Next-Generation Machine Learning for Biological Networks.

Machine learning, a collection of data-analytical techniques aimed at building predictive models from multi-dimensional datasets, is becoming integral to modern biological research. By enabling one to generate models that learn from large datasets and make predictions on likely outcomes, machine learning can be used to study complex cellular systems such as biological networks. Here, we provide a primer on machine learning for life scientists, including an introduction to deep learning. We discuss opportunities and challenges at the intersection of machine learning and network biology, which could impact disease biology, drug discovery, microbiome research, and synthetic biology.

PRDM paralogs antagonistically balance Wnt/ß-catenin activity during craniofacial chondrocyte differentiation.

Cranial neural crest cell (NCC)-derived chondrocyte precursors undergo a dynamic differentiation and maturation process to establish a scaffold for subsequent bone formation, alterations in which contribute to congenital birth defects. Here, we demonstrate that transcription factor and histone methyltransferase proteins Prdm3 and Prdm16 control the differentiation switch of cranial NCCs to craniofacial cartilage. Loss of either paralog results in hypoplastic and disorganized chondrocytes due to impaired cellular orientation and polarity. We show that these proteins regulate cartilage differentiation by controlling the timing of Wnt/ß-catenin activity in strikingly different ways: Prdm3 represses whereas Prdm16 activates global gene expression, although both act by regulating Wnt enhanceosome activity and chromatin accessibility. Finally, we show that manipulating Wnt/ß-catenin signaling pharmacologically or generating prdm3-/-;prdm16-/- double mutants rescues craniofacial cartilage defects. Our findings reveal upstream regulatory roles for Prdm3 and Prdm16 in cranial NCCs to control Wnt/ß-catenin transcriptional activity during chondrocyte differentiation to ensure proper development of the craniofacial skeleton.

Habitat escalated adaptive therapy (HEAT): a phase 2 trial utilizing radiomic habitat-directed and genomic-adjusted radiation dose (GARD) optimization for high-grade soft tissue sarcoma.

BACKGROUND: Soft tissue sarcomas (STS), have significant inter- and intra-tumoral heterogeneity, with poor response to standard neoadjuvant radiotherapy (RT). Achieving a favorable pathologic response (FPR ≥ 95%) from RT is associated with improved patient outcome. Genomic adjusted radiation dose (GARD), a radiation-specific metric that quantifies the expected RT treatment effect as a function of tumor dose and genomics, proposed that STS is significantly underdosed. STS have significant radiomic heterogeneity, where radiomic habitats can delineate regions of intra-tumoral hypoxia and radioresistance. We designed a novel clinical trial, Habitat Escalated Adaptive Therapy (HEAT), utilizing radiomic habitats to identify areas of radioresistance within the tumor and targeting them with GARD-optimized doses, to improve FPR in high-grade STS. METHODS: Phase 2 non-randomized single-arm clinical trial includes non-metastatic, resectable high-grade STS patients. Pre-treatment multiparametric MRIs (mpMRI) delineate three distinct intra-tumoral habitats based on apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) sequences. GARD estimates that simultaneous integrated boost (SIB) doses of 70 and 60 Gy in 25 fractions to the highest and intermediate radioresistant habitats, while the remaining volume receives standard 50 Gy, would lead to a > 3 fold FPR increase to 24%. Pre-treatment CT guided biopsies of each habitat along with clip placement will be performed for pathologic evaluation, future genomic studies, and response assessment. An mpMRI taken between weeks two and three of treatment will be used for biological plan adaptation to account for tumor response, in addition to an mpMRI after the completion of radiotherapy in addition to pathologic response, toxicity, radiomic response, disease control, and survival will be evaluated as secondary endpoints. Furthermore, liquid biopsy will be performed with mpMRI for future ancillary studies. DISCUSSION: This is the first clinical trial to test a novel genomic-based RT dose optimization (GARD) and to utilize radiomic habitats to identify and target radioresistance regions, as a strategy to improve the outcome of RT-treated STS patients. Its success could usher in a new phase in radiation oncology, integrating genomic and radiomic insights into clinical practice and trial designs, and may reveal new radiomic and genomic biomarkers, refining personalized treatment strategies for STS. TRIAL REGISTRATION: NCT05301283. TRIAL STATUS: The trial started recruitment on March 17, 2022.

Stereotactic body radiotherapy plus rucosopasem in locally advanced or borderline resectable pancreatic cancer: GRECO-2 phase II study design.

Ablative doses of stereotactic body radiotherapy (SBRT) may improve pancreatic cancer outcomes but may carry greater potential for gastrointestinal toxicity. Rucosopasem, an investigational selective dismutase mimetic that converts superoxide to hydrogen peroxide, can potentially increase tumor control of SBRT without compromising safety. GRECO-2 is a phase II, multicenter, randomized, double-blind, placebo-controlled trial of rucosopasem in combination with SBRT in locally advanced or borderline resectable pancreatic cancer. Patients will be randomized to rucosopasem 100 mg or placebo via intravenous infusion over 15 min, before each SBRT fraction (5 × 10 Gy). The primary end point is overall survival. Secondary end points include progression-free survival, locoregional control, time to metastasis, surgical resection rate, best overall response, in-field local response and acute and long-term toxicity.

The use of high doses of radiation delivered directly to tumors (stereotactic body radiation therapy [SBRT]) may improve survival compared with lower doses of radiation in patients with pancreatic cancer, but it may increase side effects. Rucosopasem, an investigational new drug being developed, can potentially improve the ability of SBRT to treat tumors without decreasing safety. In a previous study, median overall survival was improved when patients were treated with SBRT plus avasopasem, a drug that works the same way as rucosopasem. GRECO-2 is a clinical trial of rucosopasem used in combination with SBRT for treatment of localized pancreatic cancer. Patients will be randomly selected to receive either rucosopasem 100 mg or placebo via intravenous infusion over 15 min, before each SBRT treatment. The main result being studied is overall survival. Additional results include amount of time before tumors start to grow, how often patients get tumors surgically removed, best overall response and long-term safety. Clinical Trial Registration: NCT04698915 (ClinicalTrials.gov).

Stereotactic body radiotherapy with or without selective dismutase mimetic in pancreatic adenocarcinoma: an adaptive, randomised, double-blind, placebo-controlled, phase 1b/2 trial.

BACKGROUND: Stereotactic body radiotherapy (SBRT) has the potential to ablate localised pancreatic ductal adenocarcinoma. Selective dismutase mimetics sensitise tumours while reducing normal tissue toxicity. This trial was designed to establish the efficacy and toxicity afforded by the selective dismutase mimetic avasopasem manganese when combined with ablative SBRT for localised pancreatic ductal adenocarcinoma. METHODS: In this adaptive, randomised, double-blind, placebo-controlled, phase 1b/2 trial, patients aged 18 years or older with borderline resectable or locally advanced pancreatic cancer who had received at least 3 months of chemotherapy and had an Eastern Cooperative Oncology Group performance status of 0-2 were enrolled at six academic sites in the USA. Eligible patients were randomly assigned (1:1), with block randomisation (block sizes of 6-12) with a maximum of 24 patients per group, to receive daily avasopasem (90 mg) or placebo intravenously directly before (ie, within 180 min) SBRT (50, 55, or 60 Gy in five fractions, adaptively assigned in real time by Bayesian estimates of 90-day safety and efficacy). Patients and physicians were masked to treatment group allocation, but not to SBRT dose. The primary objective was to find the optimal dose of SBRT with avasopasem or placebo as determined by the late onset EffTox method. All analyses were done on an intention-to-treat basis. This study is registered with ClinicalTrials.gov, NCT03340974, and is complete. FINDINGS: Between Jan 25, 2018, and April 29, 2020, 47 patients were screened, of whom 42 were enrolled (median age was 71 years [IQR 63-75], 23 [55%] were male, 19 [45%] were female, 37 [88%] were White, three [7%] were Black, and one [2%] each were unknown or other races) and randomly assigned to avasopasem (n=24) or placebo (n=18); the placebo group was terminated early after failing to meet prespecified efficacy parameters. At data cutoff (June 28, 2021), the avasopasem group satisfied boundaries for both efficacy and toxicity. Late onset EffTox efficacy response was observed in 16 (89%) of 18 patients at 50 Gy and six (100%) of six patients at 55 Gy in the avasopasem group, and was observed in three (50%) of six patients at 50 Gy and nine (75%) of 12 patients at 55 Gy in the placebo group, and the Bayesian model recommended 50 Gy or 55 Gy in five fractions with avasopasem for further study. Serious adverse events of any cause were reported in three (17%) of 18 patients in the placebo group and six (25%) of 24 in the avasopasem group. In the placebo group, grade 3 adverse events within 90 days of SBRT were abdominal pain, acute cholangitis, pyrexia, increased blood lactic acid, and increased lipase (one [6%] each); no grade 4 events occurred. In the avasopasem group, grade 3-4 adverse events within 90 days of SBRT were acute kidney injury, increased blood alkaline phosphatase, haematoma, colitis, gastric obstruction, lung infection, abdominal abscess, post-surgical atrial fibrillation, and pneumonia leading to respiratory failure (one [4%] each).There were no treatment-related deaths but one late death in the avasopasem group due to sepsis in the setting of duodenal obstruction after off-study treatment was reported as potentially related to SBRT. INTERPRETATION: SBRT that uses 50 or 55 Gy in five fractions can be considered for patients with localised pancreatic ductal adenocarcinoma. The addition of avasopasem might further enhance disease outcomes. A larger phase 2 trial (GRECO-2, NCT04698915) is underway to validate these results. FUNDING: Galera Therapeutics.

Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations.

Radiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell-level) phenomena. Nevertheless, to examine the causes of frequent fast fluctuations in tissue oxygenation, models simulating individual cells' behavior are needed. Here, we provide a link between the average data values recorded for radiologic images and the cellular and vascular architecture of the corresponding tissues. Using hybrid agent-based modeling, we generate a set of tissue morphologies capable of reproducing oxygenation levels observed in radiologic images. We then use these in silico tissues to investigate whether oxygen fluctuations can be explained by changes in vascular oxygen supply or by modulations in cellular oxygen absorption. Our studies show that intravascular changes in oxygen supply reproduce the observed fluctuations in tissue oxygenation in all considered regions of interest. However, larger-magnitude fluctuations cannot be recreated by modifications in cellular absorption of oxygen in a biologically feasible manner. Additionally, we develop a procedure to identify plausible tissue morphologies for a given temporal series of average data from radiology images. In future applications, this approach can be used to generate a set of tissues comparable with radiology images and to simulate tumor responses to various anti-cancer treatments at the tissue-scale level.

Crowdsourcing biomedical research: leveraging communities as innovation engines.

The generation of large-scale biomedical data is creating unprecedented opportunities for basic and translational science. Typically, the data producers perform initial analyses, but it is very likely that the most informative methods may reside with other groups. Crowdsourcing the analysis of complex and massive data has emerged as a framework to find robust methodologies. When the crowdsourcing is done in the form of collaborative scientific competitions, known as Challenges, the validation of the methods is inherently addressed. Challenges also encourage open innovation, create collaborative communities to solve diverse and important biomedical problems, and foster the creation and dissemination of well-curated data repositories.

High-Content Drug Discovery Targeting Molecular Bladder Cancer Subtypes.

Molecular subtypes of muscle-invasive bladder cancer (MIBC) display differential survival and drug sensitivities in clinical trials. To date, they have not been used as a paradigm for phenotypic drug discovery. This study aimed to discover novel subtype-stratified therapy approaches based on high-content screening (HCS) drug discovery. Transcriptome expression data of CCLE and BLA-40 cell lines were used for molecular subtype assignment in basal, luminal, and mesenchymal-like cell lines. Two independent HCSs, using focused compound libraries, were conducted to identify subtype-specific drug leads. We correlated lead drug sensitivity data with functional genomics, regulon analysis, and in-vitro drug response-based enrichment analysis. The basal MIBC subtype displayed sensitivity to HDAC and CHK inhibitors, while the luminal subtype was sensitive to MDM2 inhibitors. The mesenchymal-like cell lines were exclusively sensitive to the ITGAV inhibitor SB273005. The role of integrins within this mesenchymal-like MIBC subtype was confirmed via its regulon activity and gene essentiality based on CRISPR-Cas9 knock-out data. Patients with high ITGAV expression showed a significant decrease in the median overall survival. Phenotypic high-content drug screens based on bladder cancer cell lines provide rationales for novel stratified therapeutic approaches as a framework for further prospective validation in clinical trials.

Heterogeneity analysis of MRI T2 maps for measurement of early tumor response to radiotherapy.

External beam radiotherapy (XRT) is a widely used cancer treatment, yet responses vary dramatically among patients. These differences are not accounted for in clinical practice, partly due to a lack of sensitive early response biomarkers. We hypothesize that quantitative magnetic resonance imaging (MRI) measures reflecting tumor heterogeneity can provide a sensitive and robust biomarker of early XRT response. MRI T2 mapping was performed every 72 hours following 10 Gy dose XRT in two models of pancreatic cancer propagated in the hind limb of mice. Interquartile range (IQR) of tumor T2 was presented as a potential biomarker of radiotherapy response compared with tumor growth kinetics, and biological validation was performed through quantitative histology analysis. Quantification of tumor T2 IQR showed sensitivity for detection of XRT-induced tumor changes 72 hours after treatment, outperforming T2-weighted and diffusion-weighted MRI, with very good robustness. Histological comparison revealed that T2 IQR provides a measure of spatial heterogeneity in tumor cell density, related to radiation-induced necrosis. Early IQR changes were found to correlate to subsequent tumor volume changes, indicating promise for treatment response prediction. Our preclinical findings indicate that spatial heterogeneity analysis of T2 MRI can provide a translatable method for early radiotherapy response assessment. We propose that the method may in future be applied for personalization of radiotherapy through adaptive treatment paradigms.

Metastatic cells are preferentially vulnerable to lysosomal inhibition.

Molecular alterations that confer phenotypic advantages to tumors can also expose specific therapeutic vulnerabilities. To search for potential treatments that would selectively affect metastatic cells, we examined the sensitivity of lineage-related human bladder cancer cell lines with different lung colonization abilities to chloroquine (CQ) or bafilomycin A1, which are inhibitors of lysosome function and autophagy. Both CQ and bafilomycin A1 were more cytotoxic in vitro to highly metastatic cells compared with their less metastatic counterparts. Genetic inactivation of macroautophagy regulators and lysosomal proteins indicated that this was due to greater reliance on the lysosome but not upon macroautophagy. To identify the mechanism underlying these effects, we generated cells resistant to CQ in vitro. Surprisingly, selection for in vitro CQ resistance was sufficient to alter gene expression patterns such that unsupervised cluster analysis of whole-transcriptome data indicated that selection for CQ resistance alone created tumor cells that were more similar to the poorly metastatic parental cells from which the metastatic cells were derived; importantly, these tumor cells also had diminished metastatic ability in vivo. These effects were mediated in part by differential expression of the transcriptional regulator ID4 (inhibitor of DNA binding 4); depletion of ID4 both promoted in vitro CQ sensitivity and restored lung colonization and metastasis of CQ-resistant cells. These data demonstrate that selection for metastasis ability confers selective vulnerability to lysosomal inhibitors and identify ID4 as a potential biomarker for the use of lysosomal inhibitors to reduce metastasis in patients.

GSEA-InContext: identifying novel and common patterns in expression experiments.

Motivation: Gene Set Enrichment Analysis (GSEA) is routinely used to analyze and interpret coordinate pathway-level changes in transcriptomics experiments. For an experiment where less than seven samples per condition are compared, GSEA employs a competitive null hypothesis to test significance. A gene set enrichment score is tested against a null distribution of enrichment scores generated from permuted gene sets, where genes are randomly selected from the input experiment. Looking across a variety of biological conditions, however, genes are not randomly distributed with many showing consistent patterns of up- or down-regulation. As a result, common patterns of positively and negatively enriched gene sets are observed across experiments. Placing a single experiment into the context of a relevant set of background experiments allows us to identify both the common and experiment-specific patterns of gene set enrichment. Results: We compiled a compendium of 442 small molecule transcriptomic experiments and used GSEA to characterize common patterns of positively and negatively enriched gene sets. To identify experiment-specific gene set enrichment, we developed the GSEA-InContext method that accounts for gene expression patterns within a background set of experiments to identify statistically significantly enriched gene sets. We evaluated GSEA-InContext on experiments using small molecules with known targets to show that it successfully prioritizes gene sets that are specific to each experiment, thus providing valuable insights that complement standard GSEA analysis. Availability and implementation: GSEA-InContext implemented in Python, Supplementary results and the background expression compendium are available at: https://github.com/CostelloLab/GSEA-InContext.

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.

BACKGROUND: Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. METHODS: Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. FINDINGS: 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39-4·62, p<0·0001; reference model: 2·56, 1·85-3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified predictive clinical variables and revealed aspartate aminotransferase as an important, albeit previously under-reported, prognostic biomarker. INTERPRETATION: Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer. FUNDING: Sanofi US Services, Project Data Sphere.

Accuracy of Unenhanced MR Imaging in the Detection of Acute Appendicitis: Single-Institution Clinical Performance Review.

PURPOSE: To determine the accuracy of unenhanced magnetic resonance (MR) imaging in the detection of acute appendicitis in patients younger than 50 years who present to the emergency department with right lower quadrant (RLQ) pain. MATERIALS AND METHODS: The institutional review board approved this retrospective study of 403 patients from August 1, 2012, to July 30, 2014, and waived the informed consent requirement. A cross-department strategy was instituted to use MR imaging as the primary diagnostic modality in patients aged 3-49 years who presented to the emergency department with RLQ pain. All MR examinations were performed with a 1.5- or 3.0-T system. Images were acquired without breath holding by using multiplanar half-Fourier single-shot T2-weighted imaging without and with spectral adiabatic inversion recovery fat suppression without oral or intravenous contrast material. MR imaging room time was measured for each patient. Prospective image interpretations from clinical records were reviewed to document acute appendicitis or other causes of abdominal pain. Final clinical outcomes were determined by using (a) surgical results (n = 77), (b) telephone follow-up combined with review of the patient's medical records (n = 291), or (c) consensus expert panel assessment if no follow-up data were available (n = 35). Logistic regression analysis was performed to evaluate the sensitivity and specificity of MR imaging in the detection of acute appendicitis, and corresponding 95% confidence intervals were determined. RESULTS: Of the 403 patients, 67 had MR imaging findings that were positive for acute appendicitis, and 336 had negative findings. MR imaging had a sensitivity of 97.0% (65 of 67) and a specificity of 99.4% (334 of 336). The mean total room time was 14 minutes (range, 8-62 minutes). An alternate diagnosis was offered in 173 (51.5%) of 336 patients. CONCLUSION: MR imaging is a highly sensitive and specific test in the evaluation of patients younger than 50 years with acute RLQ pain that uses a rapid imaging protocol performed without intravenous or oral contrast material.

Differential splicing across immune system lineages.

Alternative splicing (AS) allows increased diversity and orthogonal regulation of the transcriptional products of mammalian genomes. To assess the distribution and variation of alternative splicing across cell lineages of the immune system, we comprehensively analyzed RNA sequencing and microarray data generated by the Immunological Genome Project Consortium. AS is pervasive: 60% of genes showed frequent AS isoforms in T or B lymphocytes, with 7,599 previously unreported isoforms. Distinct cell specificity was observed, with differential exon skipping in 5% of genes otherwise coexpressed in both B and T cells. The distribution of isoforms was mostly all or none, suggesting on/off switching as a frequent mode of AS regulation in lymphocytes. From the identification of differential exon use in the microarray data, clustering of exon inclusion/exclusion patterns across all Immunological Genome Project cell types showed that ∼70% of AS exons are distributed along a common pattern linked to lineage differentiation and cell cycling. Other AS events distinguished myeloid from lymphoid cells or affected only a small set of exons without clear lineage specificity (e.g., Ptprc). Computational analysis predicted specific associations between AS exons and splicing regulators, which were verified by detection of the hnRPLL/Ptprc connection.

The hydrolysis of geminal ethers: a kinetic appraisal of orthoesters and ketals.

A novel approach to protecting jet fuel against the effects of water contamination is predicated upon the coupling of the rapid hydrolysis reactions of lipophilic cyclic geminal ethers, with the concomitant production of a hydrophilic acyclic hydroxyester with de-icing properties (Fuel Dehydrating Icing Inhibitors - FDII). To this end, a kinetic appraisal of the hydrolysis reactions of representative geminal ethers was undertaken using a convenient surrogate for the fuel-water interface (D2O/CD3CN 1:4). We present here a library of acyclic and five/six-membered cyclic geminal ethers arranged according to their hydroxonium catalytic coefficients for hydrolysis, providing for the first time a framework for the development of FDII. A combination of (1)H NMR, labelling and computational studies was used to assess the effects that may govern the observed relative rates of hydrolyses.

Wisdom of crowds for robust gene network inference.

Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus, each comprising ~1,700 transcriptional interactions at a precision of ~50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli, of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.

ProstaMine: a bioinformatics tool for identifying subtype-specific co-alterations associated with aggressiveness in prostate cancer.

Background: Prostate cancer is a leading cause of cancer-related deaths among men, marked by heterogeneous clinical and molecular characteristics. The complexity of the molecular landscape necessitates tools for identifying multi-gene co-alteration patterns that are associated with aggressive disease. The identification of such gene sets will allow for deeper characterization of the processes underlying prostate cancer progression and potentially lead to novel strategies for treatment. Methods: We developed ProstaMine to systematically identify co-alterations associated with aggressiveness in prostate cancer molecular subtypes defined by high-fidelity alterations in primary prostate cancer. ProstaMine integrates genomic, transcriptomic, and clinical data from five primary and one metastatic prostate cancer cohorts to prioritize co-alterations enriched in metastatic disease and associated with disease progression. Results: Integrated analysis of primary tumors defined a set of 17 prostate cancer alterations associated with aggressive characteristics. We applied ProstaMine to NKX3-1-loss and RB1-loss tumors and identified subtype-specific co-alterations associated with metastasis and biochemical relapse in these molecular subtypes. In NKX3-1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations known to regulate prostate cancer signaling pathways including MAPK, NF-kB, p53, PI3K, and Sonic hedgehog. In RB1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations involved in p53, STAT6, and MHC class I antigen presentation. Co-alterations impacting autophagy were noted in both molecular subtypes. Conclusion: ProstaMine is a method to systematically identify novel subtype-specific co-alterations associated with aggressive characteristics in prostate cancer. The results from ProstaMine provide insights into potential subtype-specific mechanisms of prostate cancer progression which can be formed into testable experimental hypotheses. ProstaMine is publicly available at: https://bioinformatics.cuanschutz.edu/prostamine.

Magnetic resonance imaging of tumor response to stroma-modifying pegvorhyaluronidase alpha (PEGPH20) therapy in early-phase clinical trials.

Pre-clinical and clinical studies have shown that PEGPH20 depletes intratumoral hyaluronic acid (HA), which is linked to high interstitial fluid pressures and poor distribution of chemotherapies. 29 patients with metastatic advanced solid tumors received quantitative magnetic resonance imaging (qMRI) in 3 prospective clinical trials of PEGPH20: HALO-109-101 (NCT00834704), HALO-109-102 (NCT01170897), and HALO-109-201 (NCT01453153). Apparent Diffusion Coefficient of water (ADC), T1, ktrans, vp, ve, and iAUC maps were computed from qMRI acquired at baseline and ≥ 1 time point post-PEGPH20. Tumor ADC and T1 decreased, while iAUC, ktrans, vp, and ve increased, on day 1 post-PEGPH20 relative to baseline values. This is consistent with HA depletion leading to a decrease in tumor extracellular water content and an increase in perfusion, permeability, extracellular matrix space, and vascularity. Baseline parameter values predictive of pharmacodynamic responses were: ADC > 1.46 × 10-3 mm2/s (Balanced Accuracy (BA) = 72%, p < 0.01), T1 > 0.54 s (BA = 82%, p < 0.01), iAUC < 9.2 mM-s (BA = 76%, p < 0.05), ktrans < 0.07 min-1 (BA = 72%, p = 0.2), ve < 0.17 (BA = 68%, p < 0.01), and vp < 0.02 (BA = 60%, p < 0.01). A low ve at baseline was moderately predictive of response in any parameter (BA = 65.6%, p < 0.01 averaged across patients). These qMRI biomarkers are potentially useful for guiding patient pre-selection and post-treatment follow-up in future clinical studies of PEGPH20 and other tumor stroma-modifying anti-cancer therapies.

The role of rectal magnetic resonance imaging in accurate localization and designation of colorectal cancer for optimal management: Case study.

Colorectal cancer, developing from malignant transformation of the distal gut epithelium, is the second leading cause of cancer death in the United States. We present a gentleman in his 60s who was diagnosed with colorectal cancer during a routine screening colonoscopy with no evidence of distant metastasis on subsequent staging with positron emission tomography and computed tomography (PET-CT). The outside rectal MR (magnetic resonance) imaging report localized a mass to the upper rectum. Review of the MRI at an institutional, Multidisciplinary Tumor Board designated the tumor as "rectosigmoid," straddling the rectosigmoid junction at the level of the "sigmoid take-off" (STO) or alternatively at the level of the last sigmoid artery take-off (SAT) at the origin of the superior rectal artery. The anatomic differentiation between upper rectal and lower sigmoid colon cancers carries clinical importance which is highlighted in this case report and brief literature review. Optimal anatomic localization of colorectal cancers helps direct the clinical team to tailor an individualized patient care plan.

E-cadherin expression and gene expression profiles in corticotroph pituitary neuroendocrine tumor subtypes.

Corticotroph adenomas/pituitary neuroendocrine tumors (PitNETs) are associated with significant morbidity and mortality. Predictors of tumor behavior have not shown high prognostic accuracy. For somatotroph adenomas/PitNETs, E-cadherin expression correlates strongly with prognosis. E-cadherin expression has not been investigated in other PitNETs. A retrospective chart review of adults with corticotroph adenomas/PitNETs was conducted to assess correlation between E-cadherin expression and tumor characteristics. In addition, gene expression microarray was performed in subset of tumors (n = 16). Seventy-seven patients were identified; 71% were female, with median age of cohort 45.2 years. Seventy-five percent had macroadenomas, of which 22% were hormonally active. Ninety-five percent of microadenomas were hormonally active. Adrenocorticotropic hormone granulation pattern by IHC identified 63% as densely granulated (DG) and 34% as sparsely granulated (SG). All microadenomas were DG (p < .001); 50% of macroadenomas were DG associated with increased tumor invasion compared to SG. E-cadherin IHC was positive in 80%, diminished in 17%, and absent in 20% and did not correlate with corticotroph PitNETs subtype, size, or prognosis. In contrast to the distinct transcriptomes of corticotroph PitNETs and normal pituitaries, a comparison of clinically active and silent corticotroph PitNETs demonstrated similar molecular signatures indicating their common origin, but with unique differences related to their secretory status.