Radiotherapy Response Research Articles

Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses.

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% confidence interval 0.37 to 0.78, P = 0.0001) and suggested postoperative management could be refined for 29.8% of patients. In sum, our results identify a targeted gene expression biomarker that improves discrimination of meningioma outcomes, including prediction of postoperative radiotherapy responses.

A Retrospective Comparison of Toxicity, Response and Survival of Intensity-Modulated Radiotherapy Versus Three-Dimensional Conformal Radiation Therapy in the Treatment of Rectal Carcinoma

A Retrospective Comparison of Toxicity, Response and Survival of Intensity-Modulated Radiotherapy Versus Three-Dimensional Conformal Radiation Therapy in the Treatment of Rectal Carcinoma

Methylglyoxal from gut microbes boosts radiosensitivity and radioimmunotherapy in rectal cancer by triggering endoplasmic reticulum stress and cGAS-STING activation

BackgroundPreoperative radiation therapy (preRT) is a fundamental aspect of neoadjuvant treatment for rectal cancer (RC), but the response to this treatment remains unsatisfactory. The combination of radiation therapy (RT) and...

Non-invasive monitoring of neoadjuvant radiation therapy response in soft tissue sarcomas by multiparametric MRI and quantification of circulating tumor DNA-A study protocol.

Wide resection remains the cornerstone of localized soft-tissue sarcomas (STS) treatment. Neoadjuvant radiation therapy (NRT) may decrease the risk of local recurrences; however, its effectiveness for different histological STS subtypes has not been systematically investigated. The proposed prospective study evaluates the NRT response in STS using liquid biopsies and the correlation of multiparametric magnetic resonance imaging (mpMRI) with histopathology and immunohistochemistry. Patients with localized high-grade STS, who qualify for NRT, are included in this study. Quantification of circulating tumor DNA (ctDNA) in patient blood samples is performed by targeted next-generation sequencing. Soft-tissue sarcoma subtype-specific panel sequencing in combination with patient-specific exome sequencing allows the detection of individual structural variants and point mutations. Circulating free DNA is isolated from peritherapeutically collected patient plasma samples and ctDNA quantified therein. Identification of breakpoints is carried out using FACTERA. Bioinformatic analysis is performed using samtools, picard, fgbio, and the MIRACUM Pipeline. Combination of conventional MRI sequences with diffusion-weighted imaging, intravoxel-incoherent motion, and dynamic contrast enhancement. Multiparametric MRI is performed before, during, and after NRT. We aim to correlate mpMRI data with the resected specimen's macroscopical, histological, and immunohistochemical findings. Preliminary data support the notion that quantification of ctDNA in combination with tumor mass characterization through co-registration of mpMRI and histopathology can predict NRT response of STS. The methods presented in this prospective study are necessary to assess therapy response in heterogeneous tumors and lay the foundation of future patient- and tumor-specific therapy concepts. These methods can be applied to various tumor entities. Thus, the participation and support of a wider group of oncologic surgeons are needed to validate these findings on a larger patient cohort.

A molecular classification system for estimating radiotherapy response and anticancer immunity for individual breast cancer patients.

Radiotherapy is a cornerstone of breast cancer therapy, but radiotherapy resistance is a major clinical challenge. Herein, we show a molecular classification approach for estimating individual responses to radiotherapy. Consensus clustering was adopted to classify radiotherapy-sensitive and -resistant clusters in the TCGA-BRCA cohort based upon prognostic differentially expressed radiotherapy response-related genes (DERRGs). The stability of the classification was proven in the GSE58812 cohort via NTP method and the reliability was further verified by quantitative RT-PCR analyses of DERRGs. A Riskscore system was generated through Least absolute shrinkage and selection operator (LASSO) analysis, and verified in the GSE58812 and GSE17705. Treatment response and anticancer immunity were evaluated via multiple well-established computational approaches. We classified breast cancer patients as radiotherapy-sensitive and -resistant clusters, namely C1 and C2, also verified by quantitative RT-PCR analyses of DERRGs. Two clusters presented heterogeneous clinical traits, with poorer prognosis, older age, more advanced T, and more dead status in the C2. The C1 tumors had higher activity of reactive oxygen species and response to X-ray, proving better radiotherapeutic response. Stronger anticancer immunity was found in the C1 tumors that had rich immune cell infiltration, similar expression profiling to patients who responded to anti-PD-1, and activated immunogenic cell death and ferroptosis. The Riskscore was proposed for improving patient prognosis. High Riskscore samples had lower radiotherapeutic response and stronger DNA damage repair as well as poor anticancer immunity, while low Riskscore samples were more sensitive to docetaxel, doxorubicin, and paclitaxel. Our findings propose a novel radiotherapy response classification system based upon molecular profiles for estimating radiosensitivity for individual breast cancer patients, and elucidate a methodological advancement for synergy of radiotherapy with ICB.

Radiation pneumonia predictive model for radiotherapy in esophageal carcinoma patients

BackgroundThe machine learning models with dose factors and the deep learning models with dose distribution matrix have been used to building lung toxics models for radiotherapy and achieve promising results. However, few studies have integrated clinical features into deep learning models. This study aimed to explore the role of three-dimension dose distribution and clinical features in predicting radiation pneumonitis (RP) in esophageal cancer patients after radiotherapy and designed a new hybrid deep learning network to predict the incidence of RP.MethodsA total of 105 esophageal cancer patients previously treated with radiotherapy were enrolled in this study. The three-dimension (3D) dose distributions within the lung were extracted from the treatment planning system, converted into 3D matrixes and used as inputs to predict RP with ResNet. In total, 15 clinical factors were normalized and converted into one-dimension (1D) matrixes. A new prediction model (HybridNet) was then built based on a hybrid deep learning network, which combined 3D ResNet18 and 1D convolution layers. Machine learning-based prediction models, which use the traditional dosiomic factors with and without the clinical factors as inputs, were also constructed and their predictive performance compared with that of HybridNet using tenfold cross validation. Accuracy and area under the receiver operator characteristic curve (AUC) were used to evaluate the model effect. DeLong test was used to compare the prediction results of the models.ResultsThe deep learning-based model achieved superior prediction results compared with machine learning-based models. ResNet performed best in the group that only considered dose factors (accuracy, 0.78 ± 0.05; AUC, 0.82 ± 0.25), whereas HybridNet performed best in the group that considered both dose factors and clinical factors (accuracy, 0.85 ± 0.13; AUC, 0.91 ± 0.09). HybridNet had higher accuracy than that of Resnet (p = 0.009).ConclusionBased on prediction results, the proposed HybridNet model could predict RP in esophageal cancer patients after radiotherapy with significantly higher accuracy, suggesting its potential as a useful tool for clinical decision-making. This study demonstrated that the information in dose distribution is worth further exploration, and combining multiple types of features contributes to predict radiotherapy response.

Mean global DNA methylation serves as independent prognostic marker in IDH-wildtype glioblastoma.

The IDH-wildtype glioblastoma (GBM) patients have a devastating prognosis. Here, we analyzed the potential prognostic value of global DNA methylation of the tumors. DNA methylation of 492 primary samples and 31 relapsed samples, each treated with combination therapy, and of 148 primary samples treated with radiation alone were compared with patient survival. We determined the mean methylation values and estimated the immune cell infiltration from the methylation data. Moreover, the mean global DNA methylation of 23 GBM cell lines was profiled and correlated to their cellular radiosensitivity as measured by colony formation assay. High mean DNA methylation levels correlated with improved survival, which was independent from known risk factors (MGMT promoter methylation, age, extent of resection; P = 0.009) and methylation subgroups. Notably, this correlation was also independent of immune cell infiltration, as higher number of immune cells indeed was associated with significantly better OS but lower mean methylation. Radiosensitive GBM cell lines had a significantly higher mean methylation than resistant lines (P = 0.007), and improved OS of patients treated with radiotherapy alone was also associated with higher DNA methylation (P = 0.002). Furthermore, specimens of relapsed GBM revealed a significantly lower mean DNA methylation compared to the matching primary tumor samples (P = 0.041). Our results indicate that mean global DNA methylation is independently associated with outcome in glioblastoma. The data also suggest that a higher DNA methylation is associated with better radiotherapy response and less aggressive phenotype, both of which presumably contribute to the observed correlation with OS.

Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control.

Radiation therapy (RT) is one of the most common anticancer therapies. Yet, current radiation oncology practice does not adapt RT dose for individual patients, despite wide interpatient variability in radiosensitivity and accompanying treatment response. We have previously shown that mechanistic mathematical modeling of tumor volume dynamics can simulate volumetric response to RT for individual patients and estimation personalized RT dose for optimal tumor volume reduction. However, understanding the implications of the choice of the underlying RT response model is critical when calculating personalized RT dose. In this study, we evaluate the mathematical implications and biological effects of 2 models of RT response on dose personalization: (1) cytotoxicity to cancer cells that lead to direct tumor volume reduction (DVR) and (2) radiation responses to the tumor microenvironment that lead to tumor carrying capacity reduction (CCR) and subsequent tumor shrinkage. Tumor growth was simulated as logistic growth with pre-treatment dynamics being described in the proliferation saturation index (PSI). The effect of RT was simulated according to each respective model for a standard schedule of fractionated RT with 2 Gy weekday fractions. Parameter sweeps were evaluated for the intrinsic tumor growth rate and the radiosensitivity parameter for both models to observe the qualitative impact of each model parameter. We then calculated the minimum RT dose required for locoregional tumor control (LRC) across all combinations of the full range of radiosensitvity and proliferation saturation values. Both models estimate that patients with higher radiosensitivity will require a lower RT dose to achieve LRC. However, the two models make opposite estimates on the impact of PSI on the minimum RT dose for LRC: the DVR model estimates that tumors with higher PSI values will require a higher RT dose to achieve LRC, while the CCR model estimates that higher PSI values will require a lower RT dose to achieve LRC. Ultimately, these results show the importance of understanding which model best describes tumor growth and treatment response in a particular setting, before using any such model to make estimates for personalized treatment recommendations.

Shooting the messenger: a systematic review investigating extracellular vesicle isolation and characterisation methods and their influence on understanding extracellular vesicles-radiotherapy interactions in glioblastoma

BackgroundExtracellular vesicles (EVs) hold promise for improving our understanding of radiotherapy response in glioblastoma due to their role in intercellular communication within the tumour microenvironment (TME). However, methodologies to study EVs are evolving with significant variation within the EV research community.MethodsWe conducted a systematic review to critically appraise EV isolation and characterisation methodologies and how this influences our understanding of the findings from studies investigating radiotherapy and EV interactions in glioblastoma. 246 articles published up to 24/07/2023 from PubMed and Web of Science were identified using search parameters related to radiotherapy, EVs, and glioblastoma. Two reviewers evaluated study eligibility and abstracted data.ResultsIn 26 articles eligible for inclusion (16 investigating the effects of radiotherapy on EVs, five investigating the effect of EVs on radiation response, and five clinical studies), significant heterogeneity and frequent omission of key characterisation steps was identified, reducing confidence that the results are related to EVs and their cargo as opposed to co-isolated bioactive molecules. However, the results are able to clearly identify interactions between EVs and radiotherapy bi-directionally within different cell types within the glioblastoma TME. These interactions facilitate transferable radioresistance and oncogenic signalling, highlighting that EVs are an important component in the variability of glioblastoma radiotherapy response.ConclusionsFuture multi-directional investigations interrogating the whole TME are required to improve subsequent clinical translation, and all studies should incorporate up to date controls and reporting requirements to increase the validity of their findings. This would be facilitated by increased collaboration between less experienced and more experienced EV research groups.

Association of microRNA-652 expression with radiation response of colorectal cancer: A study from rectal cancer patients in a Swedish trial of preoperative radiotherapy.

Radiotherapy is a standard adjuvant therapy in patients with progressive rectal cancer, but many patients are resistant to radiotherapy, leading to poor prognosis. Our study identified microRNA-652 (miR-652) value on radiotherapy response and outcome in rectal cancer patients. miR-652 expression was determined by qPCR in primary rectal cancer from 48 patients with and 53 patients without radiotherapy. The association of miR-652 with biological factors and the prognosis was examined. The biological function of miR-652 was identified through TCGA and GEPIA database searches. Two human colon cancer cell lines (HCT116 p53+/+ and p53-/-) were used for in vitro study. The molecular interactions of miR-652 and tumor suppressor genes were studied through a computational approach. In RT patients, miR-652 expression was significantly decreased in cancers when compared to non-radiotherapy cases (P=0.002). High miR-652 expression in non-RT patients was with increased apoptosis marker (P=0.036), ATM (P=0.010), and DNp73 expression (P=0.009). High miR-652 expression was related to worse disease-free survival of non-radiotherapy patients, independent of gender, age, tumor stage, and differentiation (P=0.028; HR=7.398, 95% CI 0.217-3.786). The biological functional analysis further identified the prognostic value and potential relationship of miR-652 with apoptosis in rectal cancer. miR-652 expression in cancers was negatively related to WRAP53 expression (P=0.022). After miR-652 inhibition, the estimation of reactive oxygen species, caspase activity, and apoptosis in HCT116 p53+/+ cells was significantly increased compared with HCT116 p53-/- cells after radiation. The results of the molecular docking analysis show that the miR652-CTNNBL1 and miR652-TP53 were highly stable. Our findings suggest the potential value of miR-652 expression as a marker for the prediction of radiation response and clinical outcome in rectal cancer patients.

Malignant Peripheral Nerve Sheath Tumors Activate Distinct Immunosuppressive Pathways Following Radiotherapy and are Associated with Immune Depletion In Vivo

Patients with neurofibromatosis type I, caused by NF1 loss, develop benign plexiform neurofibromas (pNF) in their peripheral nervous system (PNS). Malignant transformation of pNFs into malignant peripheral nerve sheath tumors (MPNSTs) occurs following CDKN2A/B and SUZ12 loss, a process associated with radiotherapy (RT). However, the molecular mechanisms underlying RT responses by different PNS cell types remain unclear. We hypothesized normal peripheral nerve cells, pNFs, and MPNSTs harbor distinct RT responses. Patient derived NF1 WT immortalized peripheral nerve cells (iPNs), NF1 mutant pNF cells, and NF1/CDKN2AB/SUZ12 mutant MPNST cells were used to study RT responses in vitro. CRISPRi was used to assess the functional effects of candidate gene repression. In vitro viability was measured by cell counts. Transcriptomic signatures were measured by bulk RNA-sequencing and integrated with single-cell RNA sequencing (scRNA-seq) data from patient-derived pNF and MPNST resection specimens. Radiation dose response curves revealed pNF cells (IC50 0.61 Gy) were more radiosensitive than MPNST cells (4.15 Gy). WT iPNs, NF1 deficient iPNs, and pNFs cells displayed no difference in cell viability (p = 0.67; t-test) following initiation of 2 Gy x 5 fractions, while MPNST cells were significantly more viable (p = 0.02; t-test). Principal component analysis of bulk RNA-sequencing data at 5 or 14 days following 2 Gy x 5 fractions revealed cell line of origin accounted for the greatest inter-sample variation (64.9% variance), with additional components separating samples based on radiation presence and timing. Using the most variable genes in PCA space to identify markers of RT response, iPNs and pNFs upregulated pro-apoptotic pathways (BAD, DAPK3) at 5 days post-radiation while MPNST cells alone upregulated pro-survival growth factor signaling). At 14 days post radiation, MPNST cells uniquely upregulated TGFβ signaling and interferon response circuits. Incorporation of scRNA-seq data revealed enrichment of growth factor signaling and TGFβ signatures in MPNSTs compared to pNF. Moreover, MPNST harbored significantly fewer immune cells than pNFs (p = 0.008, t-test), suggesting cell-autonomous signaling and crosstalk with the microenvironment are both critical to MPNST radioresistance. Our data indicate additional genetic hits beyond NF1 loss may be required for RT-associated malignant transformation of pNFs and radioresistance in MPNSTs. Analysis of transcriptomic responses to RT suggests that upregulated growth factor signaling and TGFβ-associated immunosuppression are distinct features of MPNST. Future work will focus on CRISPRi screens to unbiasedly nominate functional modifiers of RT response in NF1/CDKN2AB deficient tumors, which may be broadly useful in cancer.

Mechanisms of Intrinsic Radioresistance in Breast Cancer Identify Potential Therapeutic Vulnerabilities

Clinical management of breast cancer (BC) includes radiation therapy (RT) for most women, though the molecular mechanisms that underly RT response and intrinsic radioresistance are poorly understood. Both in vitro and in vivo models aid in our understanding of radiobiology, and we hypothesized that transcriptional changes caused by radiation in vitro in BC cell lines would be recapitulated in an in vivo mouse xenograft model and uncover targetable mechanisms of radioresistance in BC. Radiosensitivity was measured with clonogenic survival assays in 16 cell lines. RNA-seq experiments in vitro and in vivo were performed in an RT resistant (SUM-159) and RT sensitive (ZR-75) cell line 24 hrs after 4 Gy or after 2 Gy x 6 fractions, respectively. Differentially expressed genes (DEGs) were identified from RNA-seq data with DeSeq2 followed by pathway analysis with iPathwayGuide. RT sensitivity was subtype independent in 16 BC cell lines, with SUM-159 radioresistant (SF 0.88) and ZR-75-1 radiosensitive (SF 0.29). There were 75 unique pathways that were significantly altered after RT in SUM-159 cells (53 pathways in vivo only, 36 pathways in vitro only, 14 both conditions; adjusted p-value < 0.05) and 85 unique pathways that were significantly altered after RT in ZR-75-1 cells (16 pathways in vivo only, 72 in vivo only, 3 both conditions; adjusted p-value < 0.05). Pathways that were significantly affected in both cell lines exclusively in the in vitro condition include canonical RT response pathways such as cell cycle, cellular senescence, and DNA replication, though the direction of DEGs were opposite in the two cell lines for each of these pathways. The IL-17 signaling pathway was significantly altered for both cell lines in vivo. Of the pathways that were significantly altered in both conditions for SUM-159 cells, inflammation, including chemokine signaling pathway and cytokine-cytokine receptor interaction, were among the most significant. Significantly more cytokines were upregulated following RT in vivo than in vitro. Cytokines were not upregulated in ZR-75-1 cells in vitro or in vivo. Taken together, the significant changes in the IL-17 pathway and the upregulation of cytokines only in vivo indicate a potential of the tumor microenvironment in the in vivo condition that the in vitro condition lacks. Increased heterogeneity in vivo relative to in vitro may also explain the absence of several canonical RT response pathways in the in vivo conditions for each cell line. Notably, the opposite direction of DEG changes in the canonical RT response pathways between the 2 cell lines with disparate radiosensitivity levels may point to important biologic vulnerabilities that may be targeted in the resistant SUM-159 cells. Future studies are underway using additional BC cell lines and single-cell analysis to better understand RT response heterogeneity.

A Biosignature Integrating Immune and Metabolic Signaling Axes to Assess Limited Radiation Therapy Response in Early-Stage Breast Cancer from a Low-Risk Cohort

Radiation therapy (RT) post breast conserving surgery (BCS) reduces in-breast recurrence (IBR) rate in early-stage invasive breast cancer (BC) patients. The RT treatment recommendation is often driven by clinicopathological (CP) factors; however, CP factors alone have limited ability to identify which women significantly benefit from RT, or those with higher IBR risk after BCS plus RT. Biologic factors driving unique phenotypes, in addition to CP, may improve prediction of RT response. In this study we evaluated the role of immune and metabolic signaling axes in predicting RT response in hormone receptor positive, HER2 negative, early-stage BC patients. Biomarkers from immune and metabolic signaling axes were studied in a cohort of 939 women from Sweden, at a CLIA certified lab (Laguna Hills, CA). Formalin fixed paraffin embedded tissues were assayed for protein expression using multiplex immunofluorescence and multi-spectral imaging. Immune and metabolic axes were assessed using biomarkers combined with a non-linear model, adjusting for patient age. RT prediction by the model was assessed, along and adjusted for CP factors and also among patients over 50-yrs. The model defined patient risk groups that were analyzed for IBR rate using Kaplan Meier analyses and Cox proportional hazards to test for RT-risk group interaction. Within the cohort, 440 patients had hormone receptor positive, HER2 negative BC treated with BCS (negative margins) and +/- RT without chemotherapy, where 296 patients had complete biomarker data. CP factors individually were not predictive for RT benefit, but grade was prognostic for IBR rate (p = 0.02) after BCS without RT. In multivariable analysis, adjusting for CP factors (grade, palpability, continuous size and age), the model was predictive for RT benefit (p-interaction = 0.046), identifying patients (n = 129) with worse RT benefit (HR = 7.8) compared to baseline RT benefit. The model was not prognostic for IBR rate in patients treated with BCS without RT (16% 10-yr IBR rate) but identified patients with increased IBR rates after BCS plus RT (HR = 3.9, p<0.001), where corresponding 10-yr IBR rates increased from 3% to 15%. The model was also predictive for RT benefit in women over 50-yrs (p-interaction = 0.05). The model identified 28% of women over 50-yrs who had increased IBR rates after BCS plus RT (HR = 4.0, p = 0.004), where corresponding 10-yr IBR rates increased from 3% to 12%. The model incorporating metabolic and immune signaling axes assessed in the study was predictive for RT benefit among women with early-stage hormone receptor positive, HER2 negative BC. While CP factors were not predictive of RT benefit, the inclusion of metabolic and immune signaling axes improved identification of patients with high residual risk after BCS plus RT and can potentially aid in personalized treatment of early-stage breast cancer based on individualized risk.

Novel Radioenhancer NBTXR3 Activated by Radiotherapy in Cisplatin-Ineligible Locally Advanced HNSCC Patients: Final Results of a Phase I Trial

New approaches are needed for frail or elderly patients with locally advanced head and neck squamous cell carcinoma (LA HNSCC) who are unfit to receive cisplatin with concurrent radiotherapy (RT). NBTXR3 is a first-in-class radioenhancer, composed of functionalized hafnium oxide nanoparticles, administered by a single intratumoral (IT) injection and activated by RT. NBTXR3 locally amplifies the anti-tumoral response of RT without adding toxicity to surrounding healthy tissue as shown in a randomized trial in soft tissue sarcoma. This two-part study: dose-escalation followed by the dose-expansion part reported here, evaluated the safety and preliminary efficacy for NBTXR3 activated by RT in elderly or frail patients ineligible to cisplatin. This trial enrolled patients who had previously untreated AJCC 8th Stage III-IVA or T3, T4 SCC of the oral cavity or oropharynx (OPC) ineligible to cisplatin. Eligible patients received a single IT injection of NBTXR3 at the recommended dose (22% of the baseline tumor volume) followed by RT (IMRT 70 Gy in 35 fractions). The primary objectives of the dose expansion part were to test the recommended dose, to confirm its safety, and obtain preliminary evidence of efficacy. The secondary objectives included the evaluation of progression-free survival (PFS) and overall survival (OS). Fifty-sixpatients in the dose expansion part were treated from April 2019-January 2022; 44 patients were evaluable for objective tumor response. In the all-treated population, median age was 71.9 years. 64.3% had age-adjusted Charlson Comorbidity Index scores ≥4, 55.4% had OPC (45.2% HPV+) and 80% had T3-4. Median injected volume of NBTXR3 was 13.6 [0.5-57.1] mL. Grade ≥ 3 adverse events reported as potentially related to NBTXR3 or to injection procedure were 1.2% and 0.4% of all AEs reported, respectively. In the evaluable population, the best objective response rate of the NBTXR3 injected lesion was 81.8% with a complete response rate of 63.6%. The best overall response rate (injected and non-injected lesions) was 79.5%. Final analyses on PFS and OS with long-term follow-up will be presented. NBTXR3 IT injection followed by activation with RT was confirmed to be feasible and well tolerated in elderly or frail patients with LA HNSSC and significant comorbidities. The high rate of best overall response suggests that NBTXR3+RT is effective in this elderly population ineligible to cisplatin with a high unmet medical need. These results support our ongoing phase III study comparing NBTXR3/RT ± cetuximab vs. RT ± cetuximab in platinum-based chemotherapy ineligible elderly patients with LA-HNSCC: NANORAY 312 (NCIT04892173).

Identifying Gene-Treatment Interactions and Targetable Radiation Vulnerabilities in Glioblastoma through Coupling of In Vivo CRISPR Perturbation and Single Cell Transcriptomics

Glioblastoma (GBM) is an incurable brain tumor comprised of dynamic malignant cell states and microenvironment components that underlie treatment resistance. Here we use genome-wide CRISPR/Cas9 functional genomics to define biological drivers and therapeutic vulnerabilities across human and mouse GBM models. To interrogate these mechanisms in the context of the tumor microenvironment and in vivo physiology, we established in vivo Perturb-seq intracranially, a technique coupling functional genomics with single cell transcriptomics, where each cell is an individual experiment. Orthotopic intracranial tumor models were established using human (GBM6, GBM43) or mouse (GL261, SB28) GBM cells stably expressing CRISPR interference (CRISPRi) machinery. Perturb-seq target selection for phenotyping of gene-treatment interactions was performed using genome-wide CRISPRi screens ± radiotherapy in cell cultures. Dual sgRNA lentivirus libraries were transduced either ex vivo prior to intracranial GBM cell transplantation or in vivo using intratumor convection enhanced delivery (CED). Transcriptional phenotyping was performed using single-cell RNA-seq with CRISPR direct capture following focal brain radiotherapy (2 Gy x 5) or mock treatment. GBM cell states were validated using single-nucleus RNA-seq data from 86 primary-recurrent patient-matched GBMs. Mechanistic and functional validation was performed using small molecule inhibitors, immunohistochemistry, clonogenic assays, and in vivo survival experiments. In vivo Perturb-seq ± radiotherapy of 48 genes underlying GBM radiotherapy responses, which were enriched for DNA damage response and metabolic pathways, was performed in > 425,000 single cells. Radiotherapy induced 16 distinct GBM cell states, and genetic perturbations reprogrammed these cell states in a treatment-dependent fashion. Quantitative modeling of gene/radiotherapy interactions using high dimensional manifolds revealed in vivo-specific genetic dependencies. We revealed a critical role for Prkdc, the catalytic subunit of DNA-dependent protein kinase (DNA-PK), as a radiotherapy sensitizer through regulation of cell intrinsic growth and oxidative stress pathways, and cell extrinsic interferon and signaling pathways that altered cell-cell interactions in vivo. These pathways were also disrupted in single-nucleus RNA-seq analysis of post-radiotherapy human GBM tumors. Inhibition of Prkdc using a Food and Drug Administration approved small molecule sensitized GBM cells to radiotherapy and extended survival in mice harboring human intracranial xenografts. We establish in vivo Perturb-seq in orthotopic GBM models as a platform for simultaneous functional genomic discovery and characterization of therapeutic targets, revealing an underappreciated role for Prkdc in GBM tumors in vivo that is targetable using small molecules. These tools are adaptable for a wide range of disease models and treatment modalities.

Tumor Resistance to Fractionated Radiotherapy in Obese Mice

Obesity has reached pandemic levels in the United States and will soon surpass smoking as the number one cause of preventable cancer. Clinical data demonstrate that obese cancer patients are more resistant to radiotherapy and have higher rates of recurrence. Although a growing number of cancer patients are obese, and obesity is linked to poor outcomes with radiotherapy, little is understood about how obesity impacts the efficacy of radiotherapy. Understanding if and how obesity induces radio-resistance and how to best treat obese cancer patients is a critical unmet need. In this study we test the hypothesis that tumors in obese mice have increased resistance to fractionated radiotherapy. Control and diet induce obese (DIO) mice were generated by feeding 4-6-week-old, genetically identical, inbred C57BL/6 mice with a high-fat diet consisting of 60% kcal from fat (DIO) or a control diet consisting of 10% fat (control) until 6 months of age. Mice were then implanted with syngeneic B16F0 tumors in the hind leg. When tumors reached 5mm in diameter mice were treated with fractionated radiotherapy (12 Gy delivered in daily 4 Gy fractions X 3 days) using a 2cm electron cutout to treat the tumor + margin only. DIO mice had significantly increased body weight (control 30-40 g; DIO 50-65 g), significantly increased visceral and subcutaneous fat deposits, and elevated leptin levels. Blood glucose levels and HgbA1c in DIO mice, although slighter higher than controls, were within normal limits and did not indicate insulin resistance. Mice were divided into four groups of 8 mice (control, control + RT, DIO, DIO + RT). Fractionated radiotherapy (4 Gy x 3) significantly reduced the growth of B16F0 tumors by about three-fold in control mice compared to untreated controls. Radiotherapy failed to significantly reduce tumor size in DIO mice (compared to unirradiated DIO), although the treated tumors trended towards being modestly smaller. Additionally, tumors in the DIO + RT group were significantly larger than the tumors in the control + RT group. Initial mechanistic studies suggest increased tumor proliferation and immune dysfunction in DIO mice may induce the observed radio-resistance. Using genetically identical mice with genetically identical tumors we demonstrate, for the first time, that diet and obesity can drastically alter the anti-tumor effects of radiotherapy. Mechanistic studies and studies in other tumor models are underway. Understanding how obesity impacts radiotherapy response and developing strategies to address these issues will improve outcomes in obese patients. Thus, these studies can have a major clinical impact and represent a step towards personalized medicine by tailoring radiotherapy treatment strategies to a patient's metabolic parameters.

Predictors of Local Control with Palliative Radiotherapy for Multiple Myeloma

Palliative radiotherapy (RT) is employed for patients with multiple myeloma to improve or prevent symptoms. However, the optimal dose fractionation is not well defined. The role of cytogenetics in informing RT warrants further study. We performed an institutional analysis of patients with multiple myeloma receiving palliative RT and assessed factors associated with local progression, with a focus on dose fractionation and cytogenetic abnormalities. We queried a prospectively maintained, departmental database for consecutive patients who received palliative RT for multiple myeloma at our institution from 2015 to 2020. Double- and triple-hit were defined as the presence of two and three high-risk cytogenetic abnormalities. RT dose fractionation data were extracted from the database. Follow-up imaging was used to evaluate for progression. A total of 239 patients with 362 treated lesions were included. Twenty-five patients (10.4%) with 39 lesions had double-hit cytogenetics, and 4 patients (1.7%) with 7 lesions were triple-hit. Patients had the following number of lesions treated with RT: 1 (156, 65.3%), 2 (53, 22.2%), 3 (17, 7.1%), or >3 (13, 5.4%). The most commonly targeted sites were spine (125, 34.5%), abdomen/pelvis (67, 18.5%), and lower extremity (53, 14.6%). Most lesions received doses of 20 Gy/5 fx (132, 36.5%), 8 Gy/1 fx (93, 25.7%), or 30 Gy/10 fx (48, 13.3%). RT equivalent dose in 2 Gray fractions (EQD2) was <2000 cGy for 126 lesions (34.8%) and ≥2000 cGy for 236 lesions (65.2%). At a median follow-up of 4.3 years, the risk of local progression on a per lesion basis at 1 and 4 years was 7.8% (95% CI: 5.5-11.1) and 13.4% (10.3-17.5), respectively. No cytogenetic abnormalities were correlated with local progression. Factors significant on univariate analysis included female sex [hazard ratio (HR): 1.94 (1.02-3.71), p = .045], LDH at diagnosis [HR per 10 units/liter: 1.04 (1.09-1.08), p = .016], and number of treated lesions [HR per lesion: 1.38 (1.02-1.89), p = .039]. These three covariates were included on multivariable analysis, and the only covariate to approach significance was number of treated lesions [HR for >3 versus 1: 2.43 (0.88-6.74), p = .059]. In the overall cohort, EQD2 did not impact risk of progression. Among those with >3 treated lesions, EQD2 ≥2000 cGy was associated with a significantly lower risk of progression [HR: 0.05 (0.01-0.23), p<.001]. Double- and triple-hit status were not correlated with progression. Median overall survival in all patients was 4.1 years versus 1.5 and 0.6 years in those with double- and triple-hit disease, respectively. In this large, institutional study of patients with multiple myeloma, palliative RT achieves durable long-term local control. Patients with high disease burden may be at increased risk of progression at treated sites. This group may benefit from an EQD ≥2000 cGy. Cytogenetics, including double- and triple-hit status, do not appear to influence RT response.

Evaluating Tumor Hypoxia Radiosensitization Via Electron Paramagnetic Resonance Oxygen Imaging (EPROI).

Tumor hypoxia contributes to aggressive phenotypes and diminished therapeutic responses to radiation therapy (RT) with hypoxic tissue being 3-fold less radiosensitive than normoxic tissue. A major challenge in implementing hypoxic radiosensitizers is the lack of a high-resolution imaging modality that directly quantifies tissue-oxygen. The electron paramagnetic resonance oxygen-imager (EPROI) was used to quantify tumor oxygenation in two murine tumor models: E0771 syngeneic transplant breast cancers and primary p53/MCA soft tissue sarcomas, with the latter autochthonous model better recapitulating the tumor microenvironment in human malignancies. We hypothesized that tumor hypoxia differs between these models. We also aimed to quantify the absolute change in tumor hypoxia induced by the mitochondrial inhibitor papaverine (PPV) and its effect on RT response. Tumor oxygenation was characterized in E0771 and primary p53/MCA sarcomas via EPROI, with the former model also being quantified indirectly via diffuse reflectance spectroscopy (DRS). After confirming PPV's effect on hypoxic fraction (via EPROI), we compared the effect of 0 versus 2 mg/kg PPV prior to 20 Gy on tumor growth delay and survival. Hypoxic sarcomas were more radioresistant than normoxic sarcomas (p=0.0057, 2-way ANOVA), and high baseline hypoxic fraction was a significant (p=0.0063, Cox Regression Model) hazard in survivability regardless of treatment. Pre-treatment with PPV before RT did not radiosensitize tumors in the sarcoma or E0771 model. In the sarcoma model, EPROI successfully identified baseline hypoxic tumors. DRS quantification of total hemoglobin, saturated hemoglobin, changes in mitochondrial potential and glucose uptake showed no significant difference in E0771 tumors pre- and post-PPV. EPROI provides 3D high-resolution pO2 quantification; EPR is better suited than DRS to characterize tumor hypoxia. PPV did not radiosensitize E0771 tumors nor p53/MCA sarcomas, which may be related to the complex pattern of vasculature in each tumor. Additionally, understanding model-dependent tumor hypoxia will provide a much-needed foundation for future therapeutic studies with hypoxic radiosensitizers.

A radiomic- and dosiomic-based machine learning regression model for pretreatment planning in 177 Lu-DOTATATE therapy.

Standardized patient-specific pretreatment dosimetry planning is mandatory in the modern era of nuclear molecular radiotherapy, which may eventually lead to improvements in the final therapeutic outcome. Only a comprehensive definition of a dosage therapeutic window encompassing the range of absorbed doses, that is, helpful without being detrimental can lead to therapy individualization and improved outcomes. As a result, setting absorbed dose safety limits for organs at risk (OARs) requires knowledge of the absorbed dose-effect relationship. Data sets of consistent and reliable inter-center dosimetry findings are required to characterize this relationship. We developed and standardized a new pretreatment planning model consisting of a predictive dosimetry procedure for OARs in patients with neuroendocrine tumors (NETs) treated with 177 Lu-DOTATATE (Lutathera). In the retrospective study described herein, we used machine learning (ML) regression algorithms to predict absorbed doses in OARs by exploiting a combination of radiomic and dosiomic features extracted from patients' imaging data. Pretreatment and posttreatment data for 20 patients with NETs treated with 177 Lu-DOTATATE were collected from two clinical centers. A total of 3412 radiomic and dosiomic features were extracted from the patients' computed tomography (CT) scans and dose maps, respectively. All dose maps were generated using Monte Carlo simulations. An ML regression model was designed based on ML algorithms for predicting the absorbed dose in every OAR (liver, left kidney, right kidney, and spleen) before and after the therapy and between each therapy session, thus predicting any possible radiotoxic effects. We evaluated nine ML regression algorithms. Our predictive model achieved a mean absolute dose error (MAE, in Gy) of 0.61 for the liver, 1.58 for the spleen, 1.30 for the left kidney, and 1.35 for the right kidney between pretherapy 68 Ga-DOTATOC positron emission tomography (PET)/CT and posttherapy 177 Lu-DOTATATE single photon emission (SPECT)/CT scans. Τhe best predictive performance observed was based on the gradient boost for the liver, the left kidney and the right kidney, and on the extra tree regressor for the spleen. Evaluation of the model's performance according to its ability to predict the absorbed dose in each OAR in every possible combination of pretherapy 68 Ga-DOTATOC PET/CT and any posttherapy 177 Lu-DOTATATE treatment cycle SPECT/CT scans as well as any 177 Lu-DOTATATE SPECT/CT treatment cycle and the consequent 177 Lu-DOTATATE SPECT/CT treatment cycle revealed mean absorbed dose differences ranges from -0.55 to 0.68Gy. Incorporating radiodosiomics features from the 68 Ga-DOTATOC PET/CT and first 177 Lu-DOTATATE SPECT/CT treatment cycle scans further improved the precision and minimized the standard deviation of the predictions in nine out of 12 instances. An average improvement of 57.34% was observed (range: 17.53%-96.12%). However, it's important to note that in three instances (i.e., Ga,C.1→C3 in spleen and left kidney, and Ga,C.1→C2 in right kidney) we did not observe an improvement (absolute differences of 0.17, 0.08, and 0.05Gy, respectively). Wavelet-based features proved to have high correlated predictive value, whereas non-linear-based ML regression algorithms proved to be more capable than the linear-based of producing precise prediction in our case. The combination of radiomics and dosiomics has potential utility for personalized molecular radiotherapy (PMR) response evaluation and OAR dose prediction. These radiodosiomic features can potentially provide information on any possible disease recurrence and may be highly useful in clinical decision-making, especially regarding dose escalation issues.

Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications.

This study aimed to analyze differential radiotherapy (RT) responses according to the pathological type of lung cancer to see the possibility of applying adaptive radiotherapy (ART). ART planning with resampled-computed tomography was conducted for a total of 30 patients (20 non-small-cell lung cancer patients and 10 small-cell lung cancer patients) using a deformable image registration technique to reveal gross tumor volume (GTV) changes according to the duration of RT. The small-cell lung cancer group demonstrated an average GTV reduction of 20.95% after the first week of initial treatment (p = 0.001), whereas the adenocarcinoma and squamous cell carcinoma groups showed an average volume reduction of 20.47% (p = 0.015) and 12.68% in the second week. The application of ART according to the timing of GTV reduction has been shown to affect changes in radiation dose irradiated to normal tissues. This suggests that ART applications may have to be different depending on pathological differences in lung cancer. Through these results, the present study proposes the possibility of personalized treatment options for individual patients by individualizing ART based on specific radiation responses by pathologic types of lung cancer.