A genetic basis for the variation in the vulnerability of cancer to DNA damage

Effects of combined radiotherapy with immune checkpoint blockade on immunological memory in luminal-like subtype murine bladder cancer model

MIBC is a highly lethal disease, and the patient survival rate has not improved significantly over the last decades. UPPL is a cell line that can be used to recapitulate the luminal-like molecular subtype of bladder cancer and to discover effective treatments to be translated in patients. Here, we investigate the effects of combinational treatments of radiotherapy and immunotherapy in this recently characterized UPPL tumor-bearing mice. We first characterized the baseline tumor microenvironment and the effect of radiation, anti-PD-L1, and combinatorial treatments. Then, the mice were re-challenged with a second tumor (rechallenged tumor) in the contralateral flank of the first tumor to assess the immunological memory. Radiation slowed down the tumor growth. All treatments also decreased the neutrophil population and increased the T cell population. Anti-PD-L1 therapy was not able to synergize with radiation to further delay tumor growth. Furthermore, none of the treatments were able to generate immune memory. The treatments were not sufficient to induce a significant and lasting pool of memory cells. We show here that anti-PD-L1 treatment added to radiotherapy was not enough to achieve T cell-mediated memory in UPPL tumors. Stronger T cell activation signals may be required to enhance radiation efficacy in luminal-like bladder cancer.

Nano-sensitizer with self-amplified drug release and hypoxia normalization properties potentiates efficient chemoradiotherapy of pancreatic cancer

The hypoxic nature of pancreatic cancer, one of the most lethal malignancies worldwide, significantly impedes the effectiveness of chemoradiotherapy. Although the development of oxygen carriers and hypoxic sensitizers has shown promise in overcoming tumor hypoxia. The heterogeneity of hypoxia-primarily caused by limited oxygen penetration-has posed challenges. In this study, we designed a hypoxia-responsive nano-sensitizer by co-loading tirapazamine (TPZ), KP372-1, and MK-2206 in a metronidazole-modified polymeric vesicle. This nano-sensitizer relies on efficient endogenous NAD(P)H quinone oxidoreductase 1-mediated redox cycling induced by KP372-1, continuously consuming periphery oxygen and achieving evenly distributed hypoxia. Consequently, the normalized tumor microenvironment facilitates the self-amplified release and activation of TPZ without requiring deep penetration. The activated TPZ and metronidazole further sensitize radiotherapy, significantly reducing the radiation dose needed for extensive cell damage. Additionally, the coloaded MK-2206 complements inhibition of therapeutic resistance caused by Akt activation, synergistically enhancing the hypoxic chemoradiotherapy. This successful hypoxia normalization strategy not only overcomes hypoxia resistance in pancreatic cancer but also provides a potential universal approach to sensitize hypoxic tumor chemoradiotherapy by reshaping the hypoxic distribution.

Modelling radiobiology

Radiotherapy has played an essential role in cancer treatment for over a century, and remains one of the best-studied methods of cancer treatment. Because of its close links with the physical sciences, it has been the subject of extensive quantitative mathematical modelling, but a complete understanding of the mechanisms of radiotherapy has remained elusive. In part this is because of the complexity and range of scales involved in radiotherapy-from physical radiation interactions occurring over nanometres to evolution of patient responses over months and years. This review presents the current status and ongoing research in modelling radiotherapy responses across these scales, including basic physical mechanisms of DNA damage, the immediate biological responses this triggers, and genetic- and patient-level determinants of response. Finally, some of the major challenges in this field and potential avenues for future improvements are also discussed.

Radiation response assessment of organoids derived from patients with pancreatic cancer

Background

The effectiveness of radiotherapy for pancreatic cancer is debated. Patient-derived organoids (PDOs) already mimicked clinical radiation response in other cancer types, which could be valuable in pancreatic cancer as well. This study aimed to investigate whether PDOs can be used to model RT response in pancreatic cancer and to explore the presence of a dose-response correlation.

Methods

PDOs derived from two pancreatic cancer patients (HUB-08-B2-022A and HUB-08-B2-026B) were irradiated with doses ranging from 0 to 40 Gray. Viability assessments were conducted after seven and 10 days by measuring ATP-levels. Results were normalized, defining the viability at 0 Gray as 100 % and an absolute viability of 0 as 0 %. The relative area under the curve (rAUC) was calculated (0 = total sensitivity, 1 = total resistance).

Results

With a readout time of seven days, both HUB-08-B2-022A and HUB-08-B2-026B exhibited viability above 50 % at the highest dose of 12 Gy (rAUC of 0.79 and 0.69, respectively). With a readout time of 10 days, both PDOs showed a dose-response relation although HUB-08-B2-022A was more sensitive than HUB-08-B2-026B (rAUC of 0.37 and 0.51, respectively). Increasing the radiation dose to 40 Gy did not further affect viability, but the dose-response relation remained present (rAUC of 0.13 and 0.26, respectively). In the final experiment with a readout time of 10 days and a maximum dose of 14 Gy, the dose-response correlation was paramount in both PDOs (rAUC 0.28 and 0.45, respectively), with HUB-08-B2-022A being most sensitive.

Conclusions

In this setup, both pancreatic cancer PDOs showed an irradiation dose-response correlation. These preliminary findings suggest that pancreatic cancer PDOs are suitable for assessing radiation response in vitro. Further experiments are needed to eventually simulate treatment responses to personalized treatment strategies.

RAS-RAF-miR-296-3p signaling axis increases Rad18 expression to augment radioresistance in pancreatic and thyroid cancers

Oncogenic RAS and RAF signaling has been implicated in contributing to radioresistance in pancreatic and thyroid cancers. In this study, we sought to better clarify molecular mechanisms contributing to this effect. We discovered that miRNA 296-3p (miR-296-3p) is significantly correlated with radiosensitivity in a panel of pancreatic cancer cells, and miR-296-3p is highly expressed in normal cells, but low in cancer cell lines. Elevated expression of miR-296-3p increases radiosensitization while decreasing the expression of the DNA repair enzyme RAD18 in both pancreatic and thyroid cancer cells. RAD18 is overexpressed in both pancreatic and thyroid tumors compared to matched normal controls, and high expression of RAD18 in tumors is associated with poor prognostic features. Modulating the expression of mutant KRAS in pancreatic cancer cells or mutant BRAF in thyroid cancer cells demonstrates a tight regulation of RAD18 expression in both cancer types. Depletion of RAD18 results in DNA damage and radiation-induced cell death. Importantly, RAD18 depletion in combination with radiotherapy results in marked and sustained tumor regression in KRAS mutant pancreatic cancer orthotopic tumors and BRAF mutant thyroid heterotopic tumors. Overall, our findings identify a novel coordinated RAS/RAF-miR-296-3p-RAD18 signaling network in pancreatic and thyroid cancer cells, which leads to enhanced radioresistance.

Molecular Changes in Breast Cancer Induced by Radiation Therapy

PURPOSE

Breast cancer treatments are based on prognostic clinicopathologic features that form the basis for therapeutic guidelines. Although the utilization of these guidelines has decreased breast cancer-associated mortality rates over the past three decades, they are not adequate for individualized therapy. Radiation therapy (RT) is the backbone of breast cancer treatment. Although a highly successful therapeutic modality clinically, from a biological perspective, preclinical studies have shown RT to have the potential to alter tumor cell phenotype, immunogenicity, and the surrounding microenvironment, potentially changing the behavior of cancer cells and resulting in a significant variation in RT response. This review presents the recent advances in revealing the complex molecular changes induced by RT in the treatment of breast cancer and highlights the complexities of translating this information into clinically relevant tools for improved prognostic insights and the revelation of novel approaches for optimizing RT.

METHODS AND MATERIALS

Current literature was reviewed with a focus on recent advances made in the elucidation of tumor-associated radiation-induced molecular changes across molecular, genetic, and proteomic bases. This review was structured with the aim of providing an up-to-date overview over the very broad and complex subject matter of radiation-induced molecular changes and radioresistance, familiarizing the reader with the broader issue at hand.

RESULTS

The subject of radiation-induced molecular changes in breast cancer has been broached from various physiological focal points including that of the immune system, immunogenicity and the abscopal effect, tumor hypoxia, breast cancer classification and subtyping, molecular heterogeneity, and molecular plasticity. It is becoming increasingly apparent that breast cancer clinical subtyping alone does not adequately account for variation in RT response or radioresistance. Multiple components of the tumor microenvironment and immune system, delivered RT dose and fractionation schedules, radiation-induced bystander effects, and intrinsic tumor physiology and heterogeneity all contribute to the resultant RT outcome.

CONCLUSIONS

Despite recent advances and improvements in anticancer therapies, tumor resistance remains a significant challenge. As new analytical techniques and technologies continue to provide crucial insight into the complex molecular mechanisms of breast cancer and its treatment responses, it is becoming more evident that personalized anticancer treatment regimens may be vital in overcoming radioresistance.

Pre-existing subclones determine radioresistance in rectal cancer organoids

More than half of all patients with cancer receive radiation therapy, but resistance is commonly observed. Currently, it is unknown whether resistance to radiation therapy is acquired or inherently present. Here, we employed organoids derived from rectal cancer and single-cell whole-genome sequencing to investigate the long-term evolution of subclones in response to radiation. Comparing single-cell whole-genome karyotypes between in-vitro-unirradiated and -irradiated organoids revealed three patterns of subclonal evolution: (1) subclonal persistence, (2) subclonal extinction, and (3) subclonal expansion. Organoids in which subclonal shifts occurred (i.e., expansion or extinction) became more resistant to radiation. Although radioresistant subclones did not share recurrent copy-number alterations that could explain their radioresistance, resistance was associated with reduced chromosomal instability, an association that was also observed in 529 human cancer cell lines. These data suggest that resistance to radiation is inherently present and associated with reduced chromosomal instability.

Advances in Antitumor Effects Using Liposomal Citrinin in Induced Breast Cancer Model

The study aimed to evaluate the antitumor and toxicogenetic effects of liposomal nanoformulations containing citrinin in animal breast carcinoma induced by 7,12-dimethylbenzanthracene (DMBA). Mus musculus virgin females were divided into six groups treated with (1) olive oil (10 mL/kg); (2) 7,12-DMBA (6 mg/kg); (3) citrinin, CIT (2 mg/kg), (4) cyclophosphamide, CPA (25 mg/kg), (5) liposomal citrinin, LP-CIT (2 μg/kg), and (6) LP-CIT (6 µg/kg). Metabolic, behavioral, hematological, biochemical, histopathological, and toxicogenetic tests were performed. DMBA and cyclophosphamide induced behavioral changes, not observed for free and liposomal citrinin. No hematological or biochemical changes were observed for LP-CIT. However, free citrinin reduced monocytes and caused hepatotoxicity. During treatment, significant differences were observed regarding the weight of the right and left breasts treated with DMBA compared to negative controls. Treatment with CPA, CIT, and LP-CIT reduced the weight of both breasts, with better results for liposomal citrinin. Furthermore, CPA, CIT, and LP-CIT presented genotoxic effects for tumor, blood, bone marrow, and liver cells, although less DNA damage was observed for LP-CIT compared to CIT and CPA. Healthy cell damage induced by LP-CIT was repaired during treatment, unlike CPA, which caused clastogenic effects. Thus, LP-CIT showed advantages for its use as a model of nanosystems for antitumor studies.

Gene expression signature predicts radiation sensitivity in cell lines using the integral of dose-response curve

BACKGROUND

Although substantial efforts have been made to build molecular biomarkers to predict radiation sensitivity, the ability to accurately stratify the patients is still limited. In this study, we aim to leverage large-scale radiogenomics datasets to build genomic predictors of radiation response using the integral of the radiation dose-response curve.

METHODS

Two radiogenomics datasets consisting of 511 and 60 cancer cell lines were utilized to develop genomic predictors of radiation sensitivity. The intrinsic radiation sensitivity, defined as the integral of the dose-response curve (AUC) was used as the radioresponse variable. The biological determinants driving AUC and SF2 were compared using pathway analysis. To build the predictive model, the largest and smallest datasets consisting of 511 and 60 cancer cell lines were used as the discovery and validation cohorts, respectively, with AUC as the response variable.

RESULTS

Utilizing a compendium of three pathway databases, we illustrated that integral of the radiobiological model provides a more comprehensive characterization of molecular processes underpinning radioresponse compared to SF2. Furthermore, more pathways were found to be unique to AUC than SF2-30, 288 and 38 in KEGG, REACTOME and WIKIPATHWAYS, respectively. Also, the leading-edge genes driving the biological pathways using AUC were unique and different compared to SF2. With regards to radiation sensitivity gene signature, we obtained a concordance index of 0.65 and 0.61 on the discovery and validation cohorts, respectively.

CONCLUSION

We developed an integrated framework that quantifies the impact of physical radiation dose and the biological effect of radiation therapy in interventional pre-clinical model systems. With the availability of more data in the future, the clinical potential of this signature can be assessed, which will eventually provide a framework to integrate genomics into biologically-driven precision radiation oncology.

Therapeutic Path to Triple Knockout: Investigating the Pan-inhibitory Mechanisms of AKT, CDK9, and TNKS2 by a Novel 2-phenylquinazolinone Derivative in Cancer Therapy- An In-silico Investigation Therapy

BACKGROUND

Blocking the oncogenic Wnt//β-catenin pathway has of late been investigated as a viable therapeutic approach in the treatment of cancer. This involves the multi-targeting of certain members of the tankyrase-kinase family; Tankyrase 2 (TNKS2), Protein Kinase B (AKT), and Cyclin- Dependent Kinase 9 (CDK9), which propagate the oncogenic Wnt/β-catenin signalling pathway.

METHODS

During a recent investigation, the pharmacological activity of 2-(4-aminophenyl)-7-chloro- 3H-quinazolin-4-one was repurposed to serve as a 'triple-target' inhibitor of TNKS2, AKT and CDK9. Yet, the molecular mechanism that surrounds its multi-targeting activity remains unanswered. As such, this study aims to explore the pan-inhibitory mechanism of 2-(4-aminophenyl)-7-chloro-3H-quinazolin- 4-one towards AKT, CDK9, and TNKS2, using in silico techniques.

RESULTS

Results revealed favourable binding affinities of -34.17 kcal/mol, -28.74 kcal/mol, and -27.30 kcal/mol for 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one towards TNKS2, CDK9, and AKT, respectively. Pan-inhibitory binding of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one is illustrated by close interaction with specific residues on tankyrase-kinase. Structurally, 2-(4-aminophenyl)-7-chloro- 3H-quinazolin-4-one had an impact on the flexibility, solvent-accessible surface area, and stability of all three proteins, which was illustrated by numerous modifications observed in the unbound as well as the bound states of the structures, which evidenced the disruption of their biological function. Prediction of the pharmacokinetics and physicochemical properties of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4- one further established its inhibitory potential, evidenced by the favourable absorption, metabolism, excretion, and minimal toxicity properties.

CONCLUSION

The following structural insights provide a starting point for understanding the paninhibitory activity of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one. Determining the criticality of the interactions that exist between the pyrimidine ring and catalytic residues could offer insight into the structure-based design of innovative tankyrase-kinase inhibitors with enhanced therapeutic effects.

Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients

BACKGROUND

Cancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we analyzed the expression levels of RhoB and DNp73 proteins in rectal cancer, as captured in immunohistochemical images, to predict the 5-year survival time of two patient groups: one with preoperative radiotherapy and one without.

METHODS

The utilization of deep convolutional neural networks in medical research, particularly in clinical cancer studies, has been gaining substantial attention. This success primarily stems from their ability to extract intricate image features that prove invaluable in machine learning. Another innovative method for extracting features at multiple levels is the wavelet-scattering network. Our study combines the strengths of these two convolution-based approaches to robustly extract image features related to protein expression.

RESULTS

The efficacy of our approach was evaluated across various tissue types, including tumor, biopsy, metastasis, and adjacent normal tissue. Statistical assessments demonstrated exceptional performance across a range of metrics, including prediction accuracy, classification accuracy, precision, and the area under the receiver operating characteristic curve.

CONCLUSION

These results underscore the potential of dual convolutional learning to assist clinical researchers in the timely validation and discovery of cancer biomarkers.

Molecular Classification Predicts Response to Radiotherapy in the Randomized PORTEC-1 and PORTEC-2 Trials for Early-Stage Endometrioid Endometrial Cancer

PURPOSE

The molecular classification of endometrial cancer (EC) has proven to have prognostic value and is predictive of response to adjuvant chemotherapy. Here, we investigate its predictive value for response to external beam radiotherapy (EBRT) and vaginal brachytherapy (VBT) in early-stage endometrioid EC (EEC).

METHODS

Data of the randomized PORTEC-1 trial (n = 714) comparing pelvic EBRT with no adjuvant therapy in early-stage intermediate-risk EC and the PORTEC-2 trial (n = 427) comparing VBT with EBRT in early-stage high-intermediate-risk EC were used. Locoregional (including vaginal and pelvic) recurrence-free survival was compared between treatment groups across the four molecular classes using Kaplan-Meier's methodology and log-rank tests.

RESULTS

A total of 880 molecularly classified ECs, 484 from PORTEC-1 and 396 from PORTEC-2, were included. The majority were FIGO-2009 stage I EEC (97.2%). The median follow-up was 11.3 years. No locoregional recurrences were observed in EC with a pathogenic mutation of DNA polymerase-ε (POLEmut EC). In mismatch repair-deficient (MMRd) EC, locoregional recurrence-free survival was similar after EBRT (94.2%), VBT (94.2%), and no adjuvant therapy (90.3%; P = .74). In EC with a p53 abnormality (p53abn EC), EBRT (96.9%) had a substantial benefit over VBT (64.3%) and no adjuvant therapy (72.2%; P = .048). In EC with no specific molecular profile (NSMP EC), both EBRT (98.3%) and VBT (96.2%) yielded better locoregional control than no adjuvant therapy (87.7%; P < .0001).

CONCLUSION

The molecular classification of EC predicts response to radiotherapy in stage I EEC and may guide adjuvant treatment decisions. Omitting radiotherapy seems to be safe in POLEmut EC. The benefit of radiotherapy seems to be limited in MMRd EC. EBRT yields a significantly better locoregional recurrence-free survival than VBT or no adjuvant therapy in p53abn EC. VBT is the treatment of choice for NSMP EC as it is as effective as EBRT and significantly better than no adjuvant therapy for locoregional tumor control.

Emerging Roles of Circulating Tumor DNA for Increased Precision and Personalization in Radiation Oncology

Recent breakthroughs in circulating tumor DNA (ctDNA) technologies present a compelling opportunity to combine this emerging liquid biopsy approach with the field of radiogenomics, the study of how tumor genomics correlate with radiotherapy response and radiotoxicity. Canonically, ctDNA levels reflect metastatic tumor burden, although newer ultrasensitive technologies can be used after curative-intent radiotherapy of localized disease to assess ctDNA for minimal residual disease (MRD) detection or for post-treatment surveillance. Furthermore, several studies have demonstrated the potential utility of ctDNA analysis across various cancer types managed with radiotherapy or chemoradiotherapy, including sarcoma and cancers of the head and neck, lung, colon, rectum, bladder, and prostate . Additionally, because peripheral blood mononuclear cells are routinely collected alongside ctDNA to filter out mutations associated with clonal hematopoiesis, these cells are also available for single nucleotide polymorphism analysis and could potentially be used to detect patients at high risk for radiotoxicity. Lastly, future ctDNA assays will be utilized to better assess locoregional MRD in order to more precisely guide adjuvant radiotherapy after surgery in cases of localized disease, and guide ablative radiotherapy in cases of oligometastatic disease.

Machine Learning & Molecular Radiation Tumor Biomarkers

Developing radiation tumor biomarkers that can guide personalized radiotherapy clinical decision making is a critical goal in the effort towards precision cancer medicine. High-throughput molecular assays paired with modern computational techniques have the potential to identify individual tumor-specific signatures and create tools that can help understand heterogenous patient outcomes in response to radiotherapy, allowing clinicians to fully benefit from the technological advances in molecular profiling and computational biology including machine learning. However, the increasingly complex nature of the data generated from high-throughput and "omics" assays require careful selection of analytical strategies. Furthermore, the power of modern machine learning techniques to detect subtle data patterns comes with special considerations to ensure that the results are generalizable. Herein, we review the computational framework of tumor biomarker development and describe commonly used machine learning approaches and how they are applied for radiation biomarker development using molecular data, as well as challenges and emerging research trends.

Molecular mechanisms of tumor resistance to radiotherapy

BACKGROUND

Cancer is the most prevalent cause of death globally, and radiotherapy is considered the standard of care for most solid tumors, including lung, breast, esophageal, and colorectal cancers and glioblastoma. Resistance to radiation can lead to local treatment failure and even cancer recurrence.

MAIN BODY

In this review, we have extensively discussed several crucial aspects that cause resistance of cancer to radiation therapy, including radiation-induced DNA damage repair, cell cycle arrest, apoptosis escape, abundance of cancer stem cells, modification of cancer cells and their microenvironment, presence of exosomal and non-coding RNA, metabolic reprogramming, and ferroptosis. We aim to focus on the molecular mechanisms of cancer radiotherapy resistance in relation to these aspects and to discuss possible targets to improve treatment outcomes.

CONCLUSIONS

Studying the molecular mechanisms responsible for radiotherapy resistance and its interactions with the tumor environment will help improve cancer responses to radiotherapy. Our review provides a foundation to identify and overcome the obstacles to effective radiotherapy.

Clinical and genome-wide association analysis of chemoradiation-induced hearing loss in nasopharyngeal carcinoma

Chemoradiation-induced hearing loss (CRIHL) is one of the most devasting side effects for nasopharyngeal carcinoma (NPC) patients, which seriously affects survivors' long-term quality of life. However, few studies have comprehensively characterized the risk factors for CRIHL. In this study, we found that age at diagnosis, tumor stage, and concurrent cisplatin dose were positively associated with chemoradiation-induced hearing loss. We performed a genome-wide association study (GWAS) in 777 NPC patients and identified rs1050851 (within the exon 2 of NFKBIA), a variant with a high deleteriousness score, to be significantly associated with hearing loss risk (HR = 5.46, 95% CI 2.93-10.18, P = 9.51 × 10^-08). The risk genotype of rs1050851 was associated with higher NFKBIA expression, which was correlated with lower cellular tolerance to cisplatin. According to permutation-based enrichment analysis, the variants mapping to 149 hereditary deafness genes were significantly enriched among GWAS top signals, which indicated the genetic similarity between hereditary deafness and CRIHL. Pathway analysis suggested that synaptic signaling was involved in the development of CRIHL. Additionally, the risk score integrating genetic and clinical factors can predict the risk of hearing loss with a relatively good performance in the test set. Collectively, this study shed new light on the etiology of chemoradiation-induced hearing loss, which facilitates high-risk individuals' identification for personalized prevention and treatment.

Gene expression variability in long-term survivors of childhood cancer and cancer-free controls in response to ionizing irradiation

BACKGROUND

Differential expression analysis is usually adjusted for variation. However, most studies that examined the expression variability (EV) have used computations affected by low expression levels and did not examine healthy tissue. This study aims to calculate and characterize an unbiased EV in primary fibroblasts of childhood cancer survivors and cancer-free controls (N0) in response to ionizing radiation.

METHODS

Human skin fibroblasts of 52 donors with a first primary neoplasm in childhood (N1), 52 donors with at least one second primary neoplasm (N2 +), as well as 52 N0 were obtained from the KiKme case-control study and exposed to a high (2 Gray) and a low dose (0.05 Gray) of X-rays and sham- irradiation (0 Gray). Genes were then classified as hypo-, non-, or hyper-variable per donor group and radiation treatment, and then examined for over-represented functional signatures.

RESULTS

We found 22 genes with considerable EV differences between donor groups, of which 11 genes were associated with response to ionizing radiation, stress, and DNA repair. The largest number of genes exclusive to one donor group and variability classification combination were all detected in N0: hypo-variable genes after 0 Gray (n = 49), 0.05 Gray (n = 41), and 2 Gray (n = 38), as well as hyper-variable genes after any dose (n = 43). While after 2 Gray positive regulation of cell cycle was hypo-variable in N0, (regulation of) fibroblast proliferation was over-represented in hyper-variable genes of N1 and N2+. In N2+, 30 genes were uniquely classified as hyper-variable after the low dose and were associated with the ERK1/ERK2 cascade. For N1, no exclusive gene sets with functions related to the radiation response were detected in our data.

CONCLUSION

N2+ showed high degrees of variability in pathways for the cell fate decision after genotoxic insults that may lead to the transfer and multiplication of DNA-damage via proliferation, where apoptosis and removal of the damaged genome would have been appropriate. Such a deficiency could potentially lead to a higher vulnerability towards side effects of exposure to high doses of ionizing radiation, but following low-dose applications employed in diagnostics, as well.

NFE2L2 Mutations Enhance Radioresistance in Head and Neck Cancer by Modulating Intratumoral Myeloid Cells

Radiotherapy (RT) is one of the primary treatments of head and neck squamous cell carcinoma (HNSCC), which has a high-risk of locoregional failure (LRF). Presently, there is no reliable predictive biomarker of radioresistance in HNSCC. Here, we found that mutations in NFE2L2, which encodes Nrf2, are associated with a significantly higher rate of LRF in patients with oral cavity cancer treated with surgery and adjuvant (chemo)radiotherapy but not in those treated with surgery alone. Somatic mutation of NFE2L2 led to Nrf2 activation and radioresistance in HNSCC cells. Tumors harboring mutant Nrf2E79Q were substantially more radioresistant than tumors with wild-type Nrf2 in immunocompetent mice, whereas the difference was diminished in immunocompromised mice. Nrf2E79Q enhanced radioresistance through increased recruitment of intratumoral polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) and reduction of M1-polarized macrophages. Treatment with the glutaminase inhibitor CB-839 overcame the radioresistance induced by Nrf2E79Q or Nrf2E79K. RT increased expression of PMN-MDSC-attracting chemokines, including CXCL1, CXLC3, and CSF3, in Nrf2E79Q-expressing tumors via the TLR4, which could be reversed by CB-839. This study provides insights into the impact of NFE2L2 mutations on radioresistance and suggests that CB-839 can increase radiosensitivity by switching intratumoral myeloid cells to an antitumor phenotype, supporting clinical testing of CB-839 with RT in HNSCC with NFE2L2 mutations.

SIGNIFICANCE

NFE2L2 mutations are predictive biomarkers of radioresistance in head and neck cancer and confer sensitivity to glutaminase inhibitors to overcome radioresistance.

A Novel Subgroup of UCHL1-Related Cancers Is Associated with Genomic Instability and Sensitivity to DNA-Damaging Treatment

PURPOSE

Identification of molecularly-defined cancer subgroups and targeting tumor-specific vulnerabilities have a strong potential to improve treatment response and patient outcomes but remain an unmet challenge of high clinical relevance, especially in head and neck squamous cell carcinoma (HNSC).

EXPERIMENTAL DESIGN

We established a UCHL1-related gene set to identify and molecularly characterize a UCHL1-related subgroup within TCGA-HNSC by integrative analysis of multi-omics data. An extreme gradient boosting model was trained on TCGA-HNSC based on GSVA scores for gene sets of the MSigDB to robustly predict UCHL1-related cancers in other solid tumors and cancer cell lines derived thereof. Potential vulnerabilities of UCHL1-related cancer cells were elucidated by an in-silico drug screening approach.

RESULTS

We established a 497-gene set, which stratified the TCGA-HNSC cohort into distinct subgroups with a UCHL1-related or other phenotype. UCHL1-related HNSC were characterized by higher frequencies of genomic alterations, which was also evident for UCHL1-related cancers of other solid tumors predicted by the classification model. These data indicated an impaired maintenance of genomic integrity and vulnerability for DNA-damaging treatment, which was supported by a favorable prognosis of UCHL1-related tumors after radiotherapy, and a higher sensitivity of UCHL1-related cancer cells to irradiation or DNA-damaging compounds (e.g., Oxaliplatin).

CONCLUSION

Our study established UCHL1-related cancers as a novel subgroup across most solid tumor entities with a unique molecular phenotype and DNA-damaging treatment as a specific vulnerability, which requires further proof-of-concept in pre-clinical models and future clinical trials.

Analysis of Tumor Mutational Burden, Progression-Free Survival, and Local-Regional Control in Patents with Locally Advanced Non-Small Cell Lung Cancer Treated With Chemoradiation and Durvalumab

IMPORTANCE

The addition of consolidative durvalumab to chemoradiation has improved disease control and survival in locally advanced non-small cell lung cancer (NSCLC). However, there remains a need to identify biomarkers for response to this therapy to allow for risk adaptation and personalization.

OBJECTIVES

To evaluate whether TMB or other variants associated with radiation response are also associated with outcomes following definitive chemoradiation and adjuvant durvalumab among patients with locally advanced unresectable NSCLC.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included consecutive patients with unresectable locally advanced NSCLC treated with chemoradiation and adjuvant durvalumab between November 2013 and March 2020 who had prospective comprehensive genomic profiling. This study was completed at a multisite tertiary cancer center. The median (IQR) follow-up time was 26 (21-36) months. Statistical analysis was conducted from April to October 2022.

EXPOSURES

Patients were grouped into TMB-high (≥10 mutations/megabase [mt/Mb]) and TMB-low (<10 mt/Mb) groups and were additionally evaluated by the presence of somatic alterations associated with radiation resistance (KEAP1/NFE2L2) or radiation sensitivity (DNA damage repair pathway).

MAIN OUTCOMES AND MEASURES

The primary outcomes were 24-month local-regional failure (LRF) and progression-free survival (PFS).

RESULTS

In this cohort study of 81 patients (46 [57%] male patients; median [range] age, 67 [45-85] years), 36 patients (44%) had TMB-high tumors (≥10 mt/Mb). Patients with TMB-high vs TMB-low tumors had markedly lower 24-month LRF (9% [95% CI, 0%-46%] vs 51% [95% CI, 36%-71%]; P = .001) and improved 24-month PFS (66% [95% CI, 54%-84%] vs 27% [95% CI, 13%-40%]; P = .003). The 24-month LRF was 52% (95% CI, 25%-84%) among patients with KEAP1/NFE2L2-altered tumors compared with 27% (95% CI, 17%-42%) among patients with KEAP1/NFE2L2-wildtype tumors (P = .05). On Cox analysis, only TMB status was associated with LRF (hazard ratio [HR], 0.17; 95% CI, 0.03-0.64; P = .02) and PFS (HR, 0.45; 95% CI, 0.21-0.90; P = .03). Histology, disease stage, Eastern Cooperative Oncology Group status, programmed cell death ligand 1 expression, and pathogenic KEAP1/NFE2L2, KRAS, and DNA damage repair pathway alterations were not significantly associated with LRF or PFS.

CONCLUSIONS AND RELEVANCE

In this cohort study, TMB-high status was associated with improved local-regional control and PFS after definitive chemoradiation and adjuvant durvalumab. TMB status may facilitate risk-adaptive radiation strategies in unresectable locally advanced NSCLC.

PI3K-AKT-Targeting Breast Cancer Treatments: Natural Products and Synthetic Compounds

Breast cancer is the most commonly diagnosed cancer in women. The high incidence of breast cancer, which is continuing to rise, makes treatment a significant challenge. The PI3K-AKT pathway and its downstream targets influence various cellular processes. In recent years, mounting evidence has shown that natural products and synthetic drugs targeting PI3K-AKT signaling have the potential to treat breast cancer. In this review, we discuss the role of the PI3K-AKT signaling pathway in the occurrence and development of breast cancer and highlight PI3K-AKT-targeting natural products and drugs in clinical trials for the treatment of breast cancer.

Image-Based Deep Neural Network for Individualizing Radiotherapy Dose Is Transportable Across Health Systems

PURPOSE

We developed a deep neural network that queries the lung computed tomography-derived feature space to identify radiation sensitivity parameters that can predict treatment failures and hence guide the individualization of radiotherapy dose. In this article, we examine the transportability of this model across health systems.

METHODS

This multicenter cohort-based registry included 1,120 patients with cancer in the lung treated with stereotactic body radiotherapy. Pretherapy lung computed tomography images from the internal study cohort (n = 849) were input into a multitask deep neural network to generate an image fingerprint score that predicts time to local failure. Deep learning (DL) scores were input into a regression model to derive iGray, an individualized radiation dose estimate that projects a treatment failure probability of < 5% at 24 months. We validated our findings in an external, holdout cohort (n = 271).

RESULTS

There were substantive differences in the baseline patient characteristics of the two study populations, permitting an assessment of model transportability. In the external cohort, radiation treatments in patients with high DL scores failed at a significantly higher rate with 3-year cumulative incidences of local failure of 28.5% (95% CI, 19.8 to 37.8) versus 10.2% (95% CI, 5.9 to 16.2; hazard ratio, 3.3 [95% CI, 1.74 to 6.49]; P < .001). A model that included DL score alone predicted treatment failures with a concordance index of 0.68 (95% CI, 0.59 to 0.77), which had a similar performance to a nested model derived from within the internal cohort (0.70 [0.64 to 0.75]). External cohort patients with iGray values that exceeded the delivered doses had proportionately higher rates of local failure (P < .001).

CONCLUSION

Our results support the development and implementation of new DL-guided treatment guidance tools in the image-replete and highly standardized discipline of radiation oncology.

The Mutational Landscape of Cancer's Vulnerability to Ionizing Radiation

PURPOSE

Large-scale sequencing efforts have established that cancer-associated genetic alterations are highly diverse, posing a challenge to the identification of variants that regulate complex phenotypes like radiation sensitivity. The impact of the vast majority of rare or common genetic variants on the sensitivity of cancers to radiotherapy remains largely unknown.

EXPERIMENTAL DESIGN

We developed a scalable gene editing and irradiation platform to assess the role of categories of variants in cells. Variants were prioritized on the basis of genotype-phenotype associations from a previously completed large-scale cancer cell line radiation profiling study. Altogether, 488 alleles (396 unique single-nucleotide variants) from 92 genes were generated and profiled in an immortalized lung cell line, BEAS-2B. We validated our results in other cell lines (TRT-HU1 and NCI-H520), in vivo via the use of both cell line and patient-derived murine xenografts, and in clinical cohorts.

RESULTS

We show that resistance to radiation is characterized by substantial inter- and intra-gene allelic variation. Some genes (e.g., KEAP1) demonstrated significant intragenic allelic variation in the magnitude of conferred resistance and other genes (e.g., CTNNB1) displayed both resistance and sensitivity in a protein domain-dependent manner. We combined results from our platform with gene expression and metabolite features and identified the upregulation of amino acid transporters that facilitate oxidative reductive capacity and cell-cycle deregulation as key regulators of radiation sensitivity.

CONCLUSIONS

Our results reveal new insights into the genetic determinants of tumor sensitivity to radiotherapy and nominate a multitude of cancer mutations that are predicted to impact treatment efficacy.

The State of Preclinical Modeling for Early Phase Cancer Trials Using Molecularly Targeted Agents with Radiation

Preclinical studies inform and guide the development of novel treatment combination strategies that bridge the laboratory with the clinic. We aimed to evaluate approaches cancer researchers used to justify advancing new combinations of molecularly targeted agents and radiation treatment into early-phase human clinical trials. Unsolicited early phase clinical trial proposals submitted to the National Cancer Institute's Cancer Therapy Evaluation Program between January 2016 and July 2020 were curated to quantify key characteristics and proportion of preclinical data provided by trialists seeking to conduct molecularly targeted agent-radiation combination studies in cancer patients. These data elucidate the current landscape for how the rationale for a molecularly targeted agent-radiation combination therapy is supported by preclinical research and illustrate unique challenges faced in translation at the intersection of precision medicine and radiation oncology.

Radiotherapy induced immunogenic cell death by remodeling tumor immune microenvironment

Emerging evidence indicates that the induction of radiotherapy(RT) on the immunogenic cell death (ICD) is not only dependent on its direct cytotoxic effect, changes in the tumor immune microenvironment also play an important role in it. Tumor immune microenvironment (TIME) refers to the immune microenvironment that tumor cells exist, including tumor cells, inflammatory cells, immune cells, various signaling molecules and extracellular matrix. TIME has a barrier effect on the anti-tumor function of immune cells, which can inhibit all stages of anti-tumor immune response. The remodeling of TIME caused by RT may affect the degree of immunogenicity, and make it change from immunosuppressive phenotype to immunostimulatory phenotype. It is of great significance to reveal the causes of immune escape of tumor cells, especially for the treatment of drug-resistant tumor. In this review, we focus on the effect of RT on the TIME, the mechanism of RT in reversing the TIME to suppress intrinsic immunity, and the sensitization effect of the remodeling of TIME caused by RT on the effectiveness of immunotherapy.

A meta-learning approach to improving radiation response prediction in cancers

PURPOSE

Predicting the efficacy of radiotherapy in individual patients has drawn widespread attention, but the limited sample size remains a bottleneck for utilizing high-dimensional multi-omics data to guide personalized radiotherapy. We hypothesize the recently developed meta-learning framework could address this limitation.

METHODS AND MATERIALS

By combining gene expression, DNA methylation, and clinical data of 806 patients who had received radiotherapy from The Cancer Genome Atlas (TCGA), we applied the Model-Agnostic Meta-Learning (MAML) framework to tasks consisting of pan-cancer data, to obtain the best initial parameters of a neural network for a specific cancer with smaller number of samples. The performance of meta-learning framework was compared with four traditional machine learning methods based on two training schemes, and tested on Cancer Cell Line Encyclopedia (CCLE) and Chinese Glioma Genome Atlas (CGGA) datasets. Moreover, biological significance of the models was investigated by survival analysis and feature interpretation.

RESULTS

The mean AUC (Area under the ROC Curve) [95% confidence interval] of our models across nine cancer types was 0.702 [0.691-0.713], which improved by 0.166 on average over other the four machine learning methods on two training schemes. Our models performed significantly better (p < 0.05) in seven cancer types and performed comparable to the other predictors in the rest of two cancer types. The more pan-cancer samples were used to transfer meta-knowledge, the greater the performance improved (p < 0.05). The predicted response scores that our models generated were negatively correlated with cell radiosensitivity index in four cancer types (p < 0.05), while not statistically significant in the other three cancer types. Moreover, the predicted response scores were shown to be prognostic factors in seven cancer types and eight potential radiosensitivity-related genes were identified.

CONCLUSIONS

For the first time, we established the meta-learning approach to improving individual radiation response prediction by transferring common knowledge from pan-cancer data with MAML framework. The results demonstrated the superiority, generalizability, and biological significance of our approach.

Androgen and oestrogen receptor co-expression determines the efficacy of hormone receptor-mediated radiosensitisation in breast cancer

PURPOSE

Radiation therapy (RT) and hormone receptor (HR) inhibition are used for the treatment of HR-positive breast cancers; however, little is known about the interaction of the androgen receptor (AR) and estrogen receptor (ER) in response to RT in AR-positive, ER-positive (AR+/ER+) breast cancers. Here we assessed radiosensitisation of AR+/ER+ cell lines using pharmacologic or genetic inhibition/degradation of AR and/or ER.

METHODS

Radiosensitisation was assessed with AR antagonists (enzalutamide, apalutamide, darolutamide, seviteronel, ARD-61), ER antagonists (tamoxifen, fulvestrant) or using knockout of AR.

RESULTS

Treatment with AR antagonists or ER antagonists in combination with RT did not result in radiosensitisation changes (radiation enhancement ratios [rER]: 0.76-1.21). Fulvestrant treatment provided significant radiosensitisation of CAMA-1 and BT-474 cells (rER: 1.06-2.0) but not ZR-75-1 cells (rER: 0.9-1.11). Combining tamoxifen with enzalutamide did not alter radiosensitivity using a 1 h or 1-week pretreatment (rER: 0.95-1.14). Radiosensitivity was unchanged in AR knockout compared to Cas9 cells (rER: 1.07 ± 0.11), and no additional radiosensitisation was achieved with tamoxifen or fulvestrant compared to Cas9 cells (rER: 0.84-1.19).

CONCLUSION

While radiosensitising in AR + TNBC, AR inhibition does not modulate radiation sensitivity in AR+/ER+ breast cancer. The efficacy of ER antagonists in combination with RT may also be dependent on AR expression.

Combining Targeted Radionuclide Therapy and Immune Checkpoint Inhibition for Cancer Treatment

The development of immunotherapy, in particular immune checkpoint inhibitors (ICI), has revolutionized cancer treatment in the past decades. However, its efficacy is still limited to subgroups of patients with cancer. Therefore, effective treatment combination strategies are needed. Here, radiotherapy is highly promising, as it can induce immunogenic cell death, triggering the release of pro-inflammatory cytokines, thereby creating an immunogenic phenotype and sensitizing tumors to ICI. Recently, targeted radionuclide therapy (TRT) has attained significant interest for cancer treatment. In this approach, a tumor-targeting radiopharmaceutical is used to specifically deliver a therapeutic radiation dose to all tumor cells, including distant metastatic lesions, while limiting radiation exposure to healthy tissue. However, fundamental differences between TRT and conventional radiotherapy make it impossible to directly extrapolate the biological effects from conventional radiotherapy to TRT. In this review, we present a comprehensive overview of studies investigating the immunomodulatory effects of TRT and the efficacy of combined TRT-ICI treatment. Preclinical studies have evaluated a variety of murine cancer models in which α- or β-emitting radionuclides were directed to a diverse set of targets. In addition, clinical trials are ongoing to assess safety and efficacy of combined TRT-ICI in patients with cancer. Taken together, research indicates that combining TRT and ICI might improve therapeutic response in patients with cancer. Future research has to disclose what the optimal conditions are in terms of dose and treatment schedule to maximize the efficacy of this combined approach.

Interindividual variation contributes to differential PCB 126 induced gene expression in primary breast epithelial cells and tissues

PCB 126 is a pervasive, dioxin-like chemical pollutant which can activate the aryl hydrocarbon receptor (AhR). Despite being banned from the market, PCB 126 can be detected in breast milk to this day. The extent to which interindividual variation impacts the adverse responses to this chemical in the breast tissue remains unclear. This study aimed to investigate the impact of 3 nM PCB 126 on gene expression in a panel of genetically diverse benign human breast epithelial cell (HBEC) cultures and patient derived breast tissues. Six patient derived HBEC cultures were treated with 3 nM PCB 126. RNAseq was used to interrogate the impact of exposure on differential gene expression. Gene expression changes from the top critical pathways were confirmed via qRT-PCR in a larger panel of benign patient derived HBEC cultures, as well as in patient-derived breast tissue explant cultures. RNAseq analysis of HBEC cultures revealed a signature of 144 genes significantly altered by 3 nM PCB 126 treatment. Confirmation of 8 targets using a panel of 12 HBEC cultures and commercially available breast cell lines demonstrated that while the induction of canonical downstream target gene, CYP1A1, was consistent across our primary HBECs, other genes including AREG, S100A8, IL1A, IL1B, MMP7, and CCL28 exhibited significant variability across individuals. The dependence on the activity of the aryl hydrocarbon receptor was confirmed using inhibitors. PCB 126 can induce significant and consistent changes in gene expression associated with xenobiotic metabolism in benign breast epithelial cells. Although the induction of most genes was reliant on the AhR, significant variability was noted between genes and individuals. These data suggest that there is a bifurcation of the pathway following AhR activation that contributes to the variation in interindividual responses.

Targeting Squalene Epoxidase Interrupts Homologous Recombination via the ER Stress Response and Promotes Radiotherapy Efficacy

Over 50% of all patients with cancer are treated with radiotherapy. However, radiotherapy is often insufficient as a monotherapy and requires a nontoxic radiosensitizer. Squalene epoxidase (SQLE) controls cholesterol biosynthesis by converting squalene to 2,3-oxidosqualene. Given that SQLE is frequently overexpressed in human cancer, this study investigated the importance of SQLE in breast cancer and non-small cell lung cancer (NSCLC), two cancers often treated with radiotherapy. SQLE-positive IHC staining was observed in 68% of breast cancer and 56% of NSCLC specimens versus 15% and 25% in normal breast and lung tissue, respectively. Importantly, SQLE expression was an independent predictor of poor prognosis, and pharmacologic inhibition of SQLE enhanced breast and lung cancer cell radiosensitivity. In addition, SQLE inhibition enhanced sensitivity to PARP inhibition. Inhibition of SQLE interrupted homologous recombination by suppressing ataxia-telangiectasia mutated (ATM) activity via the translational upregulation of wild-type p53-induced phosphatase (WIP1), regardless of the p53 status. SQLE inhibition and subsequent squalene accumulation promoted this upregulation by triggering the endoplasmic reticulum (ER) stress response. Collectively, these results identify a novel tumor-specific radiosensitizer by revealing unrecognized cross-talk between squalene metabolites, ER stress, and the DNA damage response. Although SQLE inhibitors have been used as antifungal agents in the clinic, they have not yet been used as antitumor agents. Repurposing existing SQLE-inhibiting drugs may provide new cancer treatments.

SIGNIFICANCE

Squalene epoxidase inhibitors are novel tumor-specific radiosensitizers that promote ER stress and suppress homologous recombination, providing a new potential therapeutic approach to enhance radiotherapy efficacy.

The Radiosensitivity Index (RSI) Gene Signature Identifies Distinct Tumor Immune Microenvironment Characteristics Associated with Susceptibility to Radiotherapy

PURPOSE

Radiotherapy (RT) is a mainstay of cancer care and accumulating evidence suggests the potential for synergism with components of the immune response. However, little data describes the tumor immune contexture in relation to RT-sensitivity. To address this challenge, we employed the radiation sensitivity index (RSI) gene signature to estimate the RT-sensitivity of >10,000 primary tumors and characterized their immune microenvironments in relation to the RSI.

MATERIAL AND METHODS

We analyzed gene expression profiles of 10,469 primary tumors (31 types) within a prospective tissue collection protocol. The RT-sensitivity of each tumor was estimated by the RSI and respective distributions were characterized. The tumor biology measured by the RSI was evaluated by differentially expressed genes (DEGs) combined with single sample gene set enrichment analysis (ssGSEA). Differences in the expression of immune regulatory molecules were assessed and deconvolution algorithms were used to estimate immune cell infiltrates in relation to the RSI. A subset (n=2,368) of tumors underwent DNA sequencing for mutational frequency characterization.

RESULTS

We identified a wide range of RSI values within and across various tumor types, with several demonstrating non-unimodal distributions (e.g. colon, renal, lung, prostate, esophagus, pancreas and PAM50 breast subtypes; p <0.05). Across all tumors types, stratifying RSI at a tumor type-specific median, identified 7,148 DEGs, of which 146 were coordinate in direction. Network topology analysis demonstrates RSI measures a coordinated STAT1, IRF1, and CCL4/MIP-1β transcriptional network. Tumors with an estimated high sensitivity to RT demonstrated distinct enrichment of interferon-associated signaling pathways and immune cell infiltrates (e.g. CD8+ T cells, activated natural killer cells, M1-macrophages; q < 0.05), which was in the context of diverse expression patterns of various immunoregulatory molecules.

CONCLUSION

This analysis describes the immune microenvironments of patient tumors in relation to the RSI gene expression signature.

RadSigBench: a framework for benchmarking functional genomics signatures of cancer cell radiosensitivity

Multiple transcriptomic predictors of tumour cell radiosensitivity (RS) have been proposed, but they have not been benchmarked against one another or to control models. To address this, we present RadSigBench, a comprehensive benchmarking framework for RS signatures. The approach compares candidate models to those developed from randomly resampled control signatures and from cellular processes integral to the radiation response. Robust evaluation of signature accuracy, both overall and for individual tissues, is performed. The NCI60 and Cancer Cell Line Encyclopaedia datasets are integrated into our workflow. Prediction of two measures of RS is assessed: survival fraction after 2 Gy and mean inactivation dose. We apply the RadSigBench framework to seven prominent published signatures of radiation sensitivity and test for equivalence to control signatures. The mean out-of-sample R2 for the published models on test data was very poor at 0.01 (range: -0.05 to 0.09) for Cancer Cell Line Encyclopedia and 0.00 (range: -0.19 to 0.19) in the NCI60 data. The accuracy of both published and cellular process signatures investigated was equivalent to the resampled controls, suggesting that these signatures contain limited radiation-specific information. Enhanced modelling strategies are needed for effective prediction of intrinsic RS to inform clinical treatment regimes. We make recommendations for methodological improvements, for example the inclusion of perturbation data, multiomics, advanced machine learning and mechanistic modelling. Our validation framework provides for robust performance assessment of ongoing developments in intrinsic RS prediction.

Estrogen receptor inhibition mediates radiosensitization of ER-positive breast cancer models

Endocrine therapy (ET) is an effective first-line therapy for women with estrogen receptor-positive (ER + ) breast cancers. While both ionizing radiation (RT) and ET are used for the treatment of women with ER+ breast cancer, the most effective sequencing of therapy and the effect of ET on tumor radiosensitization remains unclear. Here we sought to understand the effects of inhibiting estrogen receptor (ER) signaling in combination with RT in multiple preclinical ER+ breast cancer models. Clonogenic survival assays were performed using variable pre- and post-treatment conditions to assess radiosensitization with estradiol, estrogen deprivation, tamoxifen, fulvestrant, or AZD9496 in ER+ breast cancer cell lines. Estrogen stimulation was radioprotective (radiation enhancement ratios [rER]: 0.51–0.82). Conversely, when given one hour prior to RT, ER inhibition or estrogen depletion radiosensitized ER+ MCF-7 and T47D cells (tamoxifen rER: 1.50–1.60, fulvestrant rER: 1.76–2.81, AZD9496 rER: 1.33–1.48, estrogen depletion rER: 1.47–1.51). Combination treatment resulted in an increase in double-strand DNA (dsDNA) breaks as a result of inhibition of non-homologous end joining-mediated dsDNA break repair with no effect on homologous recombination. Treatment with tamoxifen or fulvestrant in combination with RT also increased the number of senescent cells but did not affect apoptosis or cell cycle distribution. Using an MCF-7 xenograft model, concurrent treatment with tamoxifen and RT was synergistic and resulted in a significant decrease in tumor volume and a delay in time to tumor doubling without significant toxicity. These findings provide preclinical evidence that concurrent treatment with ET and RT may be an effective radiosensitization strategy.

Impacts of the STING-IFNAR1-STAT1-IRF1 pathway on the cellular immune reaction induced by fractionated irradiation

Radiotherapy (RT) combined with immune checkpoint inhibitors (ICIs) has recently produced outstanding results and is expected to be adaptable for various cancers. However, the precise molecular mechanism by which immune reactions are induced by fractionated RT is still controversial. We aimed to investigate the mechanism of the immune response regarding multifractionated, long-term radiation, which is most often combined with immunotherapy. Two human esophageal cancer cell lines, KYSE-450 and OE-21, were irradiated by fractionated irradiation (FIR) daily at a dose of 3 Gy in 5 days per week for 2 weeks. Western blotting (WB), and RNA sequencing identified type I interferon (IFN) and the STING pathway as candidates which regulate immune response by FIR. We inhibited STING, IFNAR1, STAT1 and IRF1 and investigated the effects on the immune response in cancer cells and the invasion of surrounding immune cells. We herein revealed type I IFN-dependent immune reactions and the positive feedback of STING, IRF1 and phosphorylated STAT1 induced by FIR. Knocking out STING, IFNAR1, STAT1 and IRF1 resulted in a poorer immunological response than that in wild-type cells. The STING-knockout KYSE-450 cell line exhibited significantly less invasion of peripheral blood mononuclear cells (PBMCs) than the wild-type cell line under FIR. In the analysis of STING-knockout cells and migrated PBMCs, we confirmed the occurrence of STING-dependent immune activation under FIR. In conclusion, we identified that the STING-IFNAR1-STAT1-IRF1 axis regulates immune reactions in cancer cells triggered by FIR and that the STING pathway also contributes to immune cell invasion of cancer cells.

Illuminating lncRNA Function Through Target Prediction

Most of the transcribed human genome codes for noncoding RNAs (ncRNAs), and long noncoding RNAs (lncRNAs) make for the lion's share of the human ncRNA space. Despite growing interest in lncRNAs, because there are so many of them, and because of their tissue specialization and, often, lower abundance, their catalog remains incomplete and there are multiple ongoing efforts to improve it. Consequently, the number of human lncRNA genes may be lower than 10,000 or higher than 200,000. A key open challenge for lncRNA research, now that so many lncRNA species have been identified, is the characterization of lncRNA function and the interpretation of the roles of genetic and epigenetic alterations at their loci. After all, the most important human genes to catalog and study are those that contribute to important cellular functions-that affect development or cell differentiation and whose dysregulation may play a role in the genesis and progression of human diseases. Multiple efforts have used screens based on RNA-mediated interference (RNAi), antisense oligonucleotide (ASO), and CRISPR screens to identify the consequences of lncRNA dysregulation and predict lncRNA function in select contexts, but these approaches have unresolved scalability and accuracy challenges. Instead-as was the case for better-studied ncRNAs in the past-researchers often focus on characterizing lncRNA interactions and investigating their effects on genes and pathways with known functions. Here, we focus most of our review on computational methods to identify lncRNA interactions and to predict the effects of their alterations and dysregulation on human disease pathways.

Impact of somatic mutations on clinical and pathologic outcomes in borderline resectable and locally advanced pancreatic cancer treated with neoadjuvant chemotherapy and stereotactic body radiotherapy followed by surgical resection

PURPOSE

The purpose of this study was to determine if somatic mutations are associated with clinical and pathologic outcomes in patients with borderline resectable pancreatic cancer (BRPC) or locally advanced pancreatic cancer (LAPC) who were treated with neoadjuvant chemotherapy and stereotactic body radiotherapy (SBRT).

MATERIALS AND METHODS

Patients treated with neoadjuvant chemotherapy and SBRT followed by surgical resection from August 2016 to January 2019 and who underwent next generation sequencing of their primary tumor were included in the study. Next-generation sequencing was performed either in-house with a Solid Tumor Panel or with FoundationOne CDx. Univariate (UVA) and multivariable analyses (MVA) were performed to determine associations between somatic mutations and pathologic and clinical outcomes.

RESULTS

Thirty-five patients were included in the study. Chemotherapy consisted of modified FOLFIRINOX, gemcitabine and nab-paclitaxel, or gemcitabine and capecitabine. Patients were treated with SBRT in 33 Gy in 5 fractions. On UVA and MVA, tumors with KRAS G12V mutation demonstrated better pathologic tumor regression grade (TRG) to neoadjuvant therapy when compared to tumors with other KRAS mutations (odds ratio = 0.087; 95% confidence interval [CI], 0.009-0.860; p = 0.036). On UVA and MVA, mutations in NOTCH1/2 were associated with worse overall survival (hazard ratio [HR] = 4.15; 95% CI, 1.57-10.95; p = 0.004) and progression-free survival (HR = 3.61; 95% CI, 1.41-9.28; p = 0.008). On UVA, only mutations in NOTCH1/2 were associated with inferior distant metastasis-free survival (HR = 3.38; 95% CI, 1.25-9.16; p = 0.017).

CONCLUSION

In BRPC and LAPC, the KRAS G12V mutation was associated with better TRG following chemotherapy and SBRT. Additionally, NOTCH1/2 mutations were associated with worse overall survival, distant metastasis-free survival, and progression-free survival.

Oncogenic KRAS drives radioresistance through upregulation of NRF2-53BP1-mediated non-homologous end-joining repair

KRAS-activating mutations are oncogenic drivers and are correlated with radioresistance of multiple cancers, including colorectal cancer, but the underlying precise molecular mechanisms remain elusive. Herein we model the radiosensitivity of isogenic HCT116 and SW48 colorectal cancer cell lines bearing wild-type or various mutant KRAS isoforms. We demonstrate that KRAS mutations indeed lead to radioresistance accompanied by reduced radiotherapy-induced mitotic catastrophe and an accelerated release from G2/M arrest. Moreover, KRAS mutations result in increased DNA damage response and upregulation of 53BP1 with associated increased non-homologous end-joining (NHEJ) repair. Remarkably, KRAS mutations lead to activation of NRF2 antioxidant signaling to increase 53BP1 gene transcription. Furthermore, genetic silencing or pharmacological inhibition of KRAS, NRF2 or 53BP1 attenuates KRAS mutation-induced radioresistance, especially in G1 phase cells. These findings reveal an important role for a KRAS-induced NRF2-53BP1 axis in the DNA repair and survival of KRAS-mutant tumor cells after radiotherapy, and indicate that targeting NRF2, 53BP1 or NHEJ may represent novel strategies to selectively abrogate KRAS mutation-mediated radioresistance.

Clinical and Preclinical Outcomes of Combining Targeted Therapy With Radiotherapy

In the era of precision medicine, radiation medicine is currently focused on the precise delivery of highly conformal radiation treatments. However, the tremendous developments in targeted therapy are yet to fulfill their full promise and arguably have the potential to dramatically enhance the radiation therapeutic ratio. The increased ability to molecularly profile tumors both at diagnosis and at relapse and the co-incident progress in the field of radiogenomics could potentially pave the way for a more personalized approach to radiation treatment in contrast to the current ‘‘one size fits all’’ paradigm. Few clinical trials to date have shown an improved clinical outcome when combining targeted agents with radiation therapy, however, most have failed to show benefit, which is arguably due to limited preclinical data. Several key molecular pathways could theoretically enhance therapeutic effect of radiation when rationally targeted either by directly enhancing tumor cell kill or indirectly through the abscopal effect of radiation when combined with novel immunotherapies. The timing of combining molecular targeted therapy with radiation is also important to determine and could greatly affect the outcome depending on which pathway is being inhibited.

Clinically validated model predicts the effect of intratumoral heterogeneity on overall survival for non-small cell lung cancer (NSCLC) patients

BACKGROUND AND OBJECTIVE

Radiation therapy is used in nearly 50% of cancer treatments in the developed world. Currently, radiation treatments are homogenous and fail to take into consideration intratumoral heterogeneity. We demonstrate the importance of considering intratumoral heterogeneity and the development of resistance during fractionated radiotherapy when the same dose of radiation is delivered for all fractions (Fractional Equivalent Dosing FED).

METHODS

A mathematical model was developed with the following parameters: a starting population of 10¹¹ non-small cell lung cancer (NSCLC) tumor cells, 48 h doubling time, and cell death per the linear-quadratic (LQ) model with α and β values derived from RSIα/β, in a previously described gene expression based model that estimates α and β. To incorporate both inter- and intratumor radiation sensitivity, RSIα/β output for each patient sample is assumed to represent an average value in a gamma distribution with the bounds set to -50% and +50% of RSIα/b. Therefore, we assume that within a given tumor there are subpopulations that have varying radiation sensitivity parameters that are distinct from other tumor samples with a different mean RSIα/β. A simulation cohort (SC) comprised of 100 lung cancer patients with available RSIα/β (patient specific α and β values) was used to investigate 60 Gy in 30 fractions with fractionally equivalent dosing (FED). A separate validation cohort (VC) of 57 lung cancer patients treated with radiation with available local control (LC), overall survival (OS), and tumor gene expression was used to clinically validate the model. Cox regression was used to test for significance to predict clinical outcomes as a continuous variable in multivariate analysis (MVA). Finally, the VC was used to compare FED schedules with various altered fractionation schema utilizing a Kruskal-Wallis test. This was examined using the end points of end of treatment log cell count (LCC) and by a parameter described as mean log kill efficiency (LKE) defined as: LCC  =  log10(tumorcellcount) [Formula: see text] RESULTS: Cox regression analysis on LCC for the VC demonstrates that, after incorporation of intratumoral heterogeneity, LCC has a linear correlation with local control (p = 0.002) and overall survival (p = < 0.001). Other suggested treatment schedules labeled as High Intensity Treatment (HIT) with a total 60 Gy delivered over 6 weeks have a lower mean LCC and an increased LKE compared to standard of care 60 Gy delivered in FED in the VC.

CONCLUSION

We find that LCC is a clinically relevant metric that is correlated with local control and overall survival in NSCLC. We conclude that 60 Gy delivered over 6 weeks with altered HIT fractionation leads to an enhancement in tumor control compared to FED when intratumoral heterogeneity is considered.

Orchestrating and sharing large multimodal data for transparent and reproducible research

Reproducibility is essential to open science, as there is limited relevance for findings that can not be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, scrutinized, challenged, and built upon. However, the intrinsic complexity and continuous growth of biomedical data makes it increasingly difficult to process, analyze, and share with the community in a FAIR (findable, accessible, interoperable, and reusable) manner. To overcome these issues, we created a cloud-based platform called ORCESTRA ( orcestra.ca ), which provides a flexible framework for the reproducible processing of multimodal biomedical data. It enables processing of clinical, genomic and perturbation profiles of cancer samples through automated processing pipelines that are user-customizable. ORCESTRA creates integrated and fully documented data objects with persistent identifiers (DOI) and manages multiple dataset versions, which can be shared for future studies.

The Evolving Genomic Landscape of Esophageal Squamous Cell Carcinoma Under Chemoradiotherapy

Esophageal squamous cell carcinoma (ESCC) often recurs after chemoradiotherapy, and the prognosis of ESCC after chemoradiotherapy has not improved over the past few decades. The mutation process in chemoradiotherapy-resistant clones and the functional relevance of genetic alterations remain unclear. To address these problems, we performed whole-exome sequencing of 52 tumor samples from 33 patients with ESCC who received radiotherapy combined with 5-fluorouracil/platinum. In multiregion analyses of pretreatment and locally recurrent lesions from five cases, most driver gene-altered clones remained under chemoradiotherapy selection pressure, while few driver gene alterations were acquired at recurrence. The mutation signatures of recurrent ESCC, including increased deletion frequency and platinum dose-dependent base substitution signatures, were substantially different from those of primary ESCC and reflected the iatrogenic impacts of chemoradiotherapy. Single-region analysis of 28 pretreatment tumors indicated that focal copy-number gain at the MYC locus was significantly associated with poor progression-free survival and overall survival after chemoradiotherapy. MYC gain remained throughout the chemoradiotherapy course and potentially contributes to intrinsic resistance to chemoradiotherapy. Consistent with these findings, MYC copy number and mRNA and protein levels in ESCC cell lines correlated positively with resistance to radiotherapy, and MYC knockdown improved sensitivity to radiotherapy. Overall, these data characterize the clonal evolution process induced by chemoradiotherapy and clinically relevant associations for genetic alterations in ESCC. These findings increase our understanding of therapeutic resistance and support the rationale for precision chemoradiotherapy. SIGNIFICANCE: Whole-exome sequencing reveals the genetic evolution of ESCC during chemoradiotherapy, highlighting MYC gain in pretreatment tumors as a potential marker of therapy resistance.

Model Selection for the Preclinical Development of New Drug-Radiotherapy Combinations

Radiotherapy plays an essential role in the treatment of more than half of all patients with cancer. In recent decades, advances in devices that deliver radiation and the development of treatment planning software have helped radiotherapy attain precise tumour targeting with minimal toxicity to surrounding tissues. Simultaneously, as more targeted drug therapies are being brought into the market, there has been significant interest in improving cure rates for cancer by adding drugs to radiotherapy to widen the therapeutic window, the difference between normal tissue toxicity and treatment efficacy. The development of new combination therapies will require judicious adaptation of preclinical models that are routinely used for traditional drug discovery. Here we highlight the strengths and weaknesses of each of these preclinical models and discuss how they can be used optimally to identify new and clinically beneficial drug-radiotherapy combinations.

Comparison of the oncogenomic landscape of canine and feline hemangiosarcoma shows novel parallels with human angiosarcoma

Angiosarcoma (AS) is a highly aggressive tumor of blood and lymphatic vessels in humans that shares many similarities with spontaneously occurring hemangiosarcoma (HSA) in dogs and cats. To investigate the genetic suitability of HSA as a model for AS, we sequenced ∼1000 cancer genes in 41 cases of HSA and matched germline tissue: 15 canine visceral HSAs, 13 canine skin HSAs and 13 feline skin HSAs. Analysis of visceral HSAs from dogs presenting with concurrent splenic and cardiac neoplasms showed that the tumors were not independent primaries, consistent with the highly metastatic nature of HSA. Comparison of HSA to AS revealed that several driver genes were recurrently mutated in both species, such as TP53, PIK3CA, ATRX, GRIN2A and LRP1B. Similar to AS, a UV mutational signature was found in a subset of canine cutaneous HSAs and both species show differing mutational profiles between tissue sites. Our characterization of canine and feline HSA demonstrates many important parallels to AS and provides hope that future studies on these cancers will benefit of all three species.

A Mechanistic DNA Repair and Survival Model (Medras): Applications to Intrinsic Radiosensitivity, Relative Biological Effectiveness and Dose-Rate

Variations in the intrinsic radiosensitivity of different cells to ionizing radiation is now widely believed to be a significant driver in differences in response to radiotherapy. While the mechanisms of radiosensitivity have been extensively studied in the laboratory, there are a lack of models which integrate this knowledge into a predictive framework. This paper presents an overview of the Medras model, which has been developed to provide a mechanistic framework in which different radiation responses can be modelled and individual responses predicted. This model simulates the repair of radiation-induced DNA damage, incorporating the overall kinetics of repair and its fidelity, to predict a range of biological endpoints including residual DNA damage, mutation, chromosome aberration, and cell death. Validation of this model against a range of exposure types is presented, including considerations of varying radiation qualities and dose-rates. This approach has the potential to inform new tools to deliver mechanistic predictions of radiation sensitivity, and support future developments in treatment personalization.

Attacking the PI3K/Akt/mTOR signaling pathway for targeted therapeutic treatment in human cancer

Cancer is the second leading cause of human death globally. PI3K/Akt/mTOR signaling is one of the most frequently dysregulated signaling pathways observed in cancer patients that plays crucial roles in promoting tumor initiation, progression and therapy responses. This is largely due to that PI3K/Akt/mTOR signaling is indispensable for many cellular biological processes, including cell growth, metastasis, survival, metabolism, and others. As such, small molecule inhibitors targeting major kinase components of the PI3K/Akt/mTOR signaling pathway have drawn extensive attention and been developed and evaluated in preclinical models and clinical trials. Targeting a single kinase component within this signaling usually causes growth arrest rather than apoptosis associated with toxicity-induced adverse effects in patients. Combination therapies including PI3K/Akt/mTOR inhibitors show improved patient response and clinical outcome, albeit developed resistance has been reported. In this review, we focus on revealing the mechanisms leading to the hyperactivation of PI3K/Akt/mTOR signaling in cancer and summarizing efforts for developing PI3K/Akt/mTOR inhibitors as either mono-therapy or combination therapy in different cancer settings. We hope that this review will facilitate further understanding of the regulatory mechanisms governing dysregulation of PI3K/Akt/mTOR oncogenic signaling in cancer and provide insights into possible future directions for targeted therapeutic regimen for cancer treatment, by developing new agents, drug delivery systems, or combination regimen to target the PI3K/Akt/mTOR signaling pathway. This information will also provide effective patient stratification strategy to improve the patient response and clinical outcome for cancer patients with deregulated PI3K/Akt/mTOR signaling.

Outcomes of extra-cranial stereotactic body radiotherapy for metastatic breast cancer: Treatment indication matters

BACKGROUND AND PURPOSE

To summarize the clinical outcomes of stereotactic body radiotherapy (SBRT) for metastatic breast cancer (mBC) from a large institution.

MATERIALS AND METHODS

Patients with mBC who received extra-cranial SBRT to metastatic lesions from 2011 to 2017 were identified. Treatment indications were: oligometastases, oligoprogression, and local control of dominant tumor (CDT). Endpoints included overall survival (OS), progression-free survival (PFS), local control (LC) and cumulative incidence of starting/changing chemo or hormonal therapy (SCT). Univariate and multivariate analyses were used to identify predictive factors.

RESULTS

We analyzed 120 patients (193 treated metastatic lesions) with a median follow up of 15.25 months. 1-and 2-year LC rates were 89% and 86.6%, respectively. 1-and 2-year OS rates were 83.5% and 70%, respectively, with treatment indication and molecular subtype being the predictive factors on MVA. 1-year OS was 91.0%, 78.5% and 63.9% for oligometastases, oligoprogression and CDT, respectively (p = 0.003). The worst OS was seen in basal subtype with 1-and 2-year OS rates of 59.2% and 39.5% (p = 0.01). Treatment indication was found to be predictive for PFS and lower rates of SCT on MVA. 1-and 2-year PFS rates were 45% and 32%, respectively. The 1-year PFS for oligometastases, oligoprogression, and CDT was 66%, 19.6%, and 14.3%, respectively (p < 0.001). The cumulative incidence of SCT at 1-year was 12% for oligometastases, 39.7% for oligoprogression and 53.3% for CDT (p < 0.001).

CONCLUSION

Patients treated for oligometastases have better OS and PFS than those treated for oligoprogression or CDT. SBRT may delay SCT in mBC patients, particularly those with oligometastases. SBRT provided an excellent LC in mBC patients.

Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance

Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challenge. Personalized prediction of tumor radiosensitivity is not currently implemented clinically due to insufficient accuracy of existing machine learning classifiers. Despite the acknowledged role of tumor metabolism in radiation response, metabolomics data is rarely collected in large multi-omics initiatives such as The Cancer Genome Atlas (TCGA) and consequently omitted from algorithm development. In this study, we circumvent the paucity of personalized metabolomics information by characterizing 915 TCGA patient tumors with genome-scale metabolic Flux Balance Analysis models generated from transcriptomic and genomic datasets. Metabolic biomarkers differentiating radiation-sensitive and -resistant tumors are predicted and experimentally validated, enabling integration of metabolic features with other multi-omics datasets into ensemble-based machine learning classifiers for radiation response. These multi-omics classifiers show improved classification accuracy, identify clinical patient subgroups, and demonstrate the utility of personalized blood-based metabolic biomarkers for radiation sensitivity. The integration of machine learning with genome-scale metabolic modeling represents a significant methodological advancement for identifying prognostic metabolite biomarkers and predicting radiosensitivity for individual patients.

Cell lines of the same anatomic site and histologic type show large variability in intrinsic radiosensitivity and relative biological effectiveness to protons and carbon ions

PURPOSE

To show that intrinsic radiosensitivity varies greatly for protons and carbon (C) ions in addition to photons, and that DNA repair capacity remains important in governing this variability.

METHODS

We measured or obtained from the literature clonogenic survival data for a number of human cancer cell lines exposed to photons, protons (9.9 keV/μm), and C-ions (13.3-77.1 keV/μm). We characterized their intrinsic radiosensitivity by the dose for 10% or 50% survival (D_10% or D_50% ), and quantified the variability at each radiation quality by the coefficient of variation (COV) in D_10% and D_50% . We also treated cells with DNA repair inhibitors prior to irradiation to assess how DNA repair capacity affects their variability.

RESULTS

We found no statistically significant differences in the COVs of D_10% or D_50% between any of the radiation qualities investigated. The same was true regardless of whether the cells were treated with DNA repair inhibitors, or whether they were stratified into histologic subsets. Even within histologic subsets, we found remarkable differences in radiosensitivity for high LET C-ions that were often greater than the variations in RBE, with brain cancer cells varying in D_10% (D_50% ) up to 100% (131%) for 77.1 keV/μm C-ions, and non-small cell lung cancer and pancreatic cancer cell lines varying up to 55% (76%) and 51% (78%), respectively, for 60.5 keV/μm C-ions. The cell lines with modulated DNA repair capacity had greater variability in intrinsic radiosensitivity across all radiation qualities.

CONCLUSIONS

Even for cell lines of the same histologic type, there are remarkable variations in intrinsic radiosensitivity, and these variations do not differ significantly between photon, proton or C-ion radiation. The importance of DNA repair capacity in governing the variability in intrinsic radiosensitivity is not significantly diminished for higher LET radiation.

Developing Tumor Radiosensitivity Signatures Using LncRNAs

Long non-coding RNAs (lncRNAs) are involved in diverse biological processes, including DNA damage repair, and are of interest as potential biomarkers of radiosensitivity. We investigated whether lncRNA radiosensitivity signatures could be derived for use in cancer patients treated with radiotherapy. Signature development involved radiosensitivity measurements for cell lines and primary tumor samples, and patient outcome after radiotherapy. A 10-lncRNA signature trained on radiosensitivity measurements in bladder cell lines showed a trend towards independent validation. In multivariable analyses, patients with tumors classified as radioresistant by the lncRNA signature had poorer local relapse-free survival (P = 0.065) in 151 patients with muscle-invasive bladder cancer who underwent radiotherapy. An mRNA-based radiosensitivity index signature performed similarly to the lncRNA bladder signature for local relapse-free survival (P = 0.055). Pathway analysis showed the lncRNA signature associated with molecular processes involved in radiation responses. Knockdown of one of the lncRNAs in the signature showed a modest increase in radiosensitivity in one cell line. An alternative approach involved training on primary cervical tumor radiosensitivity or local control after radiotherapy. Both approaches failed to generate a cervix lncRNA radiosensitivity signature, which was attributed to the age of samples in our cohorts. Our work highlights challenges in validating lncRNA signatures as biomarkers in archival tissue from radiotherapy cohorts, but supports continued investigation of lncRNAs for a role in radiosensitivity.