Radiosensitivity Index Research Articles

Abstract P5-06-16: Radiosensitivity and immune cell infiltration signature predict clinical outcome of patients in the molecular taxonomy of breast cancer international consortium (METABRIC) study cohort

Abstract Purpose/Objectives There are growing evidences that tumor radiosensitivity is associated with immune activation in solid tumors. However, previous studies have not examined the relationship between patterns of immune infiltration and radiation response according to diverse molecular subtypes of breast cancer. This study evaluated radiosensitivity and immune infiltration signature to define a group of patients would benefit most from radiation therapy. Materials/Methods We performed integrative analyses of the clinical, genomic, transciptomc, and immunogenomic data to characterize the molecular features associated with radiosensitivity. We analyzed 1,903 data sets of METABRIC Study cohort using the radiosensitivity index (RSI), CIBERSORT and xCell, gene expression deconvolution algorithm which estimates the immune composition of tumor samples. According to RSI cut-point (0.3745), the patients were grouped into radiosensitive (RS, RSI-low tumors, n=1,082) versus radioresistant (RR, RSI-high tumors, n=821). Next, patients were divided into two groups accoring to immune and stromal scores, immune infiltrated (IF, n= 650) and immune excluded (IE, n=1253) subgroups. and performed integrative analyses of the clinical, genomic, transciptomc, and immunogenomic data to characterize the molecular features associated with radiosensitivity. Results RS group showed improved prognosis compared to RR group, and IF group had better survival than IE group, however, these tendency was only significant in ER negative group. Radiosensitivity was significantly associated with activation of antitumor immunity. In contrast, radio-resistance was associated with metastatic properties, such as epithelial mesenchymal transition and angiogenesis. Differentially expressed gene analysis revealed that ER signaling pathway is correlated with suppression of antitumor immunity. Higher ER was associated with higher fraction of M2 macrophage and lower PD-1 expression. Integration of immune signature and radiosensitivity index further stratified patients into four subgroups. In ER-negative disease, IF and RS group were associated with the best prognosis, whereas in ER-positive disease, immune signature and radiation response have no prognostic significance. On multivariable cox regression, both integrated immune infiltration and radiosensitivity signature was independent predictors of relapse free survival (HR 1.12, 95% CI 1.06-1.19, p < 0.001) and overall survival (HR 1.06, 95% CI 1.01-1.11, p = 0.028). Conclusion Taken together, this results suggested that tumor radiosensitivity was associated with activation of antitumor immunity and led to better relapse free survival particularly in ER negative group. Citation Format: Byung-Hee Kang. Radiosensitivity and immune cell infiltration signature predict clinical outcome of patients in the molecular taxonomy of breast cancer international consortium (METABRIC) study cohort [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-06-16.

Relationship between Macrophage and Radiosensitivity in Human Primary and Recurrent Glioblastoma: In Silico Analysis with Publicly Available Datasets.

The glioblastoma microenvironment predominantly contains tumor-associated macrophages that support tumor growth and invasion. We investigated the relationship between tumor radiosensitivity and infiltrating M1/M2 macrophage profiles in public datasets of primary and recurrent glioblastoma. We estimated the radiosensitivity index (RSI) score based on gene expression rankings. Macrophages were profiled using the deconvolution algorithm CIBERSORTx. Samples from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), the Ivy Glioblastoma Atlas Project dataset, a single-cell RNA sequencing dataset (GSE84465), Glioma Longitudinal Analysis Consortium (GLASS), and an immunotherapy trial dataset (GSE121810) were included. RSI-high radioresistant tumors were associated with worse overall survival in TCGA and CGGA than RSI-low tumors. M1/M2 macrophage ratios and RSI scores were inversely associated, indicating that radioresistant glioblastoma tumor microenvironments contain more M2 than M1 macrophages. In the single-cell RNA sequencing dataset, the mean RSI of neoplastic cells was positively correlated with high M2 macrophages proportions. A favorable response to programmed cell death protein 1 (PD-1) therapy was observed in recurrent glioblastomas with high M1/M2 macrophage ratios and low RSI scores. In patients with recurrent glioblastoma, fewer M2 macrophages and low RSI scores were associated with improved overall survival. High M2 macrophage proportions may be involved in radioresistant glioblastoma.

TAMI-32. CORRELATION BETWEEN RADIOSENSITIVITY INDEX AND M2 MACROPHAGE PROPORTION IN TUMOR MICROENVIRONMENT OF GLIOBLASTOMA

Abstract BACKGROUND Tumor-associated macrophages (TAMs) Macrophage are predominant in glioblastoma tumor microenvironment (TME), supporting for neoplastic cell expansion and invasion. We investigated the relationship between radiosensitivity of glioblastoma and M1/M2 macrophage profiles in bulk and single cell RNA sequencing datasets. METHODS We used radiosensitivity index (RSI) gene signature and estimated RSI score based on the ranking of genes by expression level. Two large glioma datasets – The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) – were employed to identify whether RSI is clinically predictive of overall survival following radiation therapy. To analyze the association between M1/M2 macrophages and RSI within spatial context, the Ivy Glioblastoma Atlas Project dataset was investigated and single cell RNA sequencing dataset (GSE84465) was analyzed as well. Macrophages were profiled using a deconvolution algorithm, CIBERSORTx. RESULTS The RSI-high group having radioresistant tumors showed worse overall survival than the RSI-low group in both the TCGA (HR=1.87, 95% CI=1.06-3.29, P=0.031) and the CGGA (HR=1.61, 95% CI=1.04-2.50, P=0.031) glioblastoma population. In the Ivy Glioblastoma Atlas Project dataset, radiosensitive tumor having lower RSI was significantly more found in more vascular region including hyperplastic and microvascular region (coefficient=-0.07, P=0.001), meanwhile, radioresistant tumor was significantly clustered in necrotic region including perinecrotic and pseudopalisading regions (coefficient=0.07, P< 0.001). The proportion of M1/M2 macrophage and RSI score showed an inverse relationship (coefficient=-0.23, P=0.015), indicating that radioresistant glioblastomas are related with TME having more M2 than M1 macrophage. In single cell RNA sequencing dataset composed of immune and tumor cells collected from four patients, mean RSI of neoplastic cells was positively correlated with high proportion of M2 macrophages. CONCLUSION RSI can predict radiation response in terms of overall survival in glioblastoma patients. High proportion of M2 macrophage may play an important role in TME of radioresistant glioblastoma.

Radiosensitivity, Immune Activation, and Mutational Frequency of Melanoma Metastases Across Tissue Types

<h3>Purpose/Objective(s)</h3> Melanoma is a more radioresistant and immunogenic histology, associated with a higher mutational burden. However, the influence of metastasis tissue location is unknown. We hypothesize exploiting these differences may allow therapy personalization. <h3>Materials/Methods</h3> We identified metastatic melanoma samples across 6 tissues (brain, liver, lung, lymph node [LN], skin, soft tissue [ST]), which were profiled for gene expression by microarray chips. Intrinsic radiosensitivity was estimated by the radiosensitivity index (RSI), a rank-based gene expression signature, where a higher RSI (scale 0-1) indicates greater radioresistance, with a cut point of 0.375 in other histologies. Degree of inflammation in the microenvironment was calculated by an existing 12-gene chemokine signature (12CK) where a higher 12CK score indicates greater inflammation. A subset (n = 94) underwent targeted exome sequencing (1,327 cancer-associated genes) and somatic mutations (MF) were enriched after filtering known germline/silent mutations and artifacts. Differences by tissue were analyzed with the Kruskal-Wallis H test. Correlations between RSI, 12CK, and MF were tested using Spearman's rho. <h3>Results</h3> From 1995 to 2011, 337 metastatic samples were identified from unique patients. Median age at diagnosis was 61 (range 20-97). With a median follow-up of 162 months (95% CI 142.6-181.4), median survival was 59.8 months (95% CI 49.2-70.4). Median values for RSI, 12CK, and MB were 0.451 (interquartile range [IQR] 0.331-0.552), 8.700 (IQR 7.218-9.746), and 101.5 (IQR 73.75-137), respectively. Significant differences existed among tissues for both RSI (<i>P</i> = 0.003) and 12CK (<i>P</i> < 0.001), but not MF (<i>P</i> = 0.498) (Table 1). No pair-wise comparisons were significant after Bonferroni correction for RSI, but for 12CK, Brain-ST (<i>P</i> = 0.044), Brain-Lung (<i>P</i> = 0.013), Brain-LN (<i>P</i> = 0.000), and Liver-LN (<i>P</i> = 0.023) were significant. Correlation between RSI and 12CK was significant (rho = -0.661, <i>P</i> < 0.001), but correlations between MB and RSI/12CK were not significant. <h3>Conclusion</h3> In this novel composite genomic analysis of melanoma metastases, all were relatively radioresistant, but higher RSI values for liver and skin metastases may warrant radiotherapy dose escalation. Similarly, the lower inflammatory scores of liver and brain metastases may have implications for selection of patients for immunotherapy. More inflamed tumors may be more responsive to radiation. In contrast to current homogenous approaches to metastases, these results indicate personalized approaches to types/sequencing of therapy for melanoma metastases by tissue type may be warranted.

Analysis of Soft Tissue Metastases Across Primary Histologies Comparing Radiosensitivity, Immune Infiltration, and Mutational Frequency

The soft tissues are a poorly studied subsite for metastases with unclear treatment paradigms. We hypothesize elucidating differences in these metastases by primary histology may allow for optimization of therapies.We isolated soft tissue metastases with microarray data. A subset also had data from a 1,327-gene targeted exome sequencing assay. An existing radiosensitivity index (RSI) was used to estimate intrinsic radiosensitivity, where higher values denote radioresistance (0-1), with a cutpoint of 0.375. An existing 12-gene chemokine signature (12CK) was used to measure the degree of microenvironment inflammation, where higher scores denote greater inflammation. Samples with exome data were enriched for somatic mutations by filtering out artifacts and known germline/silent mutations (MF). Differences by histology were evaluated by the Kruskal-Wallis H test. Correlations between RSI, 12CK, and MB were evaluated by Spearman's rho.Between 1986 and 2010, we found 202 soft tissue metastases from unique patients across 11 primary histologies (breast [B], colorectal [CR], endometrial [E], head and neck [HN], melanoma [M], non-small cell lung [NSC], ovarian [O], renal [R], sarcoma [S], thyroid [T], and urothelial [U]). With a median follow-up of 173.2 months (95% CI 156.7-189.8), median survival was 62.4 months (95% CI 47-77.9). 41 samples across 4 histologies had targeted exome data. Median values for RSI, 12CK, and MB were 0.415 (interquartile range [IQR] 0.306-0.515), 8.20 (IQR 7.16-9.24), and 89.5 (IQR 69.5-122.75), respectively. Significant differences existed among histologies in all metrics (Table 1). After Bonferroni correction, pairwise comparisons were significant for HN-M (P = 0.008) in RSI; T-HN (P = 0.013), U-HN (P = 0.023), O-HN (P = 0.000), B-HN (P = 0.023), CR-HN (P = 0.006) in 12CK; and T-M (P = 0.024) in MB. Correlation between RSI and 12CK was significant (rho = -0.403, P < 0.001), but correlations between MF and RSI/12CK were not.In this novel exploratory analysis of soft tissue metastases, a number of histologies demonstrated sufficient radiosensitivity (RSI < 0.375) to consider radiotherapy as a component of management. Significant differences across primary histologies also suggest an opportunity for dose personalization. Significant differences in microenvironment inflammation and mutational frequency across primary histologies also may inform personalization of immunotherapy and other targeted therapies.

Immune Cell Infiltrates of the Tumor Microenvironment and Radiosensitivity of Recurrent Glioblastomas and Their Association With Outcome

GBM is a heterogenous tumor with diverse co-existing cell types. However, very little is known of the recurrent GBM (rGBM) microenvironment, and how immune cell infiltrates (ICI) may predict outcome. CIBERSORT provides an estimate of ICI via a gene expression deconvolution algorithm. We have previously validated the radiosensitivity index (RSI) as a measure of overall survival (OS) in primary GBM treated with radiotherapy (RT). In this novel study, we analyzed the presence of ICI, RSI, neutrophil-to-lymphocyte (NLR) and platelet-to-lymphocyte (PLR) ratios with respect to outcomes in previously treated rGBMs.From IRB-approved institutional tissue biorepository, we identified patients treated between 2004 - 2012, with rGBM who underwent re-excision and had complete gene expression profiling. Patients with prior low-grade glioma (secondary GBM) were excluded. Gene expression levels were assessed by Affymetrix Hu-RSTA assays. RSI was calculated using the previously published rank-based algorithm. For ICI, the presence and high expression (75%) were used to assess relationships with OS and progression free survival (PFS). For NLR, 2.4 was used based on published data in primary GBM. The 75% of PLR was assessed. Time-to-event analyses were performed with Kaplan-Meier estimates and compared via log-rank test. Associations of factors and outcomes were explored using Cox-regression.A total of 42 rGBM patients were identified, of which 40 (95%) were treated previously by adjuvant RT. Median follow-up from initial GBM diagnosis was 25 (range, 6-119) months and 8 (1-63) months from rGBM re-excision. All patients underwent surgery, 4 (9.5%) received re-irradiation, and 22 (50%) received further treatment under clinical trial. Median PFS was 2.5 (1-18) months after re-excision. Current smoking status (P = 0.04), KPS < 70 (P = 0.01) and age > 50 years (P = 0.01) were poor prognostic factors for OS. Treatment under clinical trial did not affect OS (P = 0.2) or PFS (P = 0.6). Four patients were treated with RT following re-excision. As expected, since RSI is predictive of outcome in RT treated patients, RSI was not predictive of PFS (P = 0.9) or OS (P = 0.6) in the cohort. Among ICI, lack of monocytes (P = 0.05) and presence of resting NK-cells (P = 0.01) adversely affected OS. In addition, high expression (³75%) of neutrophils (P = 0.01) and helper T-cells (P = 0.01) adversely affected OS. No other ICI subtypes were predictive of OS or PFS. Patients with pre-surgery NLR > 2.4 (P = 0.03) and high PLR > 240 (P = 0.04) had significantly worse OS. On multivariate analysis, helper T-cells (HR 0.99; 95% CI 0.98-0.99; P = 0.03), neutrophils (HR 0.43; 95% CI 0.21-0.91; P = 0.02), NLR (HR 0.33; 95% CI 0.11-0.96; P = 0.04) and PLR (HR 0.46; 95% CI 0.21-1.0; P = 0.05) remained significant for OS.Immune activation in previously treated rGBM may have a role in tumor biology affecting survival. The knowledge of ICI and NLR/PLR may serve as a unique risk-stratification and guide clinical decisions.

Radiosensitivity and Immune Cell Infiltration Signature Predict Clinical Outcome of Patients in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) Study Cohort

There is growing evidence that tumor radiosensitivity is associated with immune activation in solid tumors. However, previous studies have not examined the relationship between patterns of immune infiltration and radiation response according to diverse molecular subtypes of breast cancer. This study evaluated radiosensitivity and immune infiltration signature to define a group of patients would benefit most from radiation therapy.We performed integrative analyses of the clinical, genomic, transcriptomic, and immunogenomic data to characterize the molecular features associated with radiosensitivity. We analyzed 1,903 data sets of METABRIC Study cohort using the radiosensitivity index (RSI), CIBERSORT and xCell, gene expression deconvolution algorithm which estimates the immune composition of tumor samples. According to RSI cut-point (0.3745), the patients were grouped into radiosensitive (RS, RSI-low tumors, n = 1,082) versus radioresistant (RR, RSI-high tumors, n = 821). Next, patients were divided into two groups according to immune and stromal scores, immune infiltrated (IF, n = 650) and immune excluded (IE, n = 1253) subgroups.RR group showed poorer relapse free survival compared to RS group in multivariate (HR 1.52, 95% CI 1.23-1.89, P < 0.001) analyses and this tendency was only significant in ER negative group. In multivariate logistic regression analysis, CD8+ T cells (OR = 1.21 95% CI 1.1-1.33 P < 0.001), gamma/delta T cells (OR = 1.3 95% CI 1.19-1.43 P < 0.001), dendritic cell resting (OR = 1.54 95% CI 1.22-1.95 P < 0.001), memory B cells (OR = 1.17 95% CI 1.03-1.33 P = 0.013), Pam50 luminal B1 subtype (OR = 1.59 95% CI 1.25-2.02 P < 0.001), and triple negative InClust 10 (OR = 1.67 95% CI 1.17-2.4 P = 0.005) were significantly enriched in RS group. In contrast, M0 macrophages (OR = 0.86 95% CI 0.78-0.94 P = 0.001), HER2 enriched integrative cluster subtype (InClust) 5 (OR = 0.43 95% CI 0.31-0.61 P < 0.001), ER positive InClust 4+ (OR = 0.5 95% CI 0.37-0.68 P < 0.001), and PIK3CA pathway alteration (OR = 0.75 95% CI 0.62-0.92 P = 0.005) were significantly associated with RR group.Taken together, these results suggested that tumor radiosensitivity was associated with activation of antitumor immunity and led to better relapse free survival particularly in ER negative group.

Tumor-immune ecosystem dynamics define an individual Radiation Immune Score to predict pan-cancer radiocurability.

Radiotherapy efficacy is the result of radiation-mediated cytotoxicity coupled with stimulation of antitumor immune responses. We develop an in silico 3-dimensional agent-based model of diverse tumor-immune ecosystems (TIES) represented as anti- or pro-tumor immune phenotypes. We validate the model in 10,469 patients across 31 tumor types by demonstrating that clinically detected tumors have pro-tumor TIES. We then quantify the likelihood radiation induces antitumor TIES shifts toward immune-mediated tumor elimination by developing the individual Radiation Immune Score (iRIS). We show iRIS distribution across 31 tumor types is consistent with the clinical effectiveness of radiotherapy, and in combination with a molecular radiosensitivity index (RSI) combines to predict pan-cancer radiocurability. We show that iRIS correlates with local control and survival in a separate cohort of 59 lung cancer patients treated with radiation. In combination, iRIS and RSI predict radiation-induced TIES shifts in individual patients and identify candidates for radiation de-escalation and treatment escalation. This is the first clinically and biologically validated computational model to simulate and predict pan-cancer response and outcomes via the perturbation of the TIES by radiotherapy.

Genomic-adjusted radiation dose to personalise radiotherapy.

In The Lancet Oncology, Jacob Scott and colleagues 1 Scott JG Sedor G Ellswroth P et al. Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis. Lancet Oncol. 2021; (published Aug 4.)https://doi.org/10.1016/S1470-2045(21)00347-8 Summary Full Text Full Text PDF Scopus (17) Google Scholar describe an algorithm using the genomic-adjusted radiation dose (GARD) to personalise radiotherapy dose prescription on the basis of the biological effect of the dose rather than on physical dose alone. GARD is a preclinically and clinically validated combination of a gene expression assay, which assumes pan-tissue biological networks of radiosensitivity and radioresistance, with a linear quadratic model for estimation of total radiation dose in tissues. In previous work, the investigators identified a tumour molecular signature based on the expression of ten genes (AR, cJun [JUN], STAT1, PKC-β [PRKCB], RelA [RELA], cABL [ABL], SUMO1, PAK2, HDAC1, and IRF1) that correlated with radiosensitivity (expressed as tumour cell survival fraction per 2 Gy fraction) in a number of cancer cell lines, called the radiosensitivity index (RSI). 2 Eschrich S Zhang H Zhao H et al. Systems biology modeling of the radiation sensitivity network: a biomarker discovery platform. Int J Radiat Oncol Biol Phys. 2009; 75: 497-505 Summary Full Text Full Text PDF PubMed Scopus (157) Google Scholar , 3 Eschrich SA Pramana J Zhang H et al. A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation. Int J Radiat Oncol Biol Phys. 2009; 75: 489-496 Summary Full Text Full Text PDF PubMed Scopus (191) Google Scholar , 4 Scott JG Berglund A Schell MJ et al. A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study. Lancet Oncol. 2017; 18: 202-211 Summary Full Text Full Text PDF PubMed Scopus (219) Google Scholar Later, RSI was validated on various tumour types that led to the GARD algorithm. 4 Scott JG Berglund A Schell MJ et al. A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study. Lancet Oncol. 2017; 18: 202-211 Summary Full Text Full Text PDF PubMed Scopus (219) Google Scholar In the current publication, 1 Scott JG Sedor G Ellswroth P et al. Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis. Lancet Oncol. 2021; (published Aug 4.)https://doi.org/10.1016/S1470-2045(21)00347-8 Summary Full Text Full Text PDF Scopus (17) Google Scholar Scott and colleagues validated GARD in 1615 patients with seven cancer types from 11 study cohorts. They found that GARD was associated with time to first recurrence and overall survival for patients receiving radiotherapy and that, by contrast with physical dose, it predicted radiotherapy benefit. Consequently, GARD is a model that can potentially serve as a tool to individualise prescribed radiation doses in clinical practice. The efforts of Scott and colleagues need to be applauded worldwide, because radiotherapy is considerably lagging compared with the enormous progress done in the field of personalised medicine that currently mainly applies to decisions on the use of systemic therapy or targeted agents. Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysisThe biological effect of radiotherapy, as quantified by GARD, is significantly associated with time to first recurrence and overall survival for patients with cancer treated with radiation. It is predictive of radiotherapy benefit, and physical dose of radiation is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalising radiotherapy prescription dose. Full-Text PDF

Multiomics Differences in Lung Squamous Cell Carcinoma Patients with High Radiosensitivity Index Compared with Those with Low Radiosensitivity Index

Objectives Radiosensitivity Index (RSI) can predict intrinsic radiotherapy sensitivity. We analyzed multiomics characteristics in lung squamous cell carcinoma between high and low RSI groups, which may help understand the underlying molecular mechanism of radiosensitivity and guide optional treatment for patients in the future. Methods The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) data were used to download clinical data, mRNA, microRNA, and lncRNA expression. Differential analyses, including mRNA, miRNA, lncRNA, and G.O. and KEGG, and GSVA analyses, were performed with R. Gene set enrichment analysis was done by GSEA. miRNA-differentially expressed gene network and ceRNA network were analyzed and graphed by the Cytoscape software. Results In TCGA data, 542 patients were obtained, including 171 in the low RSI group (LRSI) and 371 in the high RSI group (HRSI). In RNAseq, 558 significantly differentially expressed genes (DEGs) were obtained. KRT6A was the most significantly upregulated gene and IDO1 was the most significantly downregulated gene. In miRNAseq, miR-1269a was the most significantly upregulated. In lncRNAseq, LINC01871 was the most upregulated. A 66-pair interaction between differentially expressed genes and miRNAs and an 11-pair interaction between differential lncRNAs and miRNAs consisted of a ceRNA network, of which miR-184 and miR-490-3p were located in the center. In the GEO data, there were 40 DEGs. A total of 17 genes were founded in both databases, such as ADAM23, AHNAK2, BST2, COL11A1, CXCL13, FBN2, IFI27, IFI44L, MAGEA6, and PTGR1. GSVA analysis revealed 31 significant pathways. GSEA found 87 gene sets enriched in HRSI and 91 gene sets in LRSI. G.O. and KEGG of RNA expression levels revealed that these genes were most enriched in T cell activation and cytokine−cytokine receptor interaction. Conclusions Patients with lung squamous cell carcinoma have different multiomics characteristics between two groups. These differences may have an essential significance with radiotherapy effect.

"Radio-Sensitivity Index" (RSI) is not a marker of radiosensitivity: it's worse than random chance!

"Radio-Sensitivity Index" (RSI) is not a marker of radiosensitivity: it's worse than random chance!

Integrating Intrinsic Radiosensitivity and Immune Status for Predicting Benefits of Radiotherapy in Head and Neck Squamous Cell Carcinoma.

BackgroundHNSCC (head and neck squamous cell carcinoma) is a heterogeneous disease for which radiotherapy is a main treatment. As intrinsic radiosensitivity and immune status affect the initial and effective stage of the radiation-induced cancer immunity cycle, respectively, it is important to consider both of them when we select patients who can benefit from radiotherapy.Material/MethodsOur study included all HNSCC patients with complete survival and radiotherapy information in TCGA database. Patients were divided into RS (radiosensitive), RR (radioresistant), immune, and non-immune groups according to their RSI (radiosensitivity index) and immune score calculated by the ESTIMATE algorithm. Survival analysis was performed to compare OS (overall survival) between patients receiving and not receiving radiotherapy. GO and KEGG pathway enrichment analysis was performed for functional analysis. Univariate Cox and ridge regression analysis were performed to construct a predictive gene signature based on the combined stratification.ResultsOnly patients in the RS-immune group could benefit from radiotherapy, and the survival analysis results remained consistent after we performed propensity score matching between patients receiving and not receiving radiotherapy. The differentially expressed genes between the RS-immune and non-RS-immune groups were mainly enriched in pathways related to immune process. The 3-gene signature we built exhibited predictive value in training and validation cohorts when treated as a binary or continuous variable.ConclusionsThe combined stratification of intrinsic radiosensitivity and immune status was superior to considering intrinsic radiosensitivity or immune status alone and could be used in preclinical evaluation to select patients or to decide whether radiotherapy sensitizers and immunotherapy should be used at the same time.

Genomic identification of sarcoma radiosensitivity and the clinical implications for radiation dose personalization

BackgroundSoft-tissue sarcomas (STS) are heterogeneous with variable response to radiation therapy (RT). Utilizing the radiosensitivity index (RSI) we estimated the radiobiologic ratio of lethal to sublethal damage (α/β), genomic-adjusted radiation dose(GARD), and in-turn a biological effective radiation dose (BED). MethodsTwo independent cohorts of patients with soft-tissue sarcoma were identified. The first cohort included 217 genomically-profiled samples from our institutional prospective tissue collection protocol; RSI was calculated for these samples, which were then used to dichotomize the population as either highly radioresistant (HRR) or conventionally radioresistant (CRR). In addition, RSI was used to calculate α/β ratio and GARD, providing ideal dosing based on sarcoma genomic radiosensitivity. A second cohort comprising 399 non-metastatic-STS patients treated with neoadjuvant RT and surgery was used to validate our findings. ResultsBased on the RSI of the sample cohort, 84% would historically be considered radioresistant. We identified a HRR subset that had a significant difference in the RSI, and clinically a lower tumor response to radiation (2.4% vs. 19.4%), 5-year locoregional-control (76.5% vs. 90.8%), and lower estimated α/β (3.29 vs. 5.98), when compared to CRR sarcoma. Using GARD, the dose required to optimize outcome in the HRR subset is a BEDα/β=3.29 of 97 Gy. ConclusionsWe demonstrate that on a genomic scale, that although STS is radioresistant overall, they are heterogeneous in terms of radiosensitivity. We validated this clinically and estimated an α/β ratio and dosing that would optimize outcome, personalizing dose.

Radiosensitivity index emerges as a potential biomarker for combined radiotherapy and immunotherapy

In the era of immunotherapy, there lacks of a reliable genomic predictor to identify optimal patient populations in combined radiotherapy and immunotherapy (CRI). The purpose of this study is to investigate whether genomic scores defining radiosensitivity are associated with immune response. Genomic data from Merged Microarray-Acquired dataset (MMD) were established and the Cancer Genome Atlas (TCGA) were obtained. Based on rank-based regression model including 10 genes, radiosensitivity index (RSI) was calculated. A total of 12832 primary tumours across 11 major cancer types were analysed for the association with DNA repair, cellular stemness, macrophage polarisation, and immune subtypes. Additional 585 metastatic tissues were extracted from MET500. RSI was stratified into RSI-Low and RSI-High by a cutpoint of 0.46. Proteomic differential analysis was used to identify significant proteins according to RSI categories. Gene Set Variance Analysis (GSVA) was applied to measure the genomic pathway activity (18 genes for T-cell inflamed activity). Kaplan-Meier analysis was performed for survival analysis. RSI was significantly associated with homologous DNA repair, cancer stemness and immune-related molecular features. Lower RSI was associated with higher fraction of M1 macrophage. Differential proteomic analysis identified significantly higher TAP2 expression in RSI-Low colorectal tumours. In the TCGA cohort, dominant interferon-γ (IFN-γ) response was characterised by low RSI and predicted better response to programmed cell death 1 (PD-1) blockade. In conclusion, in addition to radiation response, our study identified RSI to be associated with various immune-related features and predicted response to PD-1 blockade, thus, highlighting its potential as a candidate biomarker for CRI.

Comparative analysis of some radiosensitivity index results of certain radiation workers in Chongqing from 2018 to 2019

Objective This paper analyzes the physical examination results of blood routine, chromosome deformity rate, micronucleus rate and thyroid function test of some radiation workers in Chongqing from 2018 to 2019, understands the occupational problems of radiation workers, and provide scientific basis for putting forward reasonable suggestions method: Methods 2 656 cases in 2018 and 2 922 cases in 2019 were selected through the information platform of physical examination system. A total of 5 578 physical examination results in two years were statistically analyzed and analyzed. Results The abnormal rate of blood routine, the detection rate and abnormal rate of chromosome distortion and micronucleus, and the abnormal rate of thyroid gland function (T3, T4, TSH) between the control group and the radiation group are significant differences ( P < 0.05). There were significant differences in the abnormal rate of blood routine, thyroid function (T3, T4, TSH), chromosome teratosis rate, micronucleus detection rate and abnormal rate between radiation diagnosis and treatment and industrial flaw detection, but there was no significant difference in the abnormal rate of chromosome ( P > 0.05). There was significant difference between < 10 year group and 10~20 year group, and there was significant difference in platelet, white blood cell and hemoglobin between 10~20 year group and 20 year group ( P < 0.05). There was no statistical significance in erythrocyte difference ( P > 0.05). There was significant difference in the abnormal rate of thyroid function among the three working age segments ( P < 0.05). The detection rate of chromosome distortion was significantly different between < 10 years group and 10~20 year group ( P < 0.05), but there was no significant difference between the other two groups ( P > 0.05). There was significant difference in the abnormal rate between the two groups ( P < 0.05). There was no significant difference in pairwise comparison of micronucleus detection rate among groups ( P > 0.05), but there was significant difference in abnormal rate among groups ( P < 0.05). Conclusion The long-term low dose ionizing radiation environment will damage the hematopoietic and endocrine system of radiation sensitive human body. 摘要： 目的 分析 2018—2019 年重庆市部分放射工作人员血常规、染色体畸变率、微核率、甲状腺功能试验体检结 果, 了解放射工作人员的职业健康问题, 为提出合理的建议提供科学依据。 方法 通过体检系统导出 2018 年 2 656 份, 2019 年 2 922 份, 共计 5 578 份体检结果进行统计与分析。 结果 对照组、放射组 4 项血常规异常率、染色体畸变 和微核检出率和异常率、甲状腺功能 (T3、T4、TSH) 异常率差异具有统计学意义 ( P < 0.05); 放射诊疗和工业探伤四项 血常规异常率、甲状腺功能 (T3、T4、TSH) 异常率、染色体畸变检出率、微核检出率和异常率差异具有统计学意义 ( P < 0.05), 染色体异常率无统计学意义 ( P > 0.05); <10 年组和 10~20 年组差异有统计学意义, 10~20 年组和 ≥20 年组血小板、白细胞、血红蛋白差异有统计学意义 ( P < 0.05), 红细胞差异无统计学意义 ( P > 0.05); 甲状腺功能 3 个工龄段异常率差异有统计学意义 ( P < 0.05), 染色体畸变检出率两两比较 <10 与另两组有统计学意义 ( P < 0.05), 10~20 与 ≥20 差异无统计学意义 ( P > 0.05), 异常率两两比较差异有统计学意义 ( P < 0.05); 微核检出率两两比较差 异无统计学意义 ( P > 0.05), 异常率差异有统计学意义 ( P < 0.05)。 结论 长期低剂量电离辐射环境会对射线敏感的人 体造血系统、内分泌系统造成一定损伤。

Abstract PS15-06: The distribution of radiosensitivity index differs by PAM50 subtype in primary breast tumors

Abstract Background: Prior studies identified radiosensitive and radioresistant breast tumor phenotypes and demonstrated that gene-expression signatures such as the radiosensitivity index (RSI) can be used to derive biologically rational radiation dose selection. In this study, we assessed the RSI of primary breast tumor samples and its association with PAM50 subtype.Materials/Methods: Primary breast tumor samples were identified from a multi-institutional tissue biorepository. Tumors were excluded if they were treated with neoadjuvant therapy or had distant metastatic disease at the time of sample collection. The RSI gene signature and PAM50 subtype were assessed through transcriptomic profiling performed on Affymetrix microarray chips. Distribution of RSI values across PAM50 subtypes was assessed with the Kruskal-Wallis test. Differences in proportions of radioresistant and radiosensitive tumors among PAM50 subtypes were assessed with the Chi-squared test, where radioresistant was defined as RSI&amp;gt;0.3745 based on prior studies. Clinicopathologic characteristics were obtained through clinical chart review. Results: A total of 637 primary breast tumors with available genomic profiling and clinical information were included for analysis. HIstologies were predominantly invasive ductal carcinoma (81.5%) and invasive lobular (11.6%). Most tumors were T1-T2 (91.7%) while 35.9% had pathologically positive lymph nodes. The distribution of RSI significantly differed by PAM50 classification (Kruskal-Wallis p &amp;lt; 0.001). Proportions of radioresistant vs radiosensitive tumors varied significantly according to PAM50 subtype and are included in the accompanying table (Chi-squared p &amp;lt; 0.001). Median follow-up was 89 months. Conclusion: Breast tumor PAM50 subtypes demonstrate significant variation in radiosensitivity. Further studies are needed to determine if genomic subtyping can refine the ability to predict clinical radiation response and further optimize individual therapy. PAM50TotalBasalHer2LumALumBNormalRSI PhenotypeRadioresistantn (%)50 (60.2%)32 (42.1%)146 (54.4%)82 (45.3%)24 (82.8%)334 (52.4%)Radiosensitive n (%)33 (39.8%)44 (57.9%)122 (45.6%)99 (54.7%)5 (17.2%)303 (47.5%)Total837626818129637 Citation Format: Matthew Fahey, Nicholas Russo, Casey Liveringhouse, Matthew Mills, Kamran Ahmed, Roberto Diaz. The distribution of radiosensitivity index differs by PAM50 subtype in primary breast tumors [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS15-06.

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.

Connection Between Tumor Radiosensitivity and Response to Immunotherapy in 11 Major Epithelial Cancer Types

Background: Radiotherapy has gained increasing attention as an effective cytotoxic agent to improve therapeutic response to immunotherapy. However, synergic effect is seldom seen clinically and reliable biomarkers for optimal patient selection remains to be identified. Radiosensitivity index (RSI) is a well-known measure of tumor’s response to radiotherapy, which is derived from genomic data and system biology. Its association with the immune landscape in cancer is unclear. Methods: Genomic data from Merged Microarray-Acquired dataset (MMD) were established and the Cancer Genome Atlas (TCGA) were obtained. Based on rank-based regression model including 10 genes, RSI was calculated. A total of 12,832 primary tumors across 11 major cancer types were analyzed. RSI was stratified into RSI-Low and RSI-High by a cutpoint of 0.46. Gene set variance analysis was applied to measure the genomic pathway activity (18 genes for T-cell inflamed activity). Kaplan-Meier analysis was performed for survival analysis. Findings: We found that RSI was significantly associated with homologous DNA repair, cancer stemness and various cancer-specific molecular features. Tumors with low RSI were associated with significantly higher portion of M1 macrophage, relative to M2 macrophage, and higher IFNG expression. Additionally, dominant interferon-γ (IFN-γ) response was characterized by low RSI and potentially predicted better response to programmed cell death 1 (PD-1) blockade. Interpretation: RSI is strongly associated with immune response and efficacy to PD-1 blockade. IFN-γ dominant status could be estimated by RSI, providing an alternative selection strategy to identify suitable patients for combined radiotherapy and immunotherapy. Funding Statement: This study was supported by study project of Tri-Service General Hospital (TSGH-D109063). Declaration of Interests: The authors declare that they have no competing interests.

OC-1031: The radiosensitivity index predicts benefit from HDR brachytherapy in high-risk prostate cancer

OC-1031: The radiosensitivity index predicts benefit from HDR brachytherapy in high-risk prostate cancer

Characterization of Intrinsic Radiosensitivity and Immune Cell Infiltrates in Bladder Cancer

Bladder cancer is managed by surgery, systemic therapy and radiation (RT) depending on clinicopathologic features and physician/patient choice. Various RT doses are used in bladder preservation, which are guided by normal tissue tolerance, not intrinsic biology. Emerging data supports the use of immunotherapy (IO) in bladder cancer, but optimal patient selection and therapy sequencing are not defined. This study characterizes the immune cell infiltrate (ICI) and intrinsic RT-sensitivity of bladder cancer in an institutional cohort and 4 public datasets with gene expression data to understand the relationship between RT-sensitivity and the ICI. With an IRB-approved prospective tissue collection protocol, 223 bladder cancer patients profiled with Affymetrix Hu-RSTA microarray chips (Affymetrix; Santa Clara, CA) were identified. Also, 4 public bladder cancer datasets from GEO with various clinicopathologic features were analyzed: GSE48075 (n = 142) and GSE32984 (n = 308) without neoadjuvant chemotherapy (NAC); GSE87304 (n = 305) with NAC; GSE120736 (primary/recurrent tumors; n = 145). In each dataset, tumors were grouped as non-invasive (NMIBC) or invasive (MIBC) by T category. Intrinsic tumor RT-sensitivity was inferred by the radiosensitivity index (RSI), a cancer-type agnostic gene expression algorithm. RSI values were split at the median and grouped as RSIlo (i.e. RT-sensitive) or RSIhi. Tumor ICI composition was inferred by 2 algorithms: CIBERSORT (22 distinct ICI types) and XCell (64 distinct immune and stromal cell types). Groups were compared with the Mann-Whitney U test. Multiple correction testing was performed. The institutional cohort median RSI is 0.42 (range 0.02-0.86). The median RSI values for the public datasets are: [GSE48075] 0.50 (range 0.22-0.69), [GSE32894] 0.23 (range -0.40-0.45), [GSE87304] 0.33 (range -0.07-0.48) and [GSE120736] 0.40 (range 0.06-0.72). No difference was seen in the median RSI between primary and recurrent bladder tumors (p = 0.38). Only one dataset had a difference in the median RSI between NMIBC and MIBC (GSE32894, p <0.001), with a higher RSI in MIBC. Next, using CIBERSORT and XCell, we found that resting or naïve ICIs (e.g. NK, CD8+ T, CD4+ T, B, CD4+ memory T cells) were higher in NMIBC in 3 out of 4 datasets (q <0.05). Several ICIs (e.g. activated NK, M1/M2 macrophages, CD4+ memory T cells) were higher in MIBC in all datasets (q <0.05). In 3 out of 4 datasets and the institutional cohort, RSIlo vs RSIhi tumors had higher CD4+ T, M1 macrophages, activated (NK, dendritic, CD4+ memory T cells) and CD8+ T cell types (q <0.05). Bladder tumors have a range of RT-sensitivities in this analysis, implying uniform RT dosing may lead to over and under treatment. Also, NMIBC has higher resting or naïve ICIs compared to MIBC and RT-sensitive tumors are enriched with specific effector ICIs. Integration of ICI and RT-sensitivity data may assist with optimizing patient selection for certain IO and RT combinations.