Hypoxia Informed RBE-Weighted Beam Orientation Optimization for Intensity Modulated Proton Therapy Using [18F]-FMISO-PET Estimation of pO2

PURPOSE/OBJECTIVE(S)

Variable relative biological effectiveness (RBE) models have previously informed proton therapy dose optimization algorithms, but few models have incorporated hypoxia's increase on radioresistance. Here, we obtain voxel-based estimation of partial oxygen pressure to weigh RBE values in a single biologically informed beam orientation optimization (BOO) algorithm.

MATERIALS/METHODS

Four brain cancer patients with [18F]-FMISO-PET/CT images were selected from an HCP database. Oxygen values were derived from tracer uptake using a non-linear least squares curve fitting. RBE dose was then weighted using oxygen enhancement ratios (OER) for each structure and substituted into the dose fidelity term of our BOO algorithm. The nonlinear optimization problem was solved using a split-Bregman approach, with FISTA as the solver. This method (HypRBE) was compared dose fidelity terms using the Rorvik RBE model (RegRBE), without OER. Tumor homogeneity index (HI), Dmax, and D95% were evaluated along with worst-case statistics after normalization to normal tissue isotoxicity.

RESULTS

Compared to RegRBE, HypRBE increased tumor [HI, Dmax, D95%] on average by [0.5%, 2.0%, 2.5%] and improved worst-case tumor [HI, Dmax, D95%] by [5.3%, 16.2%, 9.6%]. HypRBE shows an increase in therapeutic ratio, and is notably robust against uncertainty scenarios.

CONCLUSION

We have developed an optimization algorithm whose dose fidelity term is weighted by hypoxia informed RBE values. We have shown that HypRBE selects beams that are better suited to protect low RBE, well-oxygenated normal tissue while maintaining high dose to high RBE, hypoxic tumor cells.

Contouring Analysis on Synthetic Contrast-Enhanced MR from GRMM-GAN and Implications on MR-Guide Radiation Therapy

PURPOSE/OBJECTIVE(S)

MR-guided linear accelerators have been commercialized making MR-only planning and adaptation an appealing alternative circumventing MR-CT registration. However, obtaining daily contrast-enhanced MR images can be prohibitive due to the increased risk of side effects from repeated contrast injections. In this work, we evaluate the quality of contrast-enhanced multi-modal MR image synthesis network GRMM-GAN (gradient regularized multi-modal multi-discrimination sparse-attention fusion generative adversarial network) for MR-guided radiation therapy.

MATERIALS/METHODS

With IRB approval, we trained the GRMM-GAN based on 165 abdominal MR studies from 65 patients. Each study included T2, T1 pre-contrast (T1pre), and T1 contrast enhanced (T1ce) images. The two pre-contrast MR modalities, T2 and T1pre images were adopted as inputs for GRMM-GAN, and the T1ce image at the portal venous phase was used as an output. Ten MR scans containing 21 liver tumors were selected for contouring analysis. A Turing test was first given to six radiation oncologists, in which 100 real T1ce and synthetic T1ce image slices are randomly given to the radiation oncologists to determine the authenticity of the synthesis. We then invited two radiation oncologists (RadOnc 1 and RadOnc2) to manually contour the 21 liver tumors independently on the real T1ce images. RadOnc2 then performed contouring on the respective synthetic T1ce MRs. DICE coefficient (defined as the intersection over the average of two volumes) and Hausdorff distance (HD, measuring how far two volumes are from each other) were used as analysis metrics. The DICE coefficients were calculated from the two radiation oncologists' contours on the real T1ce MR for each tumor. The DICE coefficients were also calculated from RadOnc 2's contours on real and synthetic MRs. Besides, tumor center shifts were extracted. The tumor center of mass coordinates was extracted from real and synthetic volumes. The difference in the coordinates indicated the shifts in the superior-inferior (SI), right-left (RL), and anterior-posterior (AP) directions between real and synthetic tumor volumes.

RESULTS

An average of 52.3% test score was achieved from the six radiation oncologists, which is close to random guessing. RadOnc 1 and RadOnc 2, who had participated in the contouring analysis, achieved an average DICE of 0.91±0.02 from tumor volumes drawn on the real T1ce MRs. This result sets the inter-operator uncertainty baseline in the real clinical setting. RadOnc 2 achieved an average DICE (real vs. synth) of 0.90±0.04 and HD of 4.76±1.82 mm. Only sub-millimeter (SI: 0.67 mm, RL: 0.41 mm, AP: 0.39 mm) tumor center shifts were observed in all three directions.

CONCLUSION

The GRMM-GAN method has the potential for MR-guided liver radiation when contrast agents cannot be administered daily and provide synthetic contrast-enhanced MR for better tumor targeting. The network can produce synthetic MR images with satisfactory contour agreement and geometric integrity.

Towards Automated Dosimetric Analysis of the Bladder Trigone: Deep-Learning-Based Joint Segmentation and Landmark Localization

PURPOSE/OBJECTIVE(S)

The bladder trigone dosimetry is hypothesized to have a stronger correlation with post-SBRT urinary toxicity than that of the entire bladder. However, the trigone tends to move significantly between simulation and daily treatment. Its small size, large daily motion, and proximity to the target lead to potentially consequential but unaccounted-for dosimetric uncertainties. Manual segmentation of the structure can be inconsistent and time-consuming, even with MR-guided RT. Here, we propose and demonstrate a deep-learning-based framework for joint segmentation and landmark localization to support deformable registration and comprehensive dosimetric analysis.

MATERIALS/METHODS

A total of 30 patients were randomly selected for training, and 20 were held out for testing. Each patient had 1 simulation and 5 daily pre-treatment images obtained from a clinical 0.35T MR Linac. The trigone is defined as the triangular bladder section among three landmarks (2 ureteral orifices and the internal urethral orifice). In the manual contouring process, the 3 landmarks were identified first, followed by trigone segmentation. The proposed joint method uses a modified 3D nnU-Net with 2 decoders, one for segmentation and the other for landmark localization. The shared encoder is expected to extract features useful for both tasks. The joint framework was compared with a baseline method using two separate 3D nnU-Nets for landmark localization and trigone segmentation, respectively. Since the trigone is small (∼2% of the bladder volume), we further experimented with a second-stage prediction mimicking the human contouring process. The predicted landmarks from the first stage were used to crop the trigone region, and a second network was trained on cropped images. Evaluation metrics included the Dice score, 95% Hausdorff distance (HD95), and average surface distance (ASD) for segmentation, and Euclidean distance (ED) between the predicted and ground truth landmarks for localization.

RESULTS

The quantification metrics are summarized in the table below. The joint approach shows similar Dice performance to the baseline method but markedly better HD95 by 13%. For landmark localization, the proposed method is similar to the baseline, but the integration of the segmentation task stabilizes the training process. The two-stage approach further improves HD95, ASD, and ED by 27%, 24%, and 19%.

CONCLUSION

Combining segmentation and landmark localization exhibits a synergistic effect. The proposed two-stage approach provided additional improvement. Future studies will explore the deformable registration of the trigone based on the segmentation and landmark detection, as well as analyze cumulated dose distribution.

Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq

Bacteria colonize almost all parts of the human body and can differ significantly. However, the population level transcriptomics measurements can only describe the average bacteria population behaviors, ignoring the heterogeneity among bacteria. Here, we report a droplet-based high-throughput single-microbe RNA-seq assay (smRandom-seq), using random primers for in situ cDNA generation, droplets for single-microbe barcoding, and CRISPR-based rRNA depletion for mRNA enrichment. smRandom-seq showed a high species specificity (99%), a minor doublet rate (1.6%), a reduced rRNA percentage (32%), and a sensitive gene detection (a median of ~1000 genes per single E. coli). Furthermore, smRandom-seq successfully captured transcriptome changes of thousands of individual E. coli and discovered a few antibiotic resistant subpopulations displaying distinct gene expression patterns of SOS response and metabolic pathways in E. coli population upon antibiotic stress. smRandom-seq provides a high-throughput single-microbe transcriptome profiling tool that will facilitate future discoveries in microbial resistance, persistence, microbe-host interaction, and microbiome research.

Identification of TFPI as a receptor reveals recombination-driven receptor switching in Clostridioides difficile toxin B variants

Toxin B (TcdB) is a major exotoxin responsible for diseases associated with Clostridioides difficile infection. Its sequence variations among clinical isolates may contribute to the difficulty in developing effective therapeutics. Here, we investigate receptor-binding specificity of major TcdB subtypes (TcdB1 to TcdB12). We find that representative members of subtypes 2, 4, 7, 10, 11, and 12 do not recognize the established host receptor, frizzled proteins (FZDs). Using a genome-wide CRISPR-Cas9-mediated screen, we identify tissue factor pathway inhibitor (TFPI) as a host receptor for TcdB4. TFPI is recognized by a region in TcdB4 that is homologous to the FZD-binding site in TcdB1. Analysis of 206 TcdB variant sequences reveals a set of six residues within this receptor-binding site that defines a TFPI binding-associated haplotype (designated B4/B7) that is present in all TcdB4 members, a subset of TcdB7, and one member of TcdB2. Intragenic micro-recombination (IR) events have occurred around this receptor-binding region in TcdB7 and TcdB2 members, resulting in either TFPI- or FZD-binding capabilities. Introduction of B4/B7-haplotype residues into TcdB1 enables dual recognition of TFPI and FZDs. Finally, TcdB10 also recognizes TFPI, although it does not belong to the B4/B7 haplotype, and shows species selectivity: it recognizes TFPI of chicken and to a lesser degree mouse, but not human, dog, or cattle versions. These findings identify TFPI as a TcdB receptor and reveal IR-driven changes on receptor-specificity among TcdB variants.

Emerging enterococcus pore-forming toxins with MHC/HLA-I as receptors

Enterococci are a part of human microbiota and a leading cause of multidrug resistant infections. Here, we identify a family of Enterococcus pore-forming toxins (Epxs) in E. faecalis, E. faecium, and E. hirae strains isolated across the globe. Structural studies reveal that Epxs form a branch of β-barrel pore-forming toxins with a β-barrel protrusion (designated the top domain) sitting atop the cap domain. Through a genome-wide CRISPR-Cas9 screen, we identify human leukocyte antigen class I (HLA-I) complex as a receptor for two members (Epx2 and Epx3), which preferentially recognize human HLA-I and homologous MHC-I of equine, bovine, and porcine, but not murine, origin. Interferon exposure, which stimulates MHC-I expression, sensitizes human cells and intestinal organoids to Epx2 and Epx3 toxicity. Co-culture with Epx2-harboring E. faecium damages human peripheral blood mononuclear cells and intestinal organoids, and this toxicity is neutralized by an Epx2 antibody, demonstrating the toxin-mediated virulence of Epx-carrying Enterococcus.

Contextual cues from cancer cells govern cancer-associated fibroblast heterogeneity

Cancer cells function as primary architects of the tumor microenvironment. However, the molecular features of cancer cells that govern stromal cell phenotypes remain unclear. Here, we show that cancer-associated fibroblast (CAF) heterogeneity is driven by lung adenocarcinoma (LUAD) cells at either end of the epithelial-to-mesenchymal transition (EMT) spectrum. LUAD cells that have high expression of the EMT-activating transcription factor ZEB1 reprogram CAFs through a ZEB1-dependent secretory program and direct CAFs to the tips of invasive projections through a ZEB1-driven CAF repulsion process. The EMT, in turn, sensitizes LUAD cells to pro-metastatic signals from CAFs. Thus, CAFs respond to contextual cues from LUAD cells to promote metastasis.

Bota-Rabassedas et al. show that EMT in lung adenocarcinoma cells activates a secretory process that governs CAF heterogeneity and, in turn, sensitizes lung adenocarcinoma cells to pro-metastatic signals from CAFs. Thus, EMT positions lung adenocarcinoma cells at the apex of a signaling hierarchy in the tumor microenvironment.

Sequencing-Based Protein Analysis of Single Extracellular Vesicles

Circulating extracellular vesicles (EVs)-biological nanomaterials shed from most mammalian cells-have emerged as promising biomarkers, drug delivery vesicles, and treatment modulators. While different types of vesicles are being explored for these applications, it is becoming clear that human EVs are quite heterogeneous even in homogeneous or monoclonal cell populations. Since it is the surface EV protein composition that will largely dictate their biological behavior, high-throughput single EV profiling methods are needed to better define EV subpopulations. Here, we present an antibody-based immunosequencing method that allows multiplexed measurement of protein molecules from individual nanometer-sized EVs. We use droplet microfluidics to compartmentalize and barcode individual EVs. The barcodes/antibody-DNA are then sequenced to determine protein composition. Using this highly sensitive technology, we detected specific proteins at the single EV level. We expect that this technology can be further adapted for multiplexed protein analysis of any nanoparticle.

Single-strand RPA for rapid and sensitive detection of SARS-CoV-2 RNA

We report the single-strand Recombinase Polymerase Amplification (ssRPA) method, which merges the fast, isothermal amplification of RPA with subsequent rapid conversion of the double-strand DNA amplicon to single strands, and hence enables facile hybridization-based, high-specificity readout. We demonstrate the utility of ssRPA for sensitive and rapid (4 copies per 50 μL reaction within 10 min, or 8 copies within 8 min) visual detection of SARS-CoV-2 RNA spiked samples, as well as clinical saliva and nasopharyngeal swabs in VTM or water, on lateral flow devices. The ssRPA method promises rapid, sensitive, and accessible RNA detection to facilitate mass testing in the COVID-19 pandemic.

Dissolvable Polyacrylamide Beads for High-Throughput Droplet DNA Barcoding

Droplet-based single cell sequencing technologies, such as inDrop, Drop-seq, and 10X Genomics, are catalyzing a revolution in the understanding of biology. Barcoding beads are key components for these technologies. What is limiting today are barcoding beads that are easy to fabricate, can efficiently deliver primers into drops, and thus achieve high detection efficiency. Here, this work reports an approach to fabricate dissolvable polyacrylamide beads, by crosslinking acrylamide with disulfide bridges that can be cleaved with dithiothreitol. The beads can be rapidly dissolved in drops and release DNA barcode primers. The dissolvable beads are easy to synthesize, and the primer cost for the beads is significantly lower than that for the previous barcoding beads. Furthermore, the dissolvable beads can be loaded into drops with >95% loading efficiency of a single bead per drop and the dissolution of beads does not influence reverse transcription or the polymerase chain reaction (PCR) in drops. Based on this approach, the dissolvable beads are used for single cell RNA and protein analysis.

Transcriptomic and epigenetic regulation of hair cell regeneration in the mouse utricle and its potentiation by Atoh1

The mammalian cochlea loses its ability to regenerate new hair cells prior to the onset of hearing. In contrast, the adult vestibular system can produce new hair cells in response to damage, or by reprogramming of supporting cells with the hair cell transcription factor Atoh1. We used RNA-seq and ATAC-seq to probe the transcriptional and epigenetic responses of utricle supporting cells to damage and Atoh1 transduction. We show that the regenerative response of the utricle correlates with a more accessible chromatin structure in utricle supporting cells compared to their cochlear counterparts. We also provide evidence that Atoh1 transduction of supporting cells is able to promote increased transcriptional accessibility of some hair cell genes. Our study offers a possible explanation for regenerative differences between sensory organs of the inner ear, but shows that additional factors to Atoh1 may be required for optimal reprogramming of hair cell fate.

Endocrine lineage biases arise in temporally distinct endocrine progenitors during pancreatic morphogenesis

Decoding the molecular composition of individual Ngn3 + endocrine progenitors (EPs) during pancreatic morphogenesis could provide insight into the mechanisms regulating hormonal cell fate. Here, we identify population markers and extensive cellular diversity including four EP subtypes reflecting EP maturation using high-resolution single-cell RNA-sequencing of the e14.5 and e16.5 mouse pancreas. While e14.5 and e16.5 EPs are constantly born and share select genes, these EPs are overall transcriptionally distinct concomitant with changes in the underlying epithelium. As a consequence, e16.5 EPs are not the same as e14.5 EPs: e16.5 EPs have a higher propensity to form beta cells. Analysis of e14.5 and e16.5 EP chromatin states reveals temporal shifts, with enrichment of beta cell motifs in accessible regions at later stages. Finally, we provide transcriptional maps outlining the route progenitors take as they make cell fate decisions, which can be applied to advance the in vitro generation of beta cells.

Endocrine progenitors form early in pancreatic development but the diversity of this cell population is unclear. Here, the authors use single cell RNA sequencing of the mouse pancreas at e14.5 and e16.5 to show that endocrine progenitors are temporally distinct and those formed later are more likely to become beta cells

Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming

Blockade of angiogenesis can retard tumour growth, but may also paradoxically increase metastasis^1,2. Vessel normalization (VN) may resolve this paradox³. VN involves increased pericyte coverage, improved tumour vessel perfusion, reduced vascular permeability, and consequently mitigated hypoxia³. While these processes alter tumour progression, their regulation is poorly understood. Here we show that Type 1 T helper (Th1) cells play a crucial role in VN. Bioinformatic analyses revealed that gene expression features related to VN correlate with immunostimulatory pathways, especially T lymphocyte (TL) infiltration/activities. To delineate the causal relationship, we employed various mouse models with VN or TL deficiencies. While VN disruption reduced TL infiltration as expected⁴, reciprocal depletion or inactivation of CD4⁺-TLs decreased VN, indicating a mutually-regulatory loop. Additionally, CD4⁺-TL activation by immune checkpoint blockade (ICB) increased VN. IFNγ⁺ Th1 cells are the major population associated with VN. Patient-derived xenograft (PDX) tumours growing in immunodeficient animal hosts exhibited enhanced hypoxia compared to the original tumours in immunocompetent human hosts, which was reduced by adoptive Th1 transfer. Our findings elucidate an unexpected role of Th1 in vasculature and immune reprogramming. Th1 cells may be a marker and a determinant of both ICB and anti-angiogenesis efficacies.