigated for prediction and response monitoring, preanalytic variables are of primary concern for clinical implementation, including categories of collection method and sample storage. Herein, an integrated high-density single-cell assay workflow for morphometric and genomic analysis of the liquid biopsy is used to characterize the effects of preanalytical variation and reproducibility of data from a breast cancer cohort. Following prior work quantifying performance of commonly used blood collection tubes, this study completes the analysis of four time points to assay (24, 48, 72, and 96 hours), demonstrating precision up to 48 hours after collection for assay sensitivity, highly reproducible rare cell enumeration, morphometric characterization, and high efficiency and capacity for single-cell genomic analysis. For the cell-free analysis, both freezing and use of fresh plasma produced similar quality and quantity of cell-free DNA for sequencing. The genomic analysis (copy number variation and single-nucleotide variation) described herein is broadly applicable to liquid biopsy platforms capable of isolating cell-free and cell-based DNA. Morphometric parameters and genomic signatures of individual circulating tumor cells were evaluated in relation to patient clinical response, providing preliminary evidence of clinical validity as a potential biomarker aiding clinical diagnostics or monitoring progression.

AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing.

The application of data science in cancer research has been boosted by major advances in three primary areas: (1) Data: diversity, amount, and availability of biomedical data; (2) Advances in Artificial Intelligence (AI) and Machine Learning (ML) algorithms that enable learning from complex, large-scale data; and (3) Advances in computer architectures allowing unprecedented acceleration of simulation and machine learning algorithms. These advances help build in silico ML models that can provide transformative insights from data including: molecular dynamics simulations, next-generation sequencing, omics, imaging, and unstructured clinical text documents. Unique challenges persist, however, in building ML models related to cancer, including: (1) access, sharing, labeling, and integration of multimodal and multi-institutional data across different cancer types; (2) developing AI models for cancer research capable of scaling on next generation high performance computers; and (3) assessing robustness and reliability in the AI models. In this paper, we review the National Cancer Institute (NCI) -Department of Energy (DOE) collaboration, Joint Design of Advanced Computing Solutions for Cancer (JDACS4C), a multi-institution collaborative effort focused on advancing computing and data technologies to accelerate cancer research on three levels: molecular, cellular, and population. This collaboration integrates various types of generated data, pre-exascale compute resources, and advances in ML models to increase understanding of basic cancer biology, identify promising new treatment options, predict outcomes, and eventually prescribe specialized treatments for patients with cancer.

Opportunities and Challenges in Implementation of Multiparameter Single Cell Analysis Platforms for Clinical Translation.

The high-content interrogation of single cells with platforms optimized for the multiparameter characterization of cells in liquid and solid biopsy samples can enable characterization of heterogeneous populations of cells ex vivo. Doing so will advance the diagnosis, prognosis, and treatment of cancer and other diseases. However, it is important to understand the unique issues in resolving heterogeneity and variability at the single cell level before navigating the validation and regulatory requirements in order for these technologies to impact patient care. Since 2013, leading experts representing industry, academia, and government have been brought together as part of the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium to foster the potential of high-content data integration for clinical translation.

Effect of Blood Collection Tube Type and Time to Processing on the Enumeration and High-Content Characterization of Circulating Tumor Cells Using the High-Definition Single-Cell Assay.

CONTEXT: - As circulating tumor cell (CTC) assays gain clinical relevance, it is essential to address preanalytic variability and to develop standard operating procedures for sample handling in order to successfully implement genomically informed, precision health care. OBJECTIVE: - To evaluate the effects of blood collection tube (BCT) type and time-to-assay (TTA) on the enumeration and high-content characterization of CTCs by using the high-definition single-cell assay (HD-SCA). DESIGN: - Blood samples of patients with early- and advanced-stage breast cancer were collected into cell-free DNA (CfDNA), EDTA, acid-citrate-dextrose solution, and heparin BCTs. Time-to-assay was evaluated at 24 and 72 hours, representing the fastest possible and more routine domestic shipping intervals, respectively. RESULTS: - We detected the highest CTC levels and the lowest levels of negative events in CfDNA BCT at 24 hours. At 72 hours in this BCT, all CTC subpopulations were decreased with the larger effect observed in high-definition CTCs and cytokeratin-positive cells smaller than white blood cells. Overall cell retention was also optimal in CfDNA BCT at 24 hours. Whole-genome copy number variation profiles were generated from single cells isolated from all BCT types and TTAs. Cells from CfDNA BCT at 24-hour TTA exhibited the least noise. CONCLUSIONS: - Circulating tumor cells can be identified and characterized under a variety of collection, handling, and processing conditions, but the highest quality can be achieved with optimized conditions. We quantified performance differences of the HD-SCA for specific preanalytic variables that may be used as a guide to develop best practices for implementation into patient care and/or research biorepository processes.

Piloting an approach to rapid and automated assessment of a new research initiative: Application to the National Cancer Institute's Provocative Questions initiative.

Funders of biomedical research are often challenged to understand how a new funding initiative fits within the agency's portfolio and the larger research community. While traditional assessment relies on retrospective review by subject matter experts, it is now feasible to design portfolio assessment and gap analysis tools leveraging administrative and grant application data that can be used for early and continued analysis. We piloted such methods on the National Cancer Institute's Provocative Questions (PQ) initiative to address key questions regarding diversity of applicants; whether applicants were proposing new avenues of research; and whether grant applications were filling portfolio gaps. For the latter two questions, we defined measurements called focus shift and relevance, respectively, based on text similarity scoring. We demonstrate that two types of applicants were attracted by the PQs at rates greater than or on par with the general National Cancer Institute applicant pool: those with clinical degrees and new investigators. Focus shift scores tended to be relatively low, with applicants not straying far from previous research, but the majority of applications were found to be relevant to the PQ the application was addressing. Sensitivity to comparison text and inability to distinguish subtle scientific nuances are the primary limitations of our automated approaches based on text similarity, potentially biasing relevance and focus shift measurements. We also discuss potential uses of the relevance and focus shift measures including the design of outcome evaluations, though further experimentation and refinement are needed for a fuller understanding of these measures before broad application.

High-throughput, quantitative analysis of acrolein-derived DNA adducts in human oral cells by immunohistochemistry.

Acrolein (Acr) is a ubiquitous environmental pollutant as well as an endogenous compound. Acrolein-derived 1,N(2)-propanodeoxyguanosines (Acr-dG) are exocyclic DNA adducts formed following exposure to cigarette smoke or from lipid peroxidation. Acr-dG is mutagenic and potentially carcinogenic and may represent a useful biomarker for the early detection of cancers related to smoking or other oxidative conditions, such as chronic inflammation. In this study, we have developed a high-throughput, automated method using a HistoRx PM-2000 imaging system combined with MetaMorph software for quantifying Acr-dG adducts in human oral cells by immunohistochemical detection using a monoclonal antibody recently developed by our laboratory. This method was validated in a cell culture system using BEAS-2B human bronchial epithelial cells treated with known concentrations of Acr. The results were further verified by quantitative analysis of Acr-dG in DNA of BEAS-2B cells using a liquid chromatography/tandem mass spectrometry/multiple-reaction monitoring method. The automated method is a quicker, more accurate method than manual evaluation of counting cells expressing Acr-dG and quantifying fluorescence intensity. It may be applied to other antibodies that are used for immunohistochemical detection in tissues as well as cell lines, primary cultures, and other cell types.

Dietary methyl donor depletion protects against intestinal tumorigenesis in Apc(Min/+) mice.

Despite recent population data, the influence of dietary folate supplementation on colon cancer risk remains controversial. This study examines the effects of folate deficiency, in combination with choline, methionine, and vitamin B12 depletion, on intestinal tumorigenesis in Apc(Min/+) mice. Methyl donor sufficient (MDS) and deficient (MDD) diets were started at five or 10 weeks of age and tumors evaluated at 16 weeks. MDD suppressed intestinal tumor formation in Apc(Min/+) mice (~80%) when started at five weeks of age. The protective effect was lost when MDD was initiated at 10 weeks of age, indicating an important time dependency on cancer suppression. Concomitant with cancer protection, MDD restricted body weight gain. Therefore, a second study was conducted in which MDS was given ad libitum or pair-fed with MDD. Although small intestinal tumors were reduced 54% in pair-fed MDS mice, MDD caused a further reduction (96%). In colon, although MDD did not affect tumor numbers, tumor size was reduced. Gene expression profiling of normal-appearing colonic mucosa after 11 weeks on MDD identified a total of 493 significantly downregulated genes relative to the MDS group. Pathway analysis placed many of these genes within general categories of inflammatory signaling and cell-cycle regulation, consistent with recently published human data obtained during folate depletion. Further studies are warranted to investigate the complex interplay of methyl donor status and cancer protection in high-risk populations.

Ibuprofen inhibits activation of nuclear {beta}-catenin in human colon adenomas and induces the phosphorylation of GSK-3{beta}.

Nonselective cyclooxygenase (COX) inhibitors target many of the same cancer-associated molecular pathways as COX-2-specific inhibitors. Although these nonsteroidal anti-inflammatory drugs (NSAIDs) are often associated with gastrointestinal toxicity, there is renewed interest in their use as colorectal cancer (CRC) chemopreventive agents due to the adverse side effects associated with long-term use of selective COX-2 inhibitors. In this study, we investigated the effects of long-term use (up to 25 years) of NSAIDs (ibuprofen or aspirin) on adenoma pathology and ß-catenin-mediated signaling in sporadic human colon adenomas. Although NSAID use did not impact overall adenoma size or degree of dysplasia, it did cause a significant inhibition of nuclear ß-catenin localization, which correlated with suppression of cyclin D1 expression. To further elucidate the effect of these agents in regulating ß-catenin, we treated SW480 colon cancer cells with a panel of NSAIDs and determined their effects on ß-catenin levels and cellular localization. In agreement with our in vivo results, both S-ibuprofen and aspirin were found to decrease total levels of ß-catenin while increasing its phosphorylation. In addition, S-ibuprofen induced both degradation of IκBα and nuclear localization of NF-κB. Despite its nuclear localization, however, the activation of the NF-κB target genes, Bcl-2, survivin, and cyclin D1, was suppressed. This reduction in NF-κB transcriptional activity may be due to increased phosphorylation of GSK-3ß following S-ibuprofen treatment. These data suggest that ibuprofen can effectively target both the Wnt/ß-catenin and NF-κB pathways, and potentially uncovers a novel mechanism through which NSAIDS may exert their chemopreventive efficacy.

Molecular alterations associated with sulindac-resistant colon tumors in ApcMin/+ mice.

Although nonsteroidal anti-inflammatory drugs (NSAID), including sulindac, have been used extensively as chemopreventive agents for colorectal cancer, results are not consistent. NSAIDs, most reportedly sulindac, often do not cause a complete regression of adenomas and some patients develop resistance to NSAID treatment. In this study, we evaluated the effect of sulindac on colon tumorigenesis in the Apc(Min/+) mouse model. Sulindac (180 ppm) given in drinking water for 9 weeks to Apc(Min/+) mice significantly reduced the size of colon tumors, but actually caused an increase in colon tumor multiplicity relative to untreated controls (average of 5.5 versus 1.6 tumors per mouse, respectively; P < 0.0001). This indicated that the drug could inhibit colon tumor progression but not initiation. As expected, in the small intestine, sulindac significantly reduced tumor size and multiplicity relative to untreated controls (average of 2.3 versus 42.0 tumors per mouse, respectively; P < 0.0001). Generation of a panel of prostanoids was comparably suppressed in the small intestine and colon by sulindac treatment. Sulindac is also known to exert its growth inhibitory effects through regulation of many noncyclooxygenase targets, including p21, beta-catenin, E-cadherin, mitochondrial apoptotic proteins, and peroxisome proliferator-activated receptor-gamma. We found that sulindac treatment protected against E-cadherin loss in colon tumors, with associated inhibition of nuclear beta-catenin accumulation. Importantly, p21(WAF1/cip1) and peroxisome proliferator-activated receptor-gamma expression were absent in colon tumors from sulindac-treated mice, suggesting that loss of these proteins is necessary for drug resistance. Together, these observations may be translatable to designing novel clinical therapies using combinations of agents that target multiple molecular pathways to overcome sulindac resistance.

Mutations in BRAF and KRAS differentially distinguish serrated versus non-serrated hyperplastic aberrant crypt foci in humans.

We previously reported that colon carcinomas, adenomas, and hyperplastic polyps exhibiting a serrated histology were very likely to possess BRAF mutations, whereas when these same advanced colonic lesions exhibited non-serrated histology, they were wild type for BRAF; among hyperplastic polyps, KRAS mutations were found mainly in a non-serrated variant. On this basis, we predicted that hyperplastic aberrant crypt foci (ACF), a putative precancerous lesion found in the colon, exhibiting a serrated phenotype would also harbor BRAF mutations and that non-serrated ACF would not. In contrast, KRAS mutations would be found more often in the non-serrated ACF. We examined 55 ACF collected during screening colonoscopy from a total of 28 patients. Following laser capture microdissection, DNA was isolated, and mutations in BRAF and KRAS were determined by direct PCR sequencing. When hyperplastic lesions were further classified into serrated and non-serrated histologies, there was a strong inverse relationship between BRAF and KRAS mutations: a BRAF(V600E) mutation was identified in 10 of 16 serrated compared with 1 of 33 non-serrated lesions (P = 0.001); conversely, KRAS mutations were present in 3 of 16 serrated compared with 14 of 33 non-serrated lesions. Our finding of a strong association between BRAF mutations and serrated histology in hyperplastic ACF supports the idea that these lesions are an early, sentinel, or a potentially initiating step on the serrated pathway to colorectal carcinoma.

Microsatellite instability in aberrant crypt foci from patients without concurrent colon cancer.

Aberrant crypt foci (ACF) are microscopic surface abnormalities that are putative precursors to colorectal cancer (CRC). ACF exhibit similar histological and molecular abnormalities to adenomas and CRC and potentially represent useful biomarkers of cancer risk. Microsatellite instability (MSI) is one molecular abnormality identified in concurrent ACF from CRC patients that may indicate a risk for progression. To determine if MSI can be detected in ACF from cancer-free subjects, we examined 45 ACF from 20 subjects undergoing colonoscopies. The group included 12 patients at elevated risk for CRC based on family history of CRC or personal history of CRC or advanced adenoma and 8 patients with no known risk factors. ACF were identified using close-focus magnifying chromendoscopy and collected by biopsy in situ. Genomic DNA was prepared from ACF and adjacent normal colonic epithelium isolated by laser capture microdissection and analyzed for MSI. MSI was identified in at least one marker from 9 of 30 (30%) lesions from patients at elevated risk for CRC and in 2 of 15 (13%) lesions from average risk patients. Using methylation-specific PCR analysis, we also examined the ACF for promoter hypermethylation of the DNA repair genes hMLH1 and MGMT and found moderate changes (8/39 and 3/32, respectively). Although we found only a limited relationship between hMLH1 hypermethylation and MSI, all the lesions with MGMT hypermethylation displayed an MSI-low phenotype. These lesions may be precursors to MSI-low CRC, providing a potential early biomarker to assess the effects of cancer prevention strategies.

Epigenetic alterations in RASSF1A in human aberrant crypt foci.

CpG island methylation (CIM) is an epigenetic mechanism for transcriptional silencing that occurs at various stages of colon tumorigenesis. CIM has been found in serrated adenomas and hyperplastic polyps. There is also evidence for hypermethylation in aberrant crypt foci (ACF) that are found in resected colons from cancer patients. Our study addresses promoter methylation of a tumor suppressor gene, RASSF1A, within the colonic epithelium of subjects undergoing screening colonoscopies in the absence of synchronous tumors. Patients included in this study were at elevated risk for colorectal cancer (CRC) based on family history, but without a previously occurring or synchronous colon carcinoma. ACF were identified using close-focus magnifying chromendoscopy and collected by biopsy in situ. We isolated ACF and adjacent normal colonic epithelium by laser capture microdissection (LCM) and studied methylation of the RASSF1A promoter region in ACF and in adjacent normal mucosa. Expression of RASSF1A was verified using quantitative real-time polymerase chain reaction (QRT-PCR). We found that 8.6% (3 out of 35) of ACF had K-ras mutations and 24% (6 out of 25) had RASSF1A hypermethylation. Our results demonstrate that RASSF1A hypermethylation and K-ras mutations are not mutually exclusive and are present in patients at elevated risk of CRC. Importantly, CIM of RASSF1A is an early epigenetic aberration, occurring in the absence of synchronous colon tumors and is not accompanied by field effects into the surrounding epithelium.