Combination of local radiotherapy and anti-glucocorticoid-induced tumor necrosis factor receptor (GITR) therapy augments PD-L1 blockade-mediated anti-tumor effects in murine breast cancer model.

PURPOSE: In this study, we investigated whether local radiotherapy (RT) and an anti-glucocorticoid-induced tumor necrosis factor receptor (GITR) agonist could increase the efficacy of PD-L1 blockade. METHODS AND MATERIALS: We analyzed a breast cancer dataset from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) to determine the role of GITR in breast cancer. We used the 4T1 murine TNBC model (primary and secondary tumors) to investigate the efficacy of PD-L1 blockade, local RT, anti-GITR agonist, and their combinations. We assessed tumor growth by tumor volume measurements, in vivo bioluminescence imaging, and metastatic lung nodule counts to evaluate the effects of these treatments. Flow cytometry and immunohistochemistry determined the proportions and phenotypes of CD8+ T-cells and regulatory T-cells (Tregs) in the tumors and spleen. Plasma cytokine levels were measured by enzyme-linked immunosorbent assay. RESULTS: In the METABRIC cohort, patients with high expression of TNFRSF18, which encodes GITR, had significantly better survival than those with low expression. Adding local RT or anti-GITR agonist to PD-L1 blockade did not significantly augment efficacy compared to PD-L1 blockade alone; however, adding both to PD-L1 blockade significantly reduced tumor growth and lung metastasis. The benefits of the triple combination were accompanied by increased CD8+ T-cells and decreased Tregs in the tumor microenvironment and spleen. CONCLUSIONS: The combination of local RT and an anti-GITR agonist significantly enhanced the anti-tumor immune responses induced by PD-L1 blockade. These results provide the preclinical rationale for the combination of therapy.

Dynamic Responses of Circulating T Cells After Stereotactic Body Radiation Therapy for Bone Metastasis in Patients With Breast Cancer.

PURPOSE: Preclinical studies have shown that radiation therapy modulates antitumor immune responses. However, circulating T-cell responses after radiation therapy in patients with cancer have been poorly characterized. This study aims to explore the changes in circulating T cells after stereotactic body radiation therapy (SBRT). METHODS AND MATERIALS: Peripheral blood samples of 30 patients with breast cancer who underwent SBRT for bone metastasis were analyzed using multicolor flow cytometry. Phenotypes of PD-1+ CD8+ T cells and regulatory T (TREG) cells were examined. Additionally, plasma protein levels were analyzed using a bead-based immunoassay. RESULTS: Circulating PD-1+ CD8+ T cells, which are enriched for tumor-specific clonotypes, were activated at 1 week after SBRT. However, circulating TREG cells were also activated after SBRT; this pattern was also evident among effector Foxp3hiCD45RA- TREG cells. We observed no difference in T-cell responses according to the fraction size and number. Notably, activation of TREG cells was more prominent in patients who experienced greater activation of PD-1+ CD8+ T cells. Plasma level changes in TGF-ß1, soluble CTLA-4, and soluble 4-1BB at 1 week after SBRT were associated with PD-1+ CD8+ T-cell responses. Activation of TREG cells at 1 week after SBRT was associated with worse progression-free survival. Clinical factors including molecular subtype were not associated with the T-cell responses. CONCLUSIONS: SBRT induced activation of both potentially tumor-specific CD8+ T cells and TREG cells, which were tightly associated with each other. These results may support the use of TREG cell-modulating strategies with SBRT to improve the antitumor immune response.

Modulation of CD8+ T Cell Responses by Radiotherapy-Current Evidence and Rationale for Combination with Immune Checkpoint Inhibitors.

Radiotherapy for cancer has been known to affect the responses of immune cells, especially those of CD8+ T cells that play a pivotal role in anti-tumor immunity. Clinical success of immune checkpoint inhibitors led to an increasing interest in the ability of radiation to modulate CD8+ T cell responses. Recent studies that carefully analyzed CD8+ T cell responses following radiotherapy suggest the beneficial roles of radiotherapy on anti-tumor immunity. In addition, numerous clinical trials to evaluate the efficacy of combining radiotherapy with immune checkpoint inhibitors are currently undergoing. In this review, we summarize the current status of knowledge regarding the changes in CD8+ T cells following radiotherapy from various preclinical and clinical studies. Furthermore, key biological mechanisms that underlie such modulation, including both direct and indirect effects, are described. Lastly, we discuss the current evidence and essential considerations for harnessing radiotherapy as a combination partner for immune checkpoint inhibitors.

BRD4 Inhibition Enhances the Antitumor Effects of Radiation Therapy in a Murine Breast Cancer Model.

Bromodomain-containing protein 4 (BRD4) is an intracellular protein that regulates expression of various cellular functions. This study investigated whether BRD4 inhibition can alter the immunomodulatory and antitumor effects of radiation therapy (RT). A murine breast cancer cell line was implanted into BALB/c mice. The dual-tumor model was used to evaluate the abscopal effects of RT. A total of 24 Gy was delivered and BRD4 inhibitor was injected intravenously. Tumor size was measured, and in vivo imaging was performed to evaluate tumor growth. Flow cytometry and immunohistochemistry were performed to examine immunologic changes upon treatment. The combination of BRD4 inhibitor and RT significantly suppressed tumor growth compared to RT alone. BRD4 inhibitor reduced the size of the unirradiated tumor, indicating that it may induce systemic immune responses. The expression of HIF-1α and PD-L1 in the tumor was significantly downregulated by the BRD4 inhibitor. The proportion of M1 tumor-associated macrophages (TAMs) increased, and the proportion of M2 TAMs decreased upon BRD4 inhibition. BRD4 inhibitor expanded CD4+ and CD8+ T cell populations in the tumor microenvironment. Additionally, splenic monocytic myeloid derived suppressor cells, which were increased by RT, were reduced upon the addition of BRD4 inhibitor. Therefore, the addition of BRD4 inhibitor significantly enhanced the systemic antitumor responses of local RT.

Identification of Genes Involved in EGF-induced Apoptosis Using CRISPR/Cas9 Knockout Screening: Implications for Novel Therapeutic Targets in EGFR-Overexpressing Cancers.

PURPOSE: Exogenous epidermal growth factor (EGF) causes apoptosis in EGF receptor (EGFR)-overexpressing cell lines. The apoptosis-inducing factors could be a therapeutic target. We aimed to determine the mechanism of EGF-induced apoptosis using a genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)-based knockout screen. Materials and Methods: Two-vector system of the human genome-scale CRISPR knockout library v2 was used to target 19,050 genes using 123,411 single guide RNAs (sgRNAs). Recombinant human EGF (100 nM) or distilled water four times was administered to the experimental and control groups, respectively. The read counts of each sgRNA obtained from next-generation sequencing were analyzed using the edgeR algorithm. We used another EGFR-overexpressing cell line (A549) and short hairpin RNAs (shRNAs) targeting five EGF-resistance genes for validation. DUSP1 expression in A431, A549, and HEK293FT cells was calculated using reverse transcription-quantitative polymerase chain reaction. RESULTS: We found 77 enriched and 189 depleted genes in the experimental group using the CRISPR-based knockout screen and identified the top five EGF-resistance genes: DDX20, LHFP, REPS1, DUSP1,<.i> and KRTAP10-12. Transfecting shRNAs targeting these genes into A549 cells significantly increased the surviving fractions after EGF treatment, compared with those observed in the control shRNA-transfected cells. The expression ratio of DUSP1 (inhibits ERK signaling) increased in A431 and A549 cells after EGF treatment. However, DUSP1 expression remained unchanged in HEK293FT cells after EGF treatment. CONCLUSION: The CRISPR-based knockout screen revealed 266 genes possibly responsible for EGF-induced apoptosis. DUSP1 might be a critical component of EGF-induced apoptosis and a novel target for EGFR-overexpressing cancers.

CEACAM1 Marks Highly Suppressive Intratumoral Regulatory T Cells for Targeted Depletion Therapy.

PURPOSE: Regulatory T cells (Tregs) exert immunosuppressive functions and hamper antitumor immune responses in the tumor microenvironment. Understanding the heterogeneity of intratumoral Tregs, and how it changes with tumor progression, will provide clues regarding novel target molecules of Treg-directed therapies. EXPERIMENTAL DESIGN: From 42 patients with renal cell carcinoma and 5 patients with ovarian cancer, immune cells from tumor and peripheral blood were isolated. We performed multicolor flow cytometry and RNA-sequencing to characterize the phenotypes and heterogeneity of intratumoral Tregs. In vitro functional assays were performed to evaluate suppressive capacity of Tregs and effect of carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1)-mediated depletion. The CT26 tumor model was used to evaluate the association between intratumoral Tregs and tumor growth, and examine the in vivo role of CEACAM1+ intratumoral Tregs on antitumor immunity. RESULTS: We found that CEACAM1 was selectively expressed on intratumoral Tregs, whereas its expression on peripheral Tregs or other immune cells was low. The CEACAM1+ intratumoral Tregs accumulated with tumor progression, whereas the CEACAM1- subset did not. Notably, we found that CEACAM1 marked intratumoral Tregs that exhibited highly suppressive and activated phenotypes with substantial clonal expansion. Depletion of CEACAM1-expressing cells from tumor-infiltrating leukocytes led to increased effector functions of tumor-infiltrating T cells. Moreover, CEACAM1+ cell depletion further enhanced anti-PD-1-mediated reinvigoration of exhausted CD8+ T cells. CONCLUSIONS: CEACAM1 marks highly suppressive subset of intratumoral Tregs, and can be a target for selective depletion of intratumoral Tregs. These results may inform future studies on CEACAM1-mediated depletion in patients with cancer.

Characterization of the gene signature correlated with favorable response to chemoradiotherapy in rectal cancer: A hypothesis-generating study.

PURPOSE: This study aimed to define the gene signature associated with response to neoadjuvant chemoradiotherapy (nCRT), or chemoradiosensitivity (CRS) signature, in rectal cancer, and investigate the correlation between the CRS signature and characteristics of tumor. MATERIALS AND METHODS: Three public microarray datasets of pre-nCRT rectal cancer were used to discover and validate the CRS signature, and the pathway analysis of the CRS signature was performed. Patients in The Cancer Genome Atlas (TCGA) dataset were stratified according to the CRS signature enrichment score, and mutational profile and proportions of infiltrated immune cells were compared. RESULTS: In the discovery dataset (GSE53781), 95 genes were upregulated in complete responders compared to non-complete responders and defined as the CRS signature. Pathways regarding DNA replication and repair processes as well as inflammatory response were enriched in the CRS signature. In the validation datasets (GSE35452 and GSE45404), patients with favorable response to nCRT exhibited higher enrichment score of the CRS. In TCGA-READ cohort, patients with high CRS signature harbored KRAS mutation in lower frequency than those with low CRS signature. In addition, proportions of proinflammatory immune cells were higher, but proportion of immunosuppressive M2 macrophages was lower in patients with high CRS signature than those with low CRS signature. CONCLUSIONS: The current integrative bioinformatic analysis suggests the CRS signature and showed that the CRS signature is associated with dissimilar mutational profile and increased immune response. The discovered CRS signature and related characteristics may serve as candidate of stratification factor in upcoming studies for rectal cancer.

Dynamic changes in peripheral blood monocytes early after anti-PD-1 therapy predict clinical outcomes in hepatocellular carcinoma.

Immune checkpoint inhibitors are effective for advanced hepatocellular carcinoma (HCC), but there remains a need for peripheral blood biomarkers to predict the clinical response. Here, we analyzed the peripheral blood of 45 patients with advanced HCC who underwent nivolumab. During treatment, frequency of classical monocytes (CD14+CD16-) was increased on day 7, and the fold increase in the frequency on day 7 over day 0 (cMonocyteD7/D0) was significantly higher in patients with durable clinical benefit (DCB) than in patients with non-DCB (NDB). When we analyzed transcriptomes of classical monocytes, CD274, gene encoding PD-L1, was upregulated in NDB patients compared to DCB patients at day 7. Notably, gene signature of suppressive tumor-associated macrophages, or IL4l1+PD-L1+IDO1+ macrophages, was enriched after treatment in NDB patients, but not in DCB patients. Accordingly, the fold increase in the frequency of PD-L1+ classical monocytes at day 7 over day 0 (cMonocyte-PDL1D7/D0) was higher in NDB patients than DCB patients. The combined biomarker cMonocyteD7/D0/cMonocyte-PDL1D7/D0 was termed the "monocyte index", which was significantly higher in DCB patients than NDB patients. Moreover, the monocyte index was an independent prognostic factor for survival. Overall, our results suggest that early changes of circulating classical monocytes, represented as a monocyte index, could predict clinical outcomes of advanced HCC patients undergoing anti-PD-1 therapy.

CD39+ tissue-resident memory CD8+ T cells with a clonal overlap across compartments mediate antitumor immunity in breast cancer.

Despite being a standard treatment option in breast cancer, immune checkpoint inhibitors (ICIs) are only efficacious for a subset of patients. To gain a better understanding of the antitumor immune response in breast cancer, we examined the heterogeneity of CD8+ T cells in tumors, metastatic lymph nodes (mLNs), and peripheral blood from patients with early breast cancer (n = 131). Among tissue-resident memory CD8+ T (TRM) cells, including virus- and tumor-specific CD8+ T cells, CD39 expression was observed in a tumor-specific and exhausted subpopulation in both tumors and mLNs. CD39+ TRM cells from tumors and mLNs exhibited a phenotypic similarity and clonally overlapped with each other. Moreover, tumor or mLN CD39+ TRM cells clonally overlapped with CD39- TRM and non-TRM cells in the same compartment, implying a tissue-specific differentiation process. These inter-subpopulationally overlapping CD39+ TRM clonotypes were frequently detected among effector memory CD8+ T cells in peripheral blood, suggesting a systemic clonal overlap. CD39+ TRM cell enrichment was heterogeneous among molecular subtypes of breast cancer, which is associated with the different role of antitumor immune responses in each subtype. In vitro blockade of PD-1 and/or CTLA-4 effectively restored proliferation of CD39+ TRM cells and enhanced cytokine production by CD8+ T cells from tumors or mLNs, particularly in the presence of CD39+ TRM enrichment. This suggests that CD39+ TRM cells have a capacity for functional restoration upon ICI treatment. Thus, our study indicates that CD39+ TRM cells with a clonal overlap across compartments are key players in antitumor immunity in breast cancer.

Combination of OX40 Co-Stimulation, Radiotherapy, and PD-1 Inhibition in a Syngeneic Murine Triple-Negative Breast Cancer Model.

Immune checkpoint inhibitors have been successful in a wide range of tumor types but still have limited efficacy in immunologically cold tumors, such as breast cancers. We hypothesized that the combination of agonistic anti-OX40 (α-OX40) co-stimulation, PD-1 blockade, and radiotherapy would improve the therapeutic efficacy of the immune checkpoint blockade in a syngeneic murine triple-negative breast cancer model. Murine triple-negative breast cancer cells (4T1) were grown in immune-competent BALB/c mice, and tumors were irradiated with 24 Gy in three fractions. PD-1 blockade and α-OX40 were administered five times every other day. Flow cytometric analyses and immunohistochemistry were used to monitor subsequent changes in the immune cell repertoire. The combination of α-OX40, radiotherapy, and PD-1 blockade significantly improved primary tumor control, abscopal effects, and long-term survival beyond 2 months (60%). In the tumor microenvironment, the ratio of CD8+ T cells to CD4 + FOXP3+ regulatory T cells was significantly elevated and exhausted CD8+ T cells (PD-1+, CTLA-4+, TIM-3+, or LAG-3+ cells) were significantly reduced in the triple combination group. Systemically, α-OX40 co-stimulation and radiation significantly increased the CD103+ dendritic cell response in the spleen and plasma IFN-γ, respectively. Together, our results suggest that the combination of α-OX40 co-stimulation and radiation is a viable approach to overcome therapeutic resistance to PD-1 blockade in immunologically cold tumors, such as triple-negative breast cancer.

Uncoupling immune trajectories of response and adverse events from anti-PD-1 immunotherapy in hepatocellular carcinoma.

BACKGROUND & AIMS: While immune checkpoint blockade (ICB) has shown promise in patients with hepatocellular carcinoma (HCC), it is associated with modest response rates and immune-related adverse events (irAEs) are common. In this study, we aimed to decipher immune trajectories and mechanisms of response and/or irAEs in patients with HCC receiving anti-programmed cell death 1 (anti-PD-1) therapy. METHODS: Pre- and on-treatment peripheral blood samples (n = 60) obtained from 32 patients with HCC (Singapore cohort) were analysed by cytometry by time-of-flight and single-cell RNA sequencing, with flow cytometric validation in an independent Korean cohort (n = 29). Mechanistic validation was conducted by bulk RNA sequencing of 20 pre- and on-treatment tumour biopsies and using a murine HCC model treated with different immunotherapeutic combinations. RESULTS: Single-cell analyses identified CXCR3+CD8+ effector memory T (TEM) cells and CD11c+ antigen-presenting cells (APC) as associated with response (p = 0.0004 and 0.0255, respectively), progression-free survival (p = 0.00079 and 0.0015, respectively), and irAEs (p = 0.0034 and 0.0125, respectively) in anti-PD-1-treated patients with HCC. Type-1 conventional dendritic cells were identified as the specific APC associated with response, while 2 immunosuppressive CD14+ myeloid clusters were linked to reduced irAEs. Further analyses of CXCR3+CD8+ TEM cells showed cell-cell interactions specific to response vs. irAEs, from which the anti-PD-1 and anti-TNFR2 combination was harnessed to uncouple these effects, resulting in enhanced response without increased irAEs in a murine HCC model. CONCLUSIONS: This study identifies early predictors of clinical response to anti-PD-1 ICB in patients with HCC and offers mechanistic insights into the immune trajectories of these immune subsets at the interface between response and toxicity. We also propose a new combination immunotherapy for HCC to enhance response without exacerbating irAEs. CLINICAL TRIAL NUMBER: NCT03695952. LAY SUMMARY: Response rates to immune checkpoint blockade (ICB) treatment in hepatocellular carcinoma (HCC) remain modest and adverse events are common. Herein, we identified early predictors of response and gained an in-depth understanding of the immunological mechanisms behind response and adverse events in patients with HCC treated with ICB. We also proposed a new combination immunotherapy for HCC that enhances response without exacerbating adverse events.

Radiomic models based on magnetic resonance imaging predict the spatial distribution of CD8+ tumor-infiltrating lymphocytes in breast cancer.

Infiltration of CD8+ T cells and their spatial contexture, represented by immunophenotype, predict the prognosis and therapeutic response in breast cancer. However, a non-surgical method using radiomics to evaluate breast cancer immunophenotype has not been explored. Here, we assessed the CD8+ T cell-based immunophenotype in patients with breast cancer undergoing upfront surgery (n = 182). We extracted radiomic features from the four phases of dynamic contrast-enhanced magnetic resonance imaging, and randomly divided the patients into training (n = 137) and validation (n = 45) cohorts. For predicting the immunophenotypes, radiomic models (RMs) that combined the four phases demonstrated superior performance to those derived from a single phase. For discriminating the inflamed tumor from the non-inflamed tumor, the feature-based combination model from the whole tumor (RM-wholeFC) showed high performance in both training (area under the receiver operating characteristic curve [AUC] = 0.973) and validation cohorts (AUC = 0.985). Similarly, the feature-based combination model from the peripheral tumor (RM-periFC) discriminated between immune-desert and excluded tumors with high performance in both training (AUC = 0.993) and validation cohorts (AUC = 0.984). Both RM-wholeFC and RM-periFC demonstrated good to excellent performance for every molecular subtype. Furthermore, in patients who underwent neoadjuvant chemotherapy (n = 64), pre-treatment images showed that tumors exhibiting complete response to neoadjuvant chemotherapy had significantly higher scores from RM-wholeFC and lower scores from RM-periFC. Our RMs predicted the immunophenotype of breast cancer based on the spatial distribution of CD8+ T cells with high accuracy. This approach can be used to stratify patients non-invasively based on the status of the tumor-immune microenvironment.

Radiation Response Prediction Model Based on Integrated Clinical and Genomic Data Analysis.

PURPOSE: The value of the genomic profiling by targeted gene-sequencing on radiation therapy response prediction was evaluated through integrated analysis including clinical information. Radiation response prediction model was constructed based on the analyzed findings. MATERIALS AND METHODS: Patients who had the tumor sequenced using institutional cancer panel after informed consent and received radiotherapy for the measurable disease served as the target cohort. Patients with irradiated tumor locally controlled for more than 6 months after radiotherapy were defined as the durable local control (DLC) group, otherwise, non-durable local control (NDLC) group. Significant genomic factors and domain knowledge were used to develop the Bayesian Network model to predict radiotherapy response. RESULTS: Altogether, 88 patients were collected for analysis. Of those, 41 (43.6%) and 47 (54.4%) patients were classified as the NDLC and DLC group, respectively. Somatic mutations of NOTCH2 and BCL were enriched in the NDLC group, whereas, mutations of CHEK2, MSH2, and NOTCH1 were more frequently found in the DLC group. Altered DNA repair pathway was associated with better local failure-free survival (hazard ratio, 0.40; 95% confidence interval, 0.19 to 0.86; p=0.014). Smoking somatic signature was found more frequently in the DLC group. Area under the receiver operating characteristic curve of the Bayesian network model predicting probability of 6-month local control was 0.83. CONCLUSION: Durable radiation response was associated with alterations of DNA repair pathway and smoking somatic signature. Bayesian network model could provide helpful insights for high precision radiotherapy. However, these findings should be verified in prospective cohort for further individualization.

The Role of Postoperative Radiotherapy in Intracranial Solitary Fibrous Tumor/Hemangiopericytoma: A Multi-institutional Retrospective Study (KROG 18-11).

PURPOSE: This study aimed to evaluate the role of postoperative radiotherapy (PORT) in intracranial solitary fibrous tumor/hemangiopericytoma (SFT/HPC). MATERIALS AND METHODS: A total of 133 patients with histologically confirmed HPC were included from eight institutions. Gross total resection (GTR) and subtotal resection (STR) were performed in 86 and 47 patients, respectively. PORT was performed in 85 patients (64%). The prognostic effects of sex, age, performance, World Health Organization (WHO) grade, location, size, Ki-67, surgical extent, and PORT on local control (LC), distant metastasis-free survival (DMFS), progression-free survival (PFS), and overall survival (OS) were estimated by univariate and multivariate analyses. RESULTS: The 10-year PFS, and OS rates were 45%, and 71%, respectively. The multivariate analysis suggested that PORT significantly improved LC (p < 0.001) and PFS (p < 0.001). The PFS benefit of PORT was maintained in the subgroup of GTR (p=0.001), WHO grade II (p=0.001), or STR (p < 0.001). In the favorable subgroup of GTR and WHO grade II, PORT was also significantly related to better PFS (p=0.028). WHO grade III was significantly associated with poor DMFS (p=0.029). In the PORT subgroup, the 0-0.5 cm margin of the target volume showed an inferior LC to a large margin with 1.0-2.0 cm (p=0.021). Time-dependent Cox proportion analysis showed that distant failures were significantly associated with poor OS (p=0.003). CONCLUSION: This multicenter study supports the role of PORT in disease control of intracranial SFT/HPC, irrespective of the surgical extent and grade. For LC, PORT should enclose the tumor bed with sufficient margin.

A radiomic signature model to predict the chemoradiation-induced alteration in tumor-infiltrating CD8+ cells in locally advanced rectal cancer.

BACKGROUND AND PURPOSE: Regarding the altered tumor immune status following cytotoxic treatment, this study aims to develop a radiomic signature to predict CD8+ tumor-infiltrating lymphocyte (TIL) density changes in chemoradiotherapy (CRT) of rectal cancer. MATERIALS AND METHODS: We used the magnetic resonance imaging (MRI) and immunohistochemistry data before and after neoadjuvant CRT. The discovery datasets consisted of pre-CRT dataset A1 (n = 113), post-CRT datasets A2 (n = 32; predominance of tumor) and A3 (n = 20; pure fibrosis). The developed model was validated in dataset B (n = 28). Thirty-eight radiomic features from T2-weighted MRI scans were incorporated into the least absolute shrinkage and selection operator method. RESULTS: In pre-CRT dataset A1, the area under the receiver operating characteristic curve (AUC) values of radiomic score for predicting CD8+ TILs were 0.760 and 0.729 for training and validation subsets, respectively. A significant correlation was observed between the signature and CD8+ TIL density in the post-CRT dataset A2 (Pearson's R = -0.372, P = 0.036), whereas no association was found in dataset A3 (Pearson's R = -0.069, P = 0.77). The association was also observed in the validation dataset B (Pearson's R = -0.374, P = 0.049). In dataset A2, the radiomic score difference predicted changes in CD8+ TIL density (AUC = 0.824). CONCLUSION: We established the MRI-derived radiomic signature for predicting CRT-induced alterations in CD8+ TILs. This study suggests the clinical utility of radiomics-immunophenotype modeling to evaluate tumor immune status following neoadjuvant chemoradiation in rectal cancer.

Image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance imaging.

INTRODUCTION: To develop an image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance (MR) imaging. MATERIALS AND METHODS: A total of 466 patients with locally advanced rectal cancer who received preoperative chemoradiotherapy followed by surgical resection were collected from single center, among whom 113 (24.3%) were allocated to the holdout testing set. Complete response (pCR) was defined as Dworak tumor regression grade (TRG) 4, while good response (GR) was defined as TRG 3 or 4. Based on post-chemoradiotherapy T2-weighted axial MR images, two deep learning models were developed to predict pCR and GR, respectively. The prediction performance of the deep learning models was evaluated in the testing set and was compared to that of a senior radiologist and a radiation oncologist. RESULTS: The deep learning model showed an area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 0.76, 0.30, 0.96, 0.67, 0.87, and 85.0% for predicting pCR and 0.72, 0.54, 0.81, 0.60, 0.77, and 71.7% for predicting GR, respectively. The deep learning model had a superior predictive performance than the observers. Fair agreement between the ground truth and the model was shown for pCR prediction (kappa = 0.34) and GR prediction (kappa = 0.36). CONCLUSIONS: The post-chemoradiotherapy T2-weighted axial MR image-based deep learning model showed acceptable performance in predicting pCR or GR in patients with rectal cancer, compared with human observers.

Risk Stratification Using Neoadjuvant Rectal Score in the Era of Neoadjuvant Chemoradiotherapy: Validation With Long-term Outcome Data.

BACKGROUND: Despite the widespread use of neoadjuvant chemoradiotherapy, there is no prognostic surrogate marker established in locally advanced rectal cancer. OBJECTIVE: This study evaluated the role of neoadjuvant rectal score as a prognostic factor to stratify individual-level risks of survival and tumor recurrence. DESIGN: This is a retrospective study. SETTINGS: This study was conducted at the Seoul National University Hospital. PATIENTS: A total of 397 patients who underwent chemoradiotherapy plus total mesorectal excision were analyzed. INTERVENTIONS: There was no intervention. MAIN OUTCOME MEASURES: Harrell C statistic and receiver operating characteristic analysis, as well as Cox regression analysis, were used to assess the prognostic strength. RESULTS: The low (<8), intermediate (8-16), and high (>16) neoadjuvant rectal score groups included 91 (23%), 208 (52%), and 98 patients (25%). A high neoadjuvant rectal score was independently associated with inferior overall survival and disease-free survival (p = 0.011 and 0.008). Regarding the prognostic models adjusted for neoadjuvant rectal score (I) and ypT/N stage (II), the c-index was higher in model I (0.799 and 0.787, p = 0.009 for overall survival; 0.752 and 0.743, p = 0.093 for disease-free survival). The predictive ability of the neoadjuvant rectal score was superior to tumor regression grade, ypT, and ypN in the receiver operating characteristic analyses (p < 0.05 for all). Adjuvant chemotherapy was associated with better overall and disease-free survival (p = 0.003 and 0.052) in the high neoadjuvant rectal score group. LIMITATIONS: Potential selection bias attributed to the retrospective study design was a limitation. CONCLUSIONS: We verified the applicability of the neoadjuvant rectal score to stratify the relapse risk at the individual level for patients with stage II/III rectal cancer undergoing neoadjuvant chemoradiotherapy. Additional studies are needed to validate the usability of neoadjuvant rectal score levels as a determinant of adjuvant strategy. See Video Abstract at http://links.lww.com/DCR/B354. ESTRATIFICACIÓN DE RIESGO UTILIZANDO LA PUNTUACIÓN RECTAL NEOADYUVANTE EN LA ERA DE LA QUIMIORRADIOTERAPIA NEOADYUVANTE: VALIDACIÓN CON DATOS DE RESULTADOS A LARGO PLAZO: A pesar del uso generalizado de la quimiorradioterapia neoadyuvante, no existe un marcador subrogado pronóstico establecido en el cáncer de recto localmente avanzado.Este estudio evaluó el papel de la puntuación rectal neoadyuvante como factor pronóstico para estratificar los riesgos a nivel individual de supervivencia y recurrencia tumoral.Este es un estudio retrospectivo.Este estudio se realizó en el Hospital de la Universidad Nacional de Seúl.Se analizaron un total de 397 pacientes que se sometieron a quimiorradioterapia más escisión mesorrectal total.No hubo intervención.El análisis estadístico C de Harrell y las características operativas del receptor, así como el análisis de regresión de Cox, se utilizaron para evaluar la fuerza pronóstica.Los grupos de puntaje rectal neoadyuvante bajo (<8), intermedio (8-16) y alto (> 16) incluyeron 91 (23%), 208 (52%) y 98 (25%) pacientes, respectivamente. Una puntuación rectal neoadyuvante alta se asoció independientemente con una supervivencia general y una supervivencia libre de enfermedad inferiores (p = 0.011 y 0.008, respectivamente). Con respecto a los modelos pronósticos ajustados por la puntuación rectal neoadyuvante (I) y el estadio ypT/N (II), el índice c fue mayor en el modelo I (0.799 y 0.787, p = 0.009 para la supervivencia general; 0.752 y 0.743, p = 0.093 para supervivencia libre de enfermedad). La capacidad predictiva de la puntuación rectal neoadyuvante fue superior al grado de regresión tumoral, ypT y ypN en los análisis de características operativas del receptor (p <0.05 para todos). La quimioterapia adyuvante se asoció con una mejor supervivencia global y libre de enfermedad (p = 0.003 y 0.052, respectivamente) en el grupo de puntaje rectal neoadyuvante alto.El sesgo de selección potencial debido al diseño retrospectivo del estudio fue la limitación.Verificamos la aplicabilidad de la puntuación rectal neoadyuvante para estratificar el riesgo de recurrencia a nivel individual para pacientes con cáncer rectal en estadio II/III sometidos a quimiorradioterapia neoadyuvante. Se necesitan más estudios para validar la usabilidad de los niveles de puntuación rectal neoadyuvante como determinante de la estrategia adyuvante. Consulte Video Resumen en http://links.lww.com/DCR/B354.

Machine Learning Model to Predict Pseudoprogression Versus Progression in Glioblastoma Using MRI: A Multi-Institutional Study (KROG 18-07).

Some patients with glioblastoma show a worsening presentation in imaging after concurrent chemoradiation, even when they receive gross total resection. Previously, we showed the feasibility of a machine learning model to predict pseudoprogression (PsPD) versus progressive disease (PD) in glioblastoma patients. The previous model was based on the dataset from two institutions (termed as the Seoul National University Hospital (SNUH) dataset, N = 78). To test this model in a larger dataset, we collected cases from multiple institutions that raised the problem of PsPD vs. PD diagnosis in clinics (Korean Radiation Oncology Group (KROG) dataset, N = 104). The dataset was composed of brain MR images and clinical information. We tested the previous model in the KROG dataset; however, that model showed limited performance. After hyperparameter optimization, we developed a deep learning model based on the whole dataset (N = 182). The 10-fold cross validation revealed that the micro-average area under the precision-recall curve (AUPRC) was 0.86. The calibration model was constructed to estimate the interpretable probability directly from the model output. After calibration, the final model offers clinical probability in a web-user interface.

Combining Radiomics and Blood Test Biomarkers to Predict the Response of Locally Advanced Rectal Cancer to Chemoradiation.

BACKGROUND/AIM: A noninvasive method for predicting a patient's response to neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer would be useful because this would help determine the subsequent treatment strategy. Two types of noninvasive biomarkers have previously been studied, based on radiomics and based on blood test parameters. We hypothesized that a combination of both types would provide a better predictive power, and this has not previously been investigated. PATIENTS AND METHODS: Data from 135 patients with locally advanced rectal cancer who underwent nCRT were retrospectively allocated into training and validation cohorts in a 2:1 ratio. Sixty-five radiomics features were extracted from tumors segmented on T2-weighted magnetic resonance images. An elastic net was applied to generate four models for discerning the patients with good responses to nCRT based on radiomics features (model R), blood biomarkers (model B), both (model RB), and a linear combination of models R and B (model R+B). RESULTS: Among 65 radiomics features, 17 were selected as robust features for model development. The AUC values of model R, model B, model RB, and model R+B achieved 0.751, 0.627, 0.785, and 0.711 in the training cohort (n=90), and 0.705, 0.603, 0.679, and 0.705 in validation cohort (n=45), respectively. In the entire cohort, models RB and R+B demonstrated a significantly better performance than model B but not R. There was no correlation between the scores of models R and B (p=0.76). Radiomics features had a greater influence than blood biomarkers on models RB and R+B. CONCLUSION: A non-redundancy between radiomics features and blood-based biomarkers was observed. Furthermore, radiomics features are more valuable in terms of predicting response to nCRT. The importance of combining non-invasive biomarkers in future investigations is highlighted.

Lower Extremity Lymphedema in Gynecologic Cancer Patients: Propensity Score Matching Analysis of External Beam Radiation versus Brachytherapy.

The goal of this study is to compare the risk of lower extremity lymphedema (LEL) between pelvic external beam radiation therapy (EBRT) and vaginal brachytherapy, and to identify risk factors for LEL in gynecologic cancer patients treated with adjuvant radiation therapy (RT) after radical surgery. A total of 263 stage I-III gynecologic cancer patients who underwent adjuvant RT were retrospectively reviewed. One-to-one case-matched analysis was conducted with propensity scores generated from patient, tumor, and treatment characteristics. Using the risk factors found in this study, high- and low-risk groups were identified. With a median follow-up of 36.0 months, 35 of 263 (13.3%) patients developed LEL. In multivariate analysis, laparoscopic surgery (HR 2.548; p = 0.024), harvesting more than 30 pelvic lymph nodes (HR 2.246; p = 0.028), and para-aortic lymph node dissection (PALND, HR 2.305; p = 0.014) were identified as independent risk factors for LEL. After propensity score matching, the LEL incidence of the brachytherapy group was significantly lower than the EBRT group (p = 0.025). In conclusion, high-risk patients with risk factors such as laparoscopic surgery, harvesting more than 30 pelvic lymph nodes, PALND, and adjuvant pelvic EBRT require closer observation for LEL.