Fast dual-echo estimation of apparent long T2 fraction using ultrashort echo time magnetic resonance imaging in tibialis tendons and its osteoporosis-related differences in women.

Background: Tendon and bone comprise a critical interrelating unit. Bone loss, including that seen with osteopenia (OPe) or osteoporosis (OPo), may be associated with a reduction in tendon quality, though this remains incompletely investigated. Clinical magnetic resonance imaging (MRI) sequences cannot directly detect signals from tendons because of the very short T2. Clinical MRI may detect high-graded abnormalities by changes in the adjacent structures like bone. However, ultrashort echo time MRI (UTE-MRI) can capture high signals from all tendons. To determine if the long T2 fraction, as measured by a dual-echo UTE-MRI sequence, is a sensitive quantitative technique to the age- and bone-loss-related changes of the lower leg tendons. Methods: This is a cross-sectional study conducted between January 2018 to February 2020 in the lower legs of 14 female patients with OPe [72±6 years old, body mass index (BMI) =25.8±6.2 kg/m2] and 31 female patients with OPo (73±6 years old, BMI=22.0±3.8 kg/m2), as well as 30 female subjects with normal bone (Normal, 35±18 years old, BMI =23.2±4.3 kg/m2), were imaged on a 3T clinical scanner using a dual-echo 3D Cones UTE sequence. We defined the apparent long T2 signal fraction (aFrac-LongT2) of tendons as the ratio between the signal at the second echo time (TE =2.2 ms) to the UTE signal. The average aFrac-LongT2 and the cross-sectional area were calculated for the anterior tibialis tendons (ATTs) and the posterior tibialis tendons (PTTs). The Kruskal-Wallis rank test was used to compare the differences in aFrac-LongT2 and the cross-sectional area of the tendons between the groups. Results: The aFrac-LongT2 of the ATTs and PTTs were significantly higher in the OPo group compared with the Normal group (22.2% and 34.8% in the ATT and PTT, respectively, P<0.01). The cross-sectional area in the ATTs was significantly higher for the OPo group than in the Normal group (Normal/OPo difference was 28.7, P<0.01). Such a difference for PTTs did not reach the significance level. Mean aFrac-LongT2 and cross-sectional area in the OPe group were higher than the Normal group and lower than the OPo group. However, the differences did not show statistical significance, likely due to the higher BMI in the OPe group. Conclusions: Dual-echo UTE-MRI is a rapid quantification technique, and aFrac-LongT2 values showed significant differences in tendons between Normal and OPo patients.

Pancreas preserving duodenectomy (PPrD).

BACKGROUND: Pancreaticoduodenectomy has been the standard of care for managing duodenal neoplasms, but recent studies show similar overall and disease-specific survival after pancreas-preserving duodenectomy (PPrD) with potentially less morbidity. METHODS: Retrospective cohort of all adult (age >18) patients who underwent PPrD with curative intent of a neoplasm in or invading into the duodenum at our institution from 2011 to 2022 (n â€‹= â€‹29), excluding tumors involving the Ampulla of Vater or the pancreas. Statistical analyses were performed using STATA. RESULTS: R0 resection was achieved in 93 â€‹% patients. Ten (34.4 â€‹%) experienced postoperative complications (13.7 â€‹% within Clavien-Dindo III-V). PPrD patients had lower rates of pancreatic leak, delayed gastric emptying, and deep surgical site infection. CONCLUSIONS: In this case series, we demonstrate PPrD is safe and effective, with a high rate of complete resection and lower complication rate than that seen in pancreaticoduodenectomy.

A cross-sectional study of the association of dental health factors with progression and all-cause mortality in men diagnosed with HPV-associated oropharyngeal cancer.

BACKGROUND: Human Papillomavirus-associated oropharyngeal cancer (HPV-OPC) incidence is increasing among men in the United States. Poor dental health has previously been associated with risk of head and neck cancers, oral HPV infection, and persistence but it is not understood whether dental health is associated with outcomes. We sought to determine the association of dental health with progression free survival and overall mortality among men with an HPV-OPC. METHODS: A cross sectional study of men diagnosed with HPV-OPC between 2014-2020 at Moffitt Cancer Center in Tampa, FL was conducted. Dental records were abstracted for assessment of dental fitness prior to cancer treatment. Five dental factors including number of teeth lost, pocket depth, gingival score, loss of attachment, and bone loss were individually examined. Risk factor and outcome data were collected from a patient risk questionnaire and medical record. Using item response theory, an overall dental fitness score from five dental factors was developed in which missing data were multiply imputed. Cox proportional hazards model was used to assess whether dental factors were associated with progression-free survival or overall mortality. RESULTS: Among 206 HPV-OPC cases, median follow-up was 3.4 years (IQR: 2.4-4.4) during which 40 cases involved progression or mortality and 25 deaths occurred. Overall dentition was significantly associated with progression free survival (p = 0.04) and with overall survival (p = 0.03) though findings were not significant after adjustment for age at diagnosis, stage, and smoking history (p = 0.146 and p = 0.120, respectively). A pocket depth of 7 mm or more was associated with overall survival (HR: 5.21; 95% CI: 1.43-19.11) and this remained significant after adjustment for confounding (aHR: 4.14; 95% CI: 1.72-16.26). CONCLUSIONS: Among men diagnosed with an HPV-associated OPC in the US, worse dental health was associated with reduced progression free survival and overall survival, but not after adjustment for confounders. Further studies are needed to examine whether dental health is associated with other prognostic factors and subsequent treatment-related outcomes.

Psychosocial consequences of head and neck cancer symptom burden after chemoradiation: a mixed-method study.

PURPOSE: Patients with head and neck cancer (HNC) experience significant symptom burden from combination chemotherapy and radiation (chemoradiation) that affects acute and long-term health-related quality of life (HRQOL). However, psychosocial impacts of HNC symptom burden are not well understood. This study examined psychosocial consequences of treatment-related symptom burden from the perspectives of survivors of HNC and HNC healthcare providers. METHODS: This was a cross-sectional, mixed-method study conducted at an NCI-designated comprehensive cancer center. Participants (N = 33) were survivors of HNC who completed a full course of chemoradiation (n = 20) and HNC healthcare providers (n = 13). Participants completed electronic surveys and semi-structured interviews. RESULTS: Survivors were M = 61 years old (SD = 9) and predominantly male (75%), White (90%), non-Hispanic (100%), and diagnosed with oropharynx cancer (70%). Providers were mostly female (62%), White (46%) or Asian (31%), and non-Hispanic (85%) and included physicians, registered nurses, an advanced practice nurse practitioner, a registered dietician, and a speech-language pathologist. Three qualitative themes emerged: (1) shock, shame, and self-consciousness, (2) diminished relationship satisfaction, and (3) lack of confidence at work. A subset of survivors (20%) reported clinically low social wellbeing, and more than one-third of survivors (35%) reported clinically significant fatigue, depression, anxiety, and cognitive dysfunction. CONCLUSION: Survivors of HNC and HNC providers described how treatment-related symptom burden impacts psychosocial identity processes related to body image, patient-caregiver relationships, and professional work. Results can inform the development of supportive interventions to assist survivors and caregivers with navigating the psychosocial challenges of HNC treatment and survivorship.

Automatic end-to-end VMAT treatment planning for rectal cancers.

BACKGROUND: The treatment planning process from segmentation to producing a deliverable plan is time-consuming and labor-intensive. Existing solutions automate the segmentation and planning processes individually. The feasibility of combining auto-segmentation and auto-planning for volumetric modulated arc therapy (VMAT) for rectal cancers in an end-to-end process is not clear. PURPOSE: To create and clinically evaluate a complete end-to-end process for auto-segmentation and auto-planning of VMAT for rectal cancer requiring only the gross tumor volume contour and a CT scan as inputs. METHODS: Patient scans and data were retrospectively selected from our institutional records for patients treated for malignant neoplasm of the rectum. We trained, validated, and tested deep learning auto-segmentation models using nnU-Net architecture for clinical target volume (CTV), bowel bag, large bowel, small bowel, total bowel, femurs, bladder, bone marrow, and female and male genitalia. For the CTV, we identified 174 patients with clinically drawn CTVs. We used data for 18 patients for all structures other than the CTV. The structures were contoured under the guidance of and reviewed by a gastrointestinal (GI) radiation oncologist. The predicted results for CTV in 35 patients and organs at risk (OAR) in six patients were scored by the GI radiation oncologist using a five-point Likert scale. For auto-planning, a RapidPlan knowledge-based planning solution was modeled for VMAT delivery with a prescription of 25 Gy in five fractions. The model was trained and tested on 20 and 34 patients, respectively. The resulting plans were scored by two GI radiation oncologists using a five-point Likert scale. Finally, the end-to-end pipeline was evaluated on 16 patients, and the resulting plans were scored by two GI radiation oncologists. RESULTS: In 31 of 35 patients, CTV contours were clinically acceptable without necessary modifications. The CTV achieved a Dice similarity coefficient of 0.85 (±0.05) and 95% Hausdorff distance of 15.25 (±5.59) mm. All OAR contours were clinically acceptable without edits, except for large and small bowel which were challenging to differentiate. However, contours for total, large, and small bowel were clinically acceptable. The two physicians accepted 100% and 91% of the auto-plans. For the end-to-end pipeline, the two physicians accepted 88% and 62% of the auto-plans. CONCLUSIONS: This study demonstrated that the VMAT treatment planning technique for rectal cancer can be automated to generate clinically acceptable and safe plans with minimal human interventions.

Spatial interactions modulate tumor growth and immune infiltration.

Direct observation of immune cell trafficking patterns and tumor-immune interactions is unlikely in human tumors with currently available technology, but computational simulations based on clinical data can provide insight to test hypotheses. It is hypothesized that patterns of collagen formation evolve as a mechanism of immune escape, but the exact nature of the interaction between immune cells and collagen is poorly understood. Spatial data quantifying the degree of collagen fiber alignment in squamous cell carcinomas indicates that late stage disease is associated with highly aligned fibers. Here, we introduce a computational modeling framework (called Lenia) to discriminate between two hypotheses: immune cell migration that moves 1) parallel or 2) perpendicular to collagen fiber orientation. The modeling recapitulates immune-ECM interactions where collagen patterns provide immune protection, leading to an emergent inverse relationship between disease stage and immune coverage. We also illustrate the capabilities of Lenia to model the evolution of tumor progression and immune predation. Lenia provides a flexible framework for considering a spectrum of local (cell-scale) to global (tumor-scale) dynamics by defining a kernel cell-cell interaction function that governs tumor growth dynamics under immune predation with immune cell migration. Mathematical modeling provides important mechanistic insights into cell interactions. Short-range interaction kernels provide a mechanism for tumor cell survival under conditions with strong Allee effects, while asymmetric tumor-immune interaction kernels lead to poor immune response. Thus, the length scale of tumor-immune interactions drives tumor growth and infiltration.

Identification of a Biomarker Panel from Genome-Wide Methylation to Detect Early HPV-Associated Oropharyngeal Cancer.

As oropharyngeal cancer (OPC) associated with human papillomavirus (HPV) increases in men, the need for a screening test to diagnose OPC early is crucial. This study agnostically identified differentially methylated CpG sites to identify additional biomarkers to improve screening for early OPC.DNA was extracted from oral gargles of 89 early cases and 108 frequency matched healthy controls, and processed for genome-wide methylation using the Illumina Infinium MethylationEPIC BeadChip. Selected sites were combined with our prior methylation data in the EPB41L3 gene (CpG sites 438, 427, and 425) and oral HPV16 and HPV18 status were considered as binary variables (positive/negative). Lasso regression identified CpG sites strongly associated with early OPC. ROC curves with AUC were generated. The panel was validated utilizing bootstrap resampling.Machine learning analyses identified 14 markers that are significantly associated with early OPC, including one EPB41L3 CpG site (438) and oral HPV16 status. A final model was trained on all available samples using the discovered panel and was able to predict early OPC compared with controls with an AUC of 0.970 on the training set. In the bootstrap validation sets, the average AUC was 0.935, indicating adequate internal validity.Our data suggest that this panel can detect OPC early, however external validation of this panel is needed. Further refinement of a panel of biomarkers to diagnose OPC earlier is urgently needed to prevent complex treatment of OPC and associated comorbidities, while reducing risk of recurrence. PREVENTION RELEVANCE: This study identified biomarkers using genome-wide methylation to create a panel capable of discerning early oropharyngeal cancer (OPC) from those without OPC. Such a biomarker panel would be an effective tool to detect OPC early and prevent complications of treatment associated with later diagnosis.

Characterization of the Thyroid Cancer Genomic Landscape by Plasma-Based Circulating Tumor DNA Next-Generation Sequencing.

Background: The limited availability of targeted therapies in thyroid cancer (TC) has challenged conventional treatment algorithms and has established urgency for the identification of targetable genomic abnormalities. In addition to widely adopted tissue-based next-generation sequencing (NGS), plasma-based circulating tumor DNA (ctDNA) NGS is rapidly emerging as a genomic biomarker detection method and is steadily gaining utility across solid tumors. To date, plasma-based genomic alterations in TC have not been determined. Herein, we profile potential actionable mutations detected through ctDNA in patients with TC subtypes. Methods: A retrospective data analysis of the Guardant Health, Inc. database was performed using the commercially available Guardant360® plasma-NGS test on TC samples from adult patients collected between 2016 and 2021. The landscape of genomic alterations and blood tumor mutation burden (bTMB) were analyzed in patients with different types of TC: anaplastic TC (ATC), papillary TC (PTC), follicular TC (FTC), oncolytic carcinoma of the thyroid (OCA), poorly differentiated TC (PDTC), medullary TC (MTC), and TC not otherwise specified (TC NOS). Results: Of the 1094 patients included most of the patients n = 876 had TC NOS, and 20% had a specific diagnosis (92 ATC, 62 PTC, 14 FTC, 16 OCA, 2 PDTC, and 32 MTC patients). The median age was 65 (range 10-98) and 47.3% were male. 78.3% of patients had one or more genomic alteration detected by ctDNA NGS. TP53 (46.9%) was the most common mutation detected among all TC. BRAFV600E was detected in 27.2% of ATC, 35.7% of PTC, and in none of FTC. RAS was detected in 18.5% of ATC, 11.9% of PTC, and 62.5% of FTC. RET, ALK, and NTRK fusions were seen in 1.1%, 0.5%, and 0.2% of all TC, respectively. RET mutations were detected in 66.7% of MTC. bTMB analysis was performed on 159 patients. The mean bTMB was higher in ATC compared with other types of TC (p = 0.0011, 0.0557, and <0.0001, respectively). Conclusions: Plasma-based comprehensive NGS is a promising NGS method in TC; however, future validation of the clinical utility by analysis of paired tumor and plasma samples is needed.

Achilles tendon and enthesis assessment using ultrashort echo time magnetic resonance imaging (UTE-MRI) T1 and magnetization transfer (MT) modeling in psoriatic arthritis.

The purpose of this study is to investigate the use of ultrashort echo time (UTE) magnetic resonance imaging (MRI) techniques (T1 and magnetization transfer [MT] modeling) for imaging of the Achilles tendons and entheses in patients with psoriatic arthritis (PsA) compared with asymptomatic volunteers. The heels of twenty-six PsA patients (age 59 ± 15 years, 41% female) and twenty-seven asymptomatic volunteers (age 33 ± 11 years, 47% female) were scanned in the sagittal plane with UTE-T1 and UTE-MT modeling sequences on a 3-T clinical scanner. UTE-T1 and macromolecular proton fraction (MMF; the main outcome of MT modeling) were calculated in the tensile portions of the Achilles tendon and at the enthesis (close to the calcaneus bone). Mann-Whitney-U tests were used to examine statistically significant differences between the two cohorts. UTE-T1 in the entheses was significantly higher for the PsA group compared with the asymptomatic group (967 ± 145 vs. 872 ± 133 ms, p < 0.01). UTE-T1 in the tendons was also significantly higher for the PsA group (950 ± 145 vs. 850 ± 138 ms, p < 0.01). MMF in the entheses was significantly lower in the PsA group compared with the asymptomatic group (15% ± 3% vs. 18% ± 3%, p < 0.01). MMF in the tendons was also significantly lower in the PsA group compared with the asymptomatic group (17% ± 4% vs. 20% ± 5%, p < 0.01). Percentage differences in MMF between the asymptomatic and PsA groups (-16.6% and -15.0% for the enthesis and tendon, respectively) were higher than the T1 differences (10.8% and 11.7% for the enthesis and tendon, respectively). The results suggest higher T1 and lower MMF in the Achilles tendons and entheses in PsA patients compared with the asymptomatic group. This study highlights the potential of UTE-T1 and UTE-MT modeling for quantitative evaluation of entheses and tendons in PsA patients.

Immune landscape in molecular subtypes of human papillomavirus-negative head and neck cancer.

Head and neck squamous cell carcinomas (HNSCC) remain a poorly understood disease clinically and immunologically. HPV is a known risk factor of HNSCC associated with better outcome, whereas HPV-negative HNSCC are more heterogeneous in outcome. Gene expression signatures have been developed to classify HNSCC into four molecular subtypes (classical, basal, mesenchymal, and atypical). However, the molecular underpinnings of treatment response and the immune landscape for these molecular subtypes are largely unknown. Herein, we described a comprehensive immune landscape analysis in three independent HNSCC cohorts (>700 patients) using transcriptomics data. We assigned the HPV- HNSCC patients into these four molecular subtypes and characterized the tumor microenvironment using deconvolution method. We determined that atypical and mesenchymal subtypes have greater immune enrichment and exhibit a T-cell exhaustion phenotype, compared to classical and basal subtypes. Further analyses revealed different B cell maturation and antibody isotypes enrichment patterns, and distinct immune microenvironment crosstalk in the atypical and mesenchymal subtypes. Taken together, our study suggests that treatments that enhances B cell activity may benefit patients with HNSCC of the atypical subtypes. The rationale can be utilized in the design of future precision immunotherapy trials based on the molecular subtypes of HPV- HNSCC.

An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment.

We introduce a new AI-ready computational pathology dataset containing restained and co-registered digitized images from eight head-and-neck squamous cell carcinoma patients. Specifically, the same tumor sections were stained with the expensive multiplex immunofluorescence (mIF) assay first and then restained with cheaper multiplex immunohistochemistry (mIHC). This is a first public dataset that demonstrates the equivalence of these two staining methods which in turn allows several use cases; due to the equivalence, our cheaper mIHC staining protocol can offset the need for expensive mIF staining/scanning which requires highly-skilled lab technicians. As opposed to subjective and error-prone immune cell annotations from individual pathologists (disagreement > 50%) to drive SOTA deep learning approaches, this dataset provides objective immune and tumor cell annotations via mIF/mIHC restaining for more reproducible and accurate characterization of tumor immune microenvironment (e.g. for immunotherapy). We demonstrate the effectiveness of this dataset in three use cases: (1) IHC quantification of CD3/CD8 tumor-infiltrating lymphocytes via style transfer, (2) virtual translation of cheap mIHC stains to more expensive mIF stains, and (3) virtual tumor/immune cellular phenotyping on standard hematoxylin images. The dataset is available at https://github.com/nadeemlab/DeepLIIF.

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources.

Access to radiotherapy worldwide is limited. The Radiation Planning Assistant (RPA) is a fully automated, web-based tool that is being developed to offer fully automated radiotherapy treatment planning tools to clinics with limited resources. The goal is to help clinical teams scale their efforts, thus reaching more patients with cancer. The user connects to the RPA via a webpage, completes a Service Request (prescription and information about the radiotherapy targets), and uploads the patient's CT image set. The RPA offers two approaches to automated planning. In one-step planning, the system uses the Service Request and CT scan to automatically generate the necessary contours and treatment plan. In two-step planning, the user reviews and edits the automatically generated contours before the RPA continues to generate a volume-modulated arc therapy plan. The final plan is downloaded from the RPA website and imported into the user's local treatment planning system, where the dose is recalculated for the locally commissioned linac; if necessary, the plan is edited prior to approval for clinical use.

Radiotherapy Plus Cisplatin With or Without Lapatinib for Non-Human Papillomavirus Head and Neck Carcinoma: A Phase 2 Randomized Clinical Trial.

Importance: Patients with locally advanced non-human papillomavirus (HPV) head and neck cancer (HNC) carry an unfavorable prognosis. Chemoradiotherapy (CRT) with cisplatin or anti-epidermal growth factor receptor (EGFR) antibody improves overall survival (OS) of patients with stage III to IV HNC, and preclinical data suggest that a small-molecule tyrosine kinase inhibitor dual EGFR and ERBB2 (formerly HER2 or HER2/neu) inhibitor may be more effective than anti-EGFR antibody therapy in HNC. Objective: To examine whether adding lapatinib, a dual EGFR and HER2 inhibitor, to radiation plus cisplatin for frontline therapy of stage III to IV non-HPV HNC improves progression-free survival (PFS). Design, Setting, and Participants: This multicenter, phase 2, double-blind, placebo-controlled randomized clinical trial enrolled 142 patients with stage III to IV carcinoma of the oropharynx (p16 negative), larynx, and hypopharynx with a Zubrod performance status of 0 to 1 who met predefined blood chemistry criteria from October 18, 2012, to April 18, 2017 (median follow-up, 4.1 years). Data analysis was performed from December 1, 2020, to December 4, 2020. Intervention: Patients were randomized (1:1) to 70 Gy (6 weeks) plus 2 cycles of cisplatin (every 3 weeks) plus either 1500 mg per day of lapatinib (CRT plus lapatinib) or placebo (CRT plus placebo). Main Outcomes and Measures: The primary end point was PFS, with 69 events required. Progression-free survival rates between arms for all randomized patients were compared by 1-sided log-rank test. Secondary end points included OS. Results: Of the 142 patients enrolled, 127 (median [IQR] age, 58 [53-63] years; 98 [77.2%] male) were randomized; 63 to CRT plus lapatinib and 64 to CRT plus placebo. Final analysis did not suggest improvement in PFS (hazard ratio, 0.91; 95% CI, 0.56-1.46; P = .34) or OS (hazard ratio, 1.06; 95% CI, 0.61-1.86; P = .58) with the addition of lapatinib. There were no significant differences in grade 3 to 4 acute adverse event rates (83.3% [95% CI, 73.9%-92.8%] with CRT plus lapatinib vs 79.7% [95% CI, 69.4%-89.9%] with CRT plus placebo; P = .64) or late adverse event rates (44.4% [95% CI, 30.2%-57.8%] with CRT plus lapatinib vs 40.8% [95% CI, 27.1%-54.6%] with CRT plus placebo; P = .84). Conclusion and Relevance: In this randomized clinical trial, dual EGFR-ERBB2 inhibition with lapatinib did not appear to enhance the benefit of CRT. Although the results of this trial indicate that accrual to a non-HPV HNC-specific trial is feasible, new strategies must be investigated to improve the outcome for this population with a poor prognosis. Trial Registration: ClinicalTrials.gov Identifier: NCT01711658.

Deep learning-based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers.

BACKGROUND: In recent years, deep-learning models have been used to predict entire three-dimensional dose distributions. However, the usability of dose predictions to improve plan quality should be further investigated. PURPOSE: To develop a deep-learning model to predict high-quality dose distributions for volumetric modulated arc therapy (VMAT) plans for patients with gynecologic cancer and to evaluate their usability in driving plan quality improvements. METHODS: A total of 79 VMAT plans for the female pelvis were used to train (47 plans), validate (16 plans), and test (16 plans) 3D dense dilated U-Net models to predict 3D dose distributions. The models received the normalized CT scan, dose prescription, and target and normal tissue contours as inputs. Three models were used to predict the dose distributions for plans in the test set. A radiation oncologist specializing in the treatment of gynecologic cancers scored the test set predictions using a 5-point scale (5, acceptable as-is; 4, prefer minor edits; 3, minor edits needed; 2, major edits needed; and 1, unacceptable). The clinical plans for which the dose predictions indicated that improvements could be made were reoptimized with constraints extracted from the predictions. RESULTS: The predicted dose distributions in the test set were of comparable quality to the clinical plans. The mean voxel-wise dose difference was -0.14 ± 0.46 Gy. The percentage dose differences in the predicted target metrics of D 1 % ${D}_{1{\mathrm{\% }}}$ and D 98 % ${D}_{98{\mathrm{\% }}}$ were -1.05% ± 0.59% and 0.21% ± 0.28%, respectively. The dose differences in the predicted organ at risk mean and maximum doses were -0.30 ± 1.66 Gy and -0.42 ± 2.07 Gy, respectively. A radiation oncologist deemed all of the predicted dose distributions clinically acceptable; 12 received a score of 5, and four received a score of 4. Replanning of flagged plans (five plans) showed that the original plans could be further optimized to give dose distributions close to the predicted dose distributions. CONCLUSIONS: Deep-learning dose prediction can be used to predict high-quality and clinically acceptable dose distributions for VMAT female pelvis plans, which can then be used to identify plans that can be improved with additional optimization.

Deciphering the Tumor-Immune-Microbe Interactions in HPV-Negative Head and Neck Cancer.

Patients with human papillomavirus-negative head and neck squamous cell carcinoma (HPV-negative HNSCC) have worse outcomes than HPV-positive HNSCC. In our study, we used a published dataset and investigated the microbes enriched in molecularly classified tumor groups. We showed that microbial signatures could distinguish Hypoxia/Immune phenotypes similar to the gene expression signatures. Furthermore, we identified three highly-correlated microbes with immune processes that are crucial for immunotherapy response. The survival of patients in a molecularly heterogenous group shows significant differences based on the co-abundance of the three microbes. Overall, we present evidence that tumor-associated microbiota are critical components of the tumor ecosystem that may impact tumor microenvironment and immunotherapy response. The results of our study warrant future investigation to experimentally validate the conclusions, which have significant impacts on clinical decision-making, such as treatment selection.

Unveiling targeted cell-free DNA methylation regions through paired methylome analysis of tumor and normal tissues.

Liquid biopsy analysis of cell-free DNA (cfDNA) has revolutionized cancer research by enabling non-invasive assessment of tumor-derived genetic and epigenetic changes. In this study, we conducted a comprehensive paired-sample differential methylation analysis (psDMR) on reprocessed methylation data from two large datasets, CPTAC and TCGA, to identify and validate differentially methylated regions (DMRs) as potential cfDNA biomarkers for head and neck squamous cell carcinoma (HNSC). Our hypothesis is that the paired sample test provides a more suitable and powerful approach for the analysis of heterogeneous cancers like HNSC. The psDMR analysis revealed a significant number of overlapped hypermethylated DMRs between two datasets, indicating the reliability and relevance of these regions for cfDNA methylation biomarker discovery. We identified several candidate genes, including CALCA, ALX4, and HOXD9, which have been previously established as liquid biopsy methylation biomarkers in various cancer types. Furthermore, we demonstrated the efficacy of targeted region analysis using cfDNA methylation data from oral cavity squamous cell carcinoma and nasopharyngeal carcinoma patients, further validating the utility of psDMR analysis in prioritizing cfDNA methylation biomarkers. Overall, our study contributes to the development of cfDNA-based approaches for early cancer detection and monitoring, expanding our understanding of the epigenetic landscape of HNSC, and providing valuable insights for liquid biopsy biomarker discovery not only in HNSC and other cancer types.

Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant.

PURPOSE: Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access). DESIGN: In this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology. RESULTS: RPA tools will be offered through a webpage, where users can upload computed tomography data sets and download automatically generated contours and treatment plans. All interfaces have been designed to maximize ease of use and minimize risk. The current version of the RPA includes automated contouring and planning for head and neck cancer, cervical cancer, breast cancer, and metastases to the brain. CONCLUSION: The RPA has been designed to bring high-quality treatment planning to more patients across the world, and it may encourage greater investment in treatment devices and other aspects of cancer treatment.

An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment.

We introduce a new AI-ready computational pathology dataset containing restained and co-registered digitized images from eight head-and-neck squamous cell carcinoma patients. Specifically, the same tumor sections were stained with the expensive multiplex immunofluorescence (mIF) assay first and then restained with cheaper multiplex immunohistochemistry (mIHC). This is a first public dataset that demonstrates the equivalence of these two staining methods which in turn allows several use cases; due to the equivalence, our cheaper mIHC staining protocol can offset the need for expensive mIF staining/scanning which requires highly-skilled lab technicians. As opposed to subjective and error-prone immune cell annotations from individual pathologists (disagreement > 50%) to drive SOTA deep learning approaches, this dataset provides objective immune and tumor cell annotations via mIF/mIHC restaining for more reproducible and accurate characterization of tumor immune microenvironment (e.g. for immunotherapy). We demonstrate the effectiveness of this dataset in three use cases: (1) IHC quantification of CD3/CD8 tumor-infiltrating lymphocytes via style transfer, (2) virtual translation of cheap mIHC stains to more expensive mIF stains, and (3) virtual tumor/immune cellular phenotyping on standard hematoxylin images. The dataset is available at \url{https://github.com/nadeemlab/DeepLIIF}.

EGFR Inhibition by Cetuximab Modulates Hypoxia and IFN Response Genes in Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) has one of the most hypoxic and immunosuppressive tumor microenvironments (TME) among solid tumors. However, there is no proven therapeutic strategy to remodel the TME to be less hypoxic and proinflammatory. In this study, we classified tumors according to a Hypoxia-Immune signature, characterized the immune cells in each subgroup, and analyzed the signaling pathways to identify a potential therapeutic target that can remodel the TME. We confirmed that hypoxic tumors had significantly higher numbers of immunosuppressive cells, as evidenced by a lower ratio of CD8+ T cells to FOXP3+ regulatory T cells, compared with nonhypoxic tumors. Patients with hypoxic tumors had worse outcomes after treatment with pembrolizumab or nivolumab, anti-programmed cell death-1 inhibitors. Our expression analysis also indicated that hypoxic tumors predominantly increased the expression of the EGFR and TGFß pathway genes. Cetuximab, an anti-EGFR inhibitor, decreased the expression of hypoxia signature genes, suggesting that it may alleviate the effects of hypoxia and remodel the TME to become more proinflammatory. Our study provides a rationale for treatment strategies combining EGFR-targeted agents and immunotherapy in the management of hypoxic HNSCC. Significance: While the hypoxic and immunosuppressive TME of HNSCC has been well described, comprehensive evaluation of the immune cell components and signaling pathways contributing to immunotherapy resistance has been poorly characterized. We further identified additional molecular determinants and potential therapeutic targets of the hypoxic TME to fully leverage currently available targeted therapies that can be administered with immunotherapy.