Tumour radiosensitivity is associated with immune activation in solid tumours

Parotid glands have a dysregulated immune response following radiation therapy

Head and neck cancer treatment often consists of surgical resection of the tumor followed by ionizing radiation (IR), which can damage surrounding tissues and cause adverse side effects. The underlying mechanisms of radiation-induced salivary gland dysfunction are not fully understood, and treatment options are scarce and ineffective. The wound healing process is a necessary response to tissue injury, and broadly consists of inflammatory, proliferative, and redifferentiation phases with immune cells playing key roles in all three phases. In this study, select immune cells were phenotyped and quantified, and certain cytokine and chemokine concentrations were measured in mouse parotid glands after IR. Further, we used a model where glandular function is restored to assess the immune phenotype in a regenerative response. These data suggest that irradiated parotid tissue does not progress through a typical inflammatory response observed in wounds that heal. Specifically, total immune cells (CD45+) decrease at days 2 and 5 following IR, macrophages (F4/80+CD11b+) decrease at day 2 and 5 and increase at day 30, while neutrophils (Ly6G+CD11b+) significantly increase at day 30 following IR. Additionally, radiation treatment reduces CD3- cells at all time points, significantly increases CD3+/CD4+CD8+ double positive cells, and significantly reduces CD3+/CD4-CD8- double negative cells at day 30 after IR. Previous data indicate that post-IR treatment with IGF-1 restores salivary gland function at day 30, and IGF-1 injections attenuate the increase in macrophages, neutrophils, and CD4+CD8+ T cells observed at day 30 following IR. Taken together, these data indicate that parotid salivary tissue exhibits a dysregulated immune response following radiation treatment which may contribute to chronic loss of function phenotype in head and neck cancer survivors.

C-C chemokine receptor 4 (CCR4)-positive regulatory T cells interact with tumor-associated macrophages to facilitate metastatic potential after radiation

PURPOSE

Our previous study revealed that elevated C-C motif chemokine ligand 2 (CCL2) secretion by irradiated cancer cells recruited C-C motif chemokine receptor 2 (CCR2)-positive myeloid cells and polarized M2-type tumor-associated macrophages (TAMs), promoting lung metastasis in an established mouse model. This study investigated the impact of CCL2 and TAMs on adaptive immunity.

METHODS

We assessed the influence of CCL2 and TAMs on adaptive immunity through two ectopic allograft mouse models constructed with MB49 bladder cancer cells and Lewis lung carcinoma cells. Both models exhibited delayed primary tumor growth following radiation therapy (RT), but RT promoted the development of pulmonary metastases in C57BL/6 mice. Additionally, we employed a direct coculture system to investigate the interaction between macrophages and target cells in the context of adaptive immunity.

RESULTS

C-C motif chemokine receptor 4 (CCR4)-positive regulatory T cells (Tregs) were recruited to the postirradiated tumor microenvironment (TME). Utilizing a CCR4 antagonist to inhibit CCL2-CCR4 activation reversed the infiltration of CCR4 + Tregs and reduced the incidence of pulmonary metastases. In addition, a positive feedback loop between M2-type TAMs and Tregs was observed. The combined blockade of the CCL2-CCR4 and CCL2-CCR2 signaling pathways further decreased the risk of RT-promoted lung metastasis.

CONCLUSION

The recruitment of CCR4 + Tregs to the postirradiated TME increases the metastatic potential of tumor cells through increased interactions with M2-type TAMs. A significant reduction in post-RT lung metastases in ectopic mouse models was achieved by disrupting the recruitment of both CCR4 + Tregs and CCR2 + myeloid cells, which are TAM precursors.

Individualising radiation therapy decisions in breast cancer patients based on tumour infiltrating lymphocytes and genomic biomarkers

Radiation therapy (RT) has long been fundamental for the curative treatment of breast cancer. While substantial progress has been made in the anatomical and technological precision of RT delivery, and some approaches to de-escalate or omit RT based on clinicopathologic features have been successful, there remain substantial opportunities to refine individualised RT based on tumour biology. A major area of clinical and research interest is to ascertain the individualised risk of loco-regional recurrence to direct treatment decisions regarding escalation and de-escalation of RT. Patient-tailored treatment with RT is considerably lagging behind compared with the massive progress made in the field of personalised medicine that currently mainly applies to decisions on the use of systemic therapy or targeted agents. Herein we review select literature surrounding the use of tumour genomic biomarkers and biomarkers of the immune system, including tumour infiltrating lymphocytes (TILs), within the management of breast cancer, specifically as they relate to progress in moving toward analytically validated and clinically tested biomarkers utilized in RT.

Novel insights into the progression and prognosis of the calpain family members in hepatocellular carcinoma: a comprehensive integrated analysis

Objectives: The goal of our bioinformatics study was to comprehensively analyze the association between the whole calpain family members and the progression and prognosis of hepatocellular carcinoma (HCC). Methods: The data were collected from The Cancer Genome Atlas (TCGA). The landscape of the gene expression, copy number variation (CNV), mutation, and DNA methylation of calpain members were analyzed. Clustering analysis was performed to stratify the calpain-related groups. The least absolute shrinkage and selection operator (LASSO)-based Cox model was used to select hub survival genes. Results: We found 14 out of 16 calpain members expressed differently between tumor and normal tissues of HCC. The clustering analyses revealed high- and low-risk calpain groups which had prognostic difference. We found the high-risk calpain group had higher B cell infiltration and higher expression of immune checkpoint genes HAVCR2, PDCD1, and TIGHT. The CMap analysis found that the histone deacetylase (HDAC) inhibitor trichostatin A and the PI3K-AKT-mTOR pathway inhibitors LY-294002 and wortmannin might have a therapeutic effect on the high-risk calpain group. The DEGs between calpain groups were identified. Subsequent univariate Cox analysis of each DEG and LASSO-based Cox model obtained a calpain-related prognostic signature. The risk score model of this signature showed good ability to predict the overall survival of HCC patients in TCGA datasets and external validation datasets from the Gene Expression Omnibus database and the International Cancer Genome Consortium database. Conclusion: We found that calpain family members were associated with the progression, prognosis, and drug response of HCC. Our results require further studies to confirm.

Towards Data Driven RT Prescription: Integrating Genomics into RT Clinical Practice

The genomic era has significantly changed the practice of clinical oncology. The use of genomic-based molecular diagnostics including prognostic genomic signatures and new-generation sequencing has become routine for clinical decisions regarding cytotoxic chemotherapy, targeted agents and immunotherapy. In contrast, clinical decisions regarding radiation therapy (RT) remain uninformed about the genomic heterogeneity of tumors. In this review, we discuss the clinical opportunity to utilize genomics to optimize RT dose. Although from the technical perspective, RT has been moving towards a data-driven approach, RT prescription dose is still based on a one-size-fits all approach, with most RT dose based on cancer diagnosis and stage. This approach is in direct conflict with the realization that tumors are biologically heterogeneous, and that cancer is not a single disease. Here, we discuss how genomics can be integrated into RT prescription dose, the clinical potential for this approach and how genomic-optimization of RT dose could lead to new understanding of the clinical benefit of RT.

Improving the efficacy of combined radiotherapy and immunotherapy: focusing on the effects of radiosensitivity

Cancer treatment is gradually entering an era of precision, with multitude studies in gene testing and immunotherapy. Tumor cells can be recognized and eliminated by the immune system through the expression of tumor-associated antigens, but when the cancer escapes or otherwise suppresses immunity, the balance between cancer cell proliferation and immune-induced cancer cell killing may be interrupted, resulting in tumor proliferation and progression. There has been significant attention to combining conventional cancer therapies (i.e., radiotherapy) with immunotherapy as opposed to treatment alone. The combination of radio-immunotherapy has been demonstrated in both basic research and clinical trials to provide more effective anti-tumor responses. However, the absolute benefits of radio-immunotherapy are dependent on individual characteristics and not all patients can benefit from radio-immunotherapy. At present, there are numerous articles about exploring the optimal models for combination radio-immunotherapy, but the factors affecting the efficacy of the combination, especially with regard to radiosensitivity remain inconclusive. Radiosensitivity is a measure of the response of cells, tissues, or individuals to ionizing radiation, and various studies have shown that the radiosensitivity index (RSI) will be a potential biomarker for predicting the efficacy of combination radio-immunotherapy. The purpose of this review is to focus on the factors that influence and predict the radiosensitivity of tumor cells, and to evaluate the impact and predictive significance of radiosensitivity on the efficacy of radio-immunotherapy combination.

Development and Validation of a Genomic Profile for the Omission of Local Adjuvant Radiation in Breast Cancer

PURPOSE

Adjuvant radiotherapy (RT) is used for women with early-stage invasive breast cancer treated with breast-conserving surgery. However, some women with low risk of recurrence may safely be spared RT. This study aimed to identify these women using a molecular-based approach.

METHODS

We analyzed two randomized trials of women with node-negative invasive breast cancer to ± RT following breast-conserving surgery: SweBCG91-RT (stage I-II, no adjuvant systemic therapy) and Princess Margaret (age 50 years or older, T1-T2, adjuvant tamoxifen). Transcriptome-wide profiling was performed (Affymetrix Human Exon 1.0 ST microarray). Patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative tumors and with gene expression data were included. The SweBCG91-RT cohort was divided into training (N = 243) and validation (N = 354) cohorts. A 16-gene signature named Profile for the Omission of Local Adjuvant Radiation (POLAR) was trained to predict locoregional recurrence (LRR) using elastic net regression. POLAR was then validated in the SweBCG91-RT validation cohort and the Princess Margaret cohort (N = 132).

RESULTS

Patients categorized as POLAR low-risk without RT had a 10-year LRR of 6% (95% CI, 2 to 16) and 7% (0 to 27) in SweBCG91-RT and Princess Margaret cohorts, respectively. There was no significant benefit from RT in POLAR low-risk patients (hazard ratio [HR], 1.1 [0.39 to 3.4], P = .81, and HR, 1.5 [0.14 to 16], P = .74, respectively). Patients categorized as POLAR high-risk had a significant decreased risk of LRR with RT (HR, 0.43 [0.24 to 0.78], P = .0055, and HR, 0.25 [0.07 to 0.92], P = .038, respectively). An exploratory analysis testing for interaction between RT and POLAR in the combined validation cohort was performed (P = .066).

CONCLUSION

The novel POLAR genomic signature on the basis of LRR biology may identify patients with a low risk of LRR despite not receiving RT, and thus may be candidates for RT omission.

Radiosensitivity is associated with antitumor immunity in estrogen receptor-negative breast cancer

PURPOSE

This study evaluated radiosensitivity and the tumor microenvironment (TME) to identify characteristics of breast cancer patients who would benefit most from radiation therapy.

METHODS

We analyzed 1903 records from the Molecular Taxonomy of Breast Cancer International Consortium cohort using the radiosensitivity index and gene expression deconvolution algorithms, CIBERSORT and xCell, that estimates the TME composition of tumor samples. In this study, patients were stratified according to TME and radiosensitivity. We performed integrative analyses of clinical and immuno-genomic data to characterize molecular features associated with radiosensitivity.

RESULTS

Radiosensitivity was significantly associated with activation of antitumor immunity. In contrast, radioresistance was associated with a reactive stromal microenvironment. The immuno-genomic analysis revealed that estrogen receptor (ER) pathway activity was correlated with suppression of antitumor immunity. In ER-negative disease, the best prognosis was shown in the immune-high and radiosensitive group patients, and the lowest was in the immune-low and radioresistant group patients. In ER-positive disease, immune signature and radiosensitivity had no prognostic significance.

CONCLUSION

Taken together, these results suggest that tumor radiosensitivity is associated with activation of antitumor immunity and a better prognosis, particularly in patients with ER-negative breast cancer.

Tertiary lymphoid structures are critical for cancer prognosis and therapeutic response

Tertiary lymphoid structures (TLSs) are ectopic lymphocyte aggregates that form at sites of chronic inflammation, including cancers, in non-lymphoid tissues. Although the formation of TLSs is similar to that of secondary lymphoid organs, the pathogenic factors leading to TLS formation in cancerous tissues and the mechanisms underlying the role of these structures in the intra-tumoral adaptive antitumor immune response are not fully understood. The presence of TLSs may impact patient prognosis and treatment outcomes. This review examines the current understanding of TLSs in cancers, including their composition and formation as well as their potential to predict prognosis and therapeutic efficacy. We also summarize strategies to induce TLS formation for cancer treatment.

Radioimmunotherapy in HPV-Associated Head and Neck Squamous Cell Carcinoma

HPV-associated head and neck squamous cell carcinoma (HNSCC) is a cancer entity with unique biological and clinical characteristics that requires more personalized treatment strategies. As the backbone of conventional therapeutics, radiation is now harnessed to synergize with immunotherapy in multiple malignancies. Accumulating preclinical and clinical data have suggested the potential of radioimmunotherapy in eliciting local and systemic anti-tumor response via direct killing of tumor cells and immunogenic cell death. However, this effect remains uncertain in HPV-associated HNSCC. Owing to its intrinsic radiosensitivity and distinct tumor microenvironment, HPV-associated HNSCC may represent a good candidate for radioimmunotherapy. In this review, we provide a detailed illustration of the biology, the genomic features, and immune landscapes of HPV-associated HNSCC that support the synergism between radiation and immune agents. The interaction between radiotherapy and immunotherapy is described. We also highlight the present evidence as well as ongoing trials using different combination strategies in the recurrent/metastatic or definitive settings. In addition, we have summarized the challenges and outlook for future trial design, with special emphasis on radiotherapy optimization and novel therapeutic options to incorporate.

The Role of Cancer-Associated Fibroblasts in Ovarian Cancer

Simple Summary

Ovarian cancer is a lethal gynecologic tumor and is generally resistant to conventional treatments. Stable cancer-associated fibroblasts (CAFs) are important cellular components in the ovarian cancer tumor microenvironment and may provide novel resources for future treatment strategies. Different subtypes of CAFs display specific functions in tumor pathogenesis and various CAF markers suggest potential treatment targets. Several clinical or preclinical trials have targeted stromal fibroblasts and focused on the properties of CAFs to enhance ovarian cancer treatment efficacy. This review concentrates on the origins, subtypes, and activation of CAFs, as well as specific roles of CAFs in regulating tumor development and drug resistance, and aims to provide potential and prospective targets for improving the therapeutic efficacy of ovarian cancer treatment.

Abstract

Ovarian cancer is a lethal gynecologic tumor and is generally resistant to conventional treatments. Stable cancer-associated fibroblasts (CAFs) are important cellular components in the ovarian cancer tumor microenvironment and may provide novel resources for future treatment strategies. Different subtypes of CAFs display specific functions in tumor pathogenesis and various CAF markers suggest potential treatment targets, such as FAP and GPR77. Both autocrine and paracrine cytokines play important roles in the CAF activation process and regulate tumor progression. Downstream mediators and pathways, including IL-6, TGF-β, NF-κB, mitogen-activated protein kinase (MAPK), and AKT/mTOR/(p70S6K), play important roles in the initiation, proliferation, invasiveness, and metastasis of ovarian cancer cells and also participate in angiogenesis, therapeutic resistance, and other biological processes. Several clinical or preclinical trials have targeted stromal fibroblasts and focused on the properties of CAFs to enhance ovarian cancer treatment outcomes. This review concentrates on the origins, subtypes, and activation of CAFs, as well as specific roles of CAFs in regulating tumor development and drug resistance, and aims to provide potential and prospective targets for improving the therapeutic efficacy of ovarian cancer treatment.

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.

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.

Combination of Radiosensitivity Gene Signature and PD-L1 Status Predicts Clinical Outcome of Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma: A Study Based on The Cancer Genome Atlas Dataset

Aim: The aim of our study was to investigate the potential predictive value of the combination of radiosensitivity gene signature and PD-L1 expression for the prognosis of locally advanced head and neck squamous cell carcinoma (HNSCC).

Methods: The cohort was selected from The Cancer Genome Atlas (TCGA) and classified into the radiosensitive (RS) group and radioresistant (RR) group by a radiosensitivity-related gene signature. The cohort was also grouped as PD-L1-high or PD-L1-low based on PD-L1 mRNA expression. The least absolute shrinkage and selection operator (lasso)-based Cox model was used to select hub survival genes. An independent validation cohort was obtained from the Gene Expression Omnibus (GEO) database.

Results: We selected 288 locally advanced HNSCC patients from TCGA. The Kaplan–Meier method found that the RR and PD-L1-high group had a worse survival than others (p = 0.033). The differentially expressed gene (DEG) analysis identified 553 upregulated genes and 486 downregulated genes (p < 0.05, fold change >2) between the RR and PD-L1-high group and others. The univariate Cox analysis of each DEG and subsequent lasso-based Cox model revealed five hub survival genes (POU4F1, IL34, HLF, CBS, and RNF165). A further hub survival gene-based risk score model was constructed, which was validated by an external cohort. We observed that a higher risk score predicted a worse prognosis (p = 0.0013). The area under the receiver operating characteristic curve (AUC) plots showed that this risk score model had good prediction value (1-year AUC = 0.684, 2-year AUC = 0.702, and 3-year AUC = 0.688). Five different deconvolution methods all showed that the B cells were lower in the RR and PD-L1-high group (p < 0.05). Finally, connectivity mapping analysis showed that the histone deacetylase (HDAC) inhibitor trichostatin A might have the potential to reverse the phenotype of RR and PD-L1-high in locally advanced HNSCC (p < 0.05, false discovery rate <0.1).

Conclusion: The combination of 31-gene signature and the PD-L1 mRNA expression had a potential predictive value for the prognosis of locally advanced HNSCC who had RT. The B cells were lower in the RR and PD-L1-high group. The identified risk gene signature of locally advanced HNSCC and the potential therapeutic drug trichostatin A for the RR and PD-L1-high group are worth being further studied in a prospective homogenous cohort.

Moving towards the Future of Radio-Immunotherapy: Could We “Tailor” the Abscopal Effect on Head and Neck Cancer Patients?

The abscopal effect (AbE) is defined as radiation-induced shrinkage of distant, non-treated, neoplastic lesions and it is considered the best clinical picture of the efficient immune stimulation by irradiation. The first report about abscopal tumor regression upon radiotherapy dates back to the beginning of the 20th century. The growing preclinical and clinical synergism between radiation and immunotherapy gave birth the purpose to more easily reproduce the abscopal effect, nevertheless, it is still rare in clinical practice. In this review we summarize immunological modulation of radiotherapy, focusing on the well-balanced equilibrium of tumor microenvironment and how radio-immunotherapy combinations can perturb it, with particular attention on head and neck squamous cell cancer. Finally, we investigate future perspectives, with the aim to “tailor” the abscopal effect to the patient.

A CTL/M2 macrophage-related four-gene signature predicting metastasis-free survival in triple-negative breast cancer treated with adjuvant radiotherapy

PURPOSE

This study aimed to develop and validate a prognostic model for metastasis-free survival (MFS) based on genes that may functionally interact with cytotoxic T lymphocytes (CTLs) and M2 macrophages in patients with triple-negative breast cancer (TNBC) who underwent adjuvant radiotherapy.

METHODS

The transcriptional and phenotypic profiles of TNBC and other breast cancer subtypes were downloaded from gene expression omnibus (GEO). The abundance of infiltrated immune cells was evaluated through CIBERSORTx or MCP-counter. A weighted linear model, the score for MFS (SMFS), was developed using the least absolute shrinkage and selection operator (LASSO) in GSE58812 and validated in GSE2034 and GSE12276. The biological implication of the SMFS was explored by evaluating its associations with TNBC molecular subtypes and other radiosensitivity- or immune-related signatures.

RESULTS

A model consisting of the PCDH12/ELP3, PCDH12/MSRA, and FAM160B2/MSRA gene expression ratios with non-zero coefficients finally selected by LASSO was developed using GSE58812. In GSE2034 (treatment with adjuvant radiotherapy), the SMFS was significantly associated with MFS in TNBC patients (hazard ratio (HR) = 8.767, 95% confidence interval (CI) 1.856-41.408, P = 0.006) and, to a lesser extent, in non-TNBC patients (HR = 2.888, 95% CI 1.076-7.750, P = 0.035). However, the interaction of subtype (TNBC vs non-TNBC) and the SMFS tended to be significant (P_interaction = 0.081). In contrast, the SMFS was not significantly associated with MFS in either TNBC patients (P = 0.499) or non-TNBC patients (P = 0.536) in GSE12276 (treatment without radiotherapy). Among the four TNBC molecular subtypes, the c1 and c4 subtypes exhibited higher CTL infiltration and lower SMFS values than the c2 and c3 subtypes. In addition, the SMFS was positively correlated with the abundance of endothelial cells (r = 0.413, P < 0.001).

CONCLUSION

The proposed model has the potential to predict MFS in TNBC patients after adjuvant radiotherapy, and the SMFS may represent a measurement of tumor immune suppression.

Tumor Microenvironment in Breast Cancer-Updates on Therapeutic Implications and Pathologic Assessment

The tumor microenvironment (TME) in breast cancer comprises local factors, cancer cells, immune cells and stromal cells of the local and distant tissues. The interaction between cancer cells and their microenvironment plays important roles in tumor proliferation, propagation and response to therapies. There is increasing research in exploring and manipulating the non-cancerous components of the TME for breast cancer treatment. As the TME is now increasingly recognized as a treatment target, its pathologic assessment has become a critical component of breast cancer management. The latest WHO classification of tumors of the breast listed stromal response pattern/fibrotic focus as a prognostic factor and includes recommendations on the assessment of tumor infiltrating lymphocytes and PD-1/PD-L1 expression, with therapeutic implications. This review dissects the TME of breast cancer, describes pathologic assessment relevant for prognostication and treatment decision, and details therapeutic options that interacts with and/or exploits the TME in breast cancer.

Architecture of Cancer-Associated Fibroblasts in Tumor Microenvironment: Mapping Their Origins, Heterogeneity, and Role in Cancer Therapy Resistance

The tumor stroma, a key component of the tumor microenvironment (TME), is a key determinant of response and resistance to cancer treatment. The stromal cells, extracellular matrix (ECM), and blood vessels influence cancer cell response to therapy and play key roles in tumor relapse and therapeutic outcomes. Of the stromal cells present in the TME, much attention has been given to cancer-associated fibroblasts (CAFs) as they are the most abundant and important in cancer initiation, progression, and therapy resistance. Besides releasing several factors, CAFs also synthesize the ECM, a key component of the tumor stroma. In this expert review, we examine the role of CAFs in the regulation of tumor cell behavior and reveal how CAF-derived factors and signaling influence tumor cell heterogeneity and development of novel strategies to combat cancer. Importantly, CAFs display both phenotypic and functional heterogeneity, with significant ramifications on CAF-directed therapies. Principal anti-cancer therapies targeting CAFs take the form of: (1) CAFs' ablation through use of immunotherapies, (2) re-education of CAFs to normalize the cells, (3) cellular therapies involving CAFs delivering drugs such as oncolytic adenoviruses, and (4) stromal depletion via targeting the ECM and its related signaling. The CAFs' heterogeneity could be a result of different cellular origins and the cancer-specific tumor microenvironmental effects, underscoring the need for further multiomics and biochemical studies on CAFs and the subsets. Lastly, we present recent advances in therapeutic targeting of CAFs and the success of such endeavors or their lack thereof. We recommend that to advance global public health and personalized medicine, treatments in the oncology clinic should be combinatorial in nature, strategically targeting both cancer cells and stromal cells, and their interactions.

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.

Identification of an immune classification for cervical cancer and integrative analysis of multiomics data

BACKGROUND

To understand the molecular mechanisms of the antitumour response, we analysed the immune landscape of cervical cancer to identify novel immune molecular classes.

METHODS

We established a stable immune molecular classification using a nonnegative matrix factorization algorithm and validated the correlation in two validation sets of 249 samples.

RESULTS

Approximately 78% of cervical cancers (CCs) (228/293) were identified to show significant enrichment in immune cells (e.g., CD8 T cells and macrophages), a type I IFN response, enhanced cytolytic activity and high PDCD1, and these CCs were referred to as the "immune class". We further identified two subtypes of the immune class: active immune and exhausted subtypes. Although the active immune subtype was characterized by enrichment of IFN signatures and better survival, the exhausted subtype expressed activated stroma, a wound healing signature, enhanced M2 macrophages and absence of CD8 T cells and the TGF-β response signature. Integrative analysis of multiomics data identified EGFR, JUN, MYC, FN1 and SERPINE1 as key modulators of the tumour immune microenvironment and potential targets for combination therapies which was validated in two validation sets.

CONCLUSIONS

Our study introduces a novel immune classification that might predict ideal candidates to receive immunotherapy or specific combination therapies.

Effect of radiotherapy on T cell and PD-1 / PD-L1 blocking therapy in tumor microenvironment

Cancer is a worldwide problem that threatens human health. Radiotherapy plays an important role in a variety of cancer treatment methods. The administration of radiotherapy can alter the differentiation pathways and functions of T cells, which in turn improves the immune response of T cells. Radiotherapy can also induce up-regulation of PD-L1 expression, which means that it has great potential for enhancing the therapeutic effect of anti-PD-1/PD-L1 inhibitors and reducing the risk of drug resistance toward them. At present, the combination of radiotherapy and anti-PD-1/PD-L1 inhibitors has shown significant therapeutic effects in clinical tumor research. This review focuses on the mechanism of radiotherapy on T cells reported in recent years, as well as related research progress in the application of PD-1/PD-L1 blockers. It will provide a theoretical basis for the rational clinical application of radiotherapy combined with PD-1/PD-L1 inhibitors.

Exploring the role of survivin in neuroendocrine neoplasms

Neuroendocrine tumors (NETs) are a heterogenous group of tumors. While most NETs have excellent prognosis, certain subsets have aggressive biology and have limited treatment options. We explored the role of survivin in NET as a prognostic and potentially therapeutic marker. Tissue microarrays of 132 patients were stained for survivin using immunohistochemistry (IHC) and correlated with outcomes. Using genomic database, we then correlated survivin (BIRC5) mRNA expression with radiosensitivity index (RSI) in 52 samples of NET. Finally, we studied the effect of radiation on survivin expression in human cell lines and the impact of knock-down of BIRC5 on cell proliferation and radiation sensitivity. We found that survivin positivity by IHC correlated with a shorter survival (overall survival 8.5 years vs. 18.3 years, p < 0.001). There was a positive correlation between BIRC5 expression and RSI (r = 0.234, p < 0.0001). Radiation exposure increased BIRC5 gene expression in a human carcinoid cell line. Knockout of BIRC5 using siRNA reduced proliferation of neuroendocrine cells but did not increase radiation sensitivity. We conclude that survivin expression in NET correlates with an inferior survival and survivin expression in human carcinoid cell lines increases after exposure to ionizing radiation.

Endogenous Retrovirus Activation as a Key Mechanism of Anti-Tumor Immune Response in Radiotherapy

The generation of DNA double-strand breaks has historically been taught as the mechanism through which radiotherapy kills cancer cells. Recently, radiation-induced cytosolic DNA release and activation of the cGAS/STING pathway, with ensuing induction of interferon secretion and immune activation, have been recognized as important mechanisms for radiation-mediated anti-tumor efficacy. Here we demonstrate that radiation-induced activation of endogenous retroviruses (ERVs) also plays a major role in regulating the anti-tumor immune response during irradiation. Radiation-induced ERV-associated dsRNA transcription and subsequent activation of the innate antiviral MDA5/MAVS/TBK1 pathway led to downstream transcription of interferon-stimulated genes. Additionally, genetic knockout of KAP1, a chromatin modulator responsible for suppressing ERV transcription sites within the genome, enhanced the effect of radiation-induced anti-tumor response in vivo in two different tumor models. This anti-tumor response was immune-mediated and required an intact host immune system. Our findings indicate that radiation-induced ERV-dsRNA expression and subsequent immune response play critical roles in clinical radiotherapy, and manipulation of epigenetic regulators and the dsRNA-sensing innate immunity pathway could be promising targets to enhance the efficacy of radiotherapy and cancer immunotherapy.

[Predictive assays for responses of tumors and normal tissues in radiation oncology]

The impact of curative radiotherapy depends mainly on the total dose delivered homogenously in the target volume. Tumor sensitivity to radiotherapy may be particularly inconstant depending on location, histology, somatic genetic parameters and the capacity of the immune system to infiltrate the tumor. In addition, the dose delivered to the surrounding healthy tissues may reduce the therapeutic ratio of many radiation treatments. In a same population treated in one center with the same technique, it appears that individual radiosensitivity clearly exists, namely in terms of late side effects that are in principle non-reversible. This review details the different radiobiological approaches that have been developed to better predict the tumor response but also the radiation-induced late effects.

Utilizing the genomically adjusted radiation dose (GARD) to personalize adjuvant radiotherapy in triple negative breast cancer management

Background

Utilizing the linear quadratic model and the radiosensitivity index (RSI), we have derived an expression for the genomically adjusted radiation dose (GARD) to model radiation dose effect. We hypothesize GARD is associated with local recurrence and can be used to optimize individual triple negative breast cancer (TNBC) radiation dose.

Methods

TN patients from two independent datasets were assessed. The first cohort consisted of 58 patients treated at 5 European centers with breast conservation surgery followed by adjuvant radiotherapy (RT). The second dataset consisted of 55 patients treated with adjuvant radiation therapy.

Findings

In cohort 1, multivariable analysis revealed that as a dichotomous variable (HR: 2.5 95% CI 1–7.1; p = .05), GARD was associated with local control. This was confirmed in the second independent dataset where GARD was the only significant factor associated with local control (HR: 4.4 95% CI 1.1–29.5; p = .04). We utilized GARD to calculate an individualized radiation dose for each TN patient in cohort 2 by determining the physical dose required to achieve the GARD target value (GARD ≥ 21). While 7% of patients were optimized with a dose of 30 Gy, 91% of patients would be optimized with 70 Gy.

Interpretation

GARD is associated with local control following whole breast or post-mastectomy radiotherapy (RT) in TN patients. By modeling RT dose effect with GARD, we demonstrate that no single dose is optimal for all patients and propose the first dose range to optimize RT at an individual patient level in TNBC.

Radiosensitivity Differences between EGFR Mutant and Wild-Type Lung Cancer Cells are Larger at Lower Doses

In the era of precision medicine, radiotherapy strategies should be determined based on genetic profiles that predict tumor radiosensitivity. Accordingly, pre-clinical research aimed at discovering clinically applicable genetic profiles is needed. However, how a given genetic profile affects cancer cell radiosensitivity is unclear. To address this issue, we performed a pilot in vitro study by utilizing EGFR mutational status as a model for genetic profile. Clonogenic assays of EGFR mutant (n = 6) and wild-type (n = 9) non-small cell lung carcinoma (NSCLC) cell lines were performed independently by two oncologists. Clonogenic survival parameters SF₂, SF₄, SF₆, SF₈, mean inactivation dose (MID), D₁₀, D₅₀, α, and β were obtained using the linear quadratic model. The differences in the clonogenic survival parameters between the EGFR mutant and wild-type cell lines were assessed using the Mann-Whitney U test. As a result, for both datasets, the p values for SF₂, SF₄, D₅₀, α, and α/β were below 0.05, and those for SF₂ were lowest. These data indicate that a genetic profile of NSCLC cell lines might be predictive for their radiation response; i.e., EGFR mutant cell lines might be more sensitive to low dose- and low fraction sized-irradiation.

Clinical update on head and neck cancer: molecular biology and ongoing challenges

Head and neck squamous cell carcinomas (HNSCCs) are an aggressive, genetically complex and difficult to treat group of cancers. In lieu of truly effective targeted therapies, surgery and radiotherapy represent the primary treatment options for most patients. But these treatments are associated with significant morbidity and a reduction in quality of life. Resistance to both radiotherapy and the only available targeted therapy, and subsequent relapse are common. Research has therefore focussed on identifying biomarkers to stratify patients into clinically meaningful groups and to develop more effective targeted therapies. However, as we are now discovering, the poor response to therapy and aggressive nature of HNSCCs is not only affected by the complex alterations in intracellular signalling pathways but is also heavily influenced by the behaviour of the extracellular microenvironment. The HNSCC tumour landscape is an environment permissive of these tumours' aggressive nature, fostered by the actions of the immune system, the response to tumour hypoxia and the influence of the microbiome. Solving these challenges now rests on expanding our knowledge of these areas, in parallel with a greater understanding of the molecular biology of HNSCC subtypes. This update aims to build on our earlier 2014 review by bringing up to date our understanding of the molecular biology of HNSCCs and provide insights into areas of ongoing research and perspectives for the future.

Integrating Mathematical Modeling into the Roadmap for Personalized Adaptive Radiation Therapy

In current radiation oncology practice, treatment protocols are prescribed based on the average outcomes of large clinical trials, with limited personalization and without adaptations of dose or dose fractionation to individual patients based on their individual clinical responses. Predicting tumor responses to radiation and comparing predictions against observed responses offers an opportunity for novel treatment evaluation. These analyses can lead to protocol adaptation aimed at the improvement of patient outcomes with better therapeutic ratios. We foresee the integration of mathematical models into radiation oncology to simulate individual patient tumor growth and predict treatment response as dynamic biomarkers for personalized adaptive radiation therapy (RT).

Genomic stratification based on radiosensitivity and PD-L1 for tailoring therapeutic strategies in cervical cancer

Aim: We performed an immunogenomic analysis to help identify a model for the cervical cancer therapeutic module. Patients & methods: Patients were divided into groups according to radiosensitivity and PD-L1 expression status. Results: The PD-L1-low-radioresistant (RR) group indicated worse overall survival under radiotherapy. In addition, the PD-L1-low-RR group showed the lowest immunophenoscore and predicted poor response to anti-PD-1 treatment. Differentially expressed genes associated with the PD-L1-low-RR group were found to play a role in the immune response pathways. FGF19 and PLA2G5 were validated to be upregulated in the PD-L1-low-RR group in the Gene Expression Omnibus database, which predicted the overall survival in the The Cancer Genome Atlas. Conclusion: It will be important to test radiosensitivity and PD-L1 stratification to predict the response to strategies in cervical cancer patients.

Tertiary lymphoid structures in the era of cancer immunotherapy

Tertiary lymphoid structures (TLSs) are ectopic lymphoid organs that develop in non-lymphoid tissues at sites of chronic inflammation including tumours. Key common characteristics between secondary lymphoid organogenesis and TLS neogenesis have been identified. TLSs exist under different maturation states in tumours, culminating in germinal centre formation. The mechanisms that underlie the role of TLSs in the adaptive antitumour immune response are being deciphered. The description of the correlation between TLS presence and clinical benefit in patients with cancer, suggesting that TLSs could be a prognostic and predictive factor, has drawn strong interest into investigating the role of TLSs in tumours. A current major challenge is to exploit TLSs to promote lymphocyte infiltration, activation by tumour antigens and differentiation to increase the antitumour immune response. Several approaches are being developed using chemokines, cytokines, antibodies, antigen-presenting cells or synthetic scaffolds to induce TLS formation. Strategies aiming to induce TLS neogenesis in immune-low tumours and in immune-high tumours, in this case, in combination with therapeutic agents dampening the inflammatory environment and/or with immune checkpoint inhibitors, represent promising avenues for cancer treatment.

Chemokines Modulate Immune Surveillance in Tumorigenesis, Metastasis, and Response to Immunotherapy

Chemokines are small secreted proteins that orchestrate migration and positioning of immune cells within the tissues. Chemokines are essential for the function of the immune system. Accumulating evidence suggest that chemokines play important roles in tumor microenvironment. In this review we discuss an association of chemokine expression and activity within the tumor microenvironment with cancer outcome. We summarize regulation of immune cell recruitment into the tumor by chemokine-chemokine receptor interactions and describe evidence implicating chemokines in promotion of the "inflamed" immune-cell enriched tumor microenvironment. We review both tumor-promoting function of chemokines, such as regulation of tumor metastasis, and beneficial chemokine roles, including stimulation of anti-tumor immunity and response to immunotherapy. Finally, we discuss the therapeutic strategies target tumor-promoting chemokines or induce/deliver beneficial chemokines within the tumor focusing on pre-clinical studies and clinical trials going forward. The goal of this review is to provide insight into comprehensive role of chemokines and their receptors in tumor pathobiology and treatment.

Cytokine Modulation in Breast Cancer Patients Undergoing Radiotherapy: A Revision of the Most Recent Studies

Breast cancer (BC) is the most common tumor and the second cause for cancer-related death in women worldwide, although combined treatments are well-established interventions. Several effects seem to be responsible for poor outcomes in advanced or triple-negative BC patients. Focusing on the interaction of ionizing radiation with tumor and normal tissues, the role of cytokine modulation as a surrogate of immunomodulation must still be explored. In this work, we carried out an overview of studies published in the last five years involving the cytokine profile in BC patients undergoing radiotherapy. The goal of this review was to evaluate the profile and modulation of major cytokines and interleukins as potential biomarkers of survival, treatment response, and toxicity in BC patient undergoing radiotherapy. Out of 47 retrieved papers selected using PubMed search, 15 fulfilled the inclusion criteria. Different studies reported that the modulation of specific cytokines was time- and treatment-dependent. Radiotherapy (RT) induces the modulation of inflammatory cytokines up to 6 months for most of the analyzed cytokines, which in some cases can persist up to several years post-treatment. The role of specific cytokines as prognostic and predictive of radiotherapy outcome is critically discussed.

The Future of Radiation Oncology in Soft Tissue Sarcoma

Radiotherapy (RT) is an important component of the treatment of soft tissue sarcomas (STS) and has been traditionally incorporated with a homogenous approach despite the reality that STS displays a known heterogeneity in clinicopathologic features and treatment outcomes. In this article, we explore the principle components of personalized medicine, including genomics, radiomics, and treatment response, along with their impact on the future of radiation therapy for STS. We propose a shift in the treatment paradigm for STS from a one-size-fits-all technique to one that implements the tenets of personalized medicine and includes the framework for a potential clinical trial technique in this heterogeneous disease.

Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors

BACKGROUND

Adjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify patients for adjuvant radiotherapy. This study presents the development and validation of a targeted gene expression assay to predict the risk of ipsilateral breast tumor recurrence and response to adjuvant radiotherapy after breast-conserving surgery in primary breast cancer.

METHODS

Fresh-frozen primary tumors from 336 patients radically (clear margins) operated on with breast-conserving surgery with or without radiotherapy were collected. Patients were split into a discovery cohort (N = 172) and a validation cohort (N = 164). Genes predicting ipsilateral breast tumor recurrence in an Illumina HT12 v4 whole transcriptome analysis were combined with genes identified in the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single-sample predictors for ipsilateral breast tumor recurrence based on a k-top scoring pairs algorithm were trained, stratified for estrogen receptor (ER) status and radiotherapy. Two previously published profiles, the radiosensitivity signature of Speers et al., and the 10-gene signature of Eschrich et al., were also included in the targeted panel.

RESULTS

Derived single-sample predictors were prognostic for ipsilateral breast tumor recurrence in radiotherapy-treated ER+ patients (AUC 0.67, p = 0.01), ER+ patients without radiotherapy (AUC = 0.89, p = 0.02), and radiotherapy-treated ER- patients (AUC = 0.78, p < 0.001). Among ER+ patients, radiotherapy had an excellent effect on tumors classified as radiosensitive (p < 0.001), while radiotherapy had no effect on tumors classified as radioresistant (p = 0.36) and there was a high risk of ipsilateral breast tumor recurrence (55% at 10 years). Our single-sample predictors developed in ER+ tumors and the radiosensitivity signature correlated with proliferation, while single-sample predictors developed in ER- tumors correlated with immune response. The 10-gene signature negatively correlated with both proliferation and immune response.

CONCLUSIONS

Our targeted single-sample predictors were prognostic for ipsilateral breast tumor recurrence and have the potential to stratify patients for adjuvant radiotherapy. The correlation of models with biology may explain the different performance in subgroups of breast cancer.

Personalizing Radiation Treatment Delivery in the Management of Breast Cancer

Long-term data establishes the efficacy of radiotherapy in the adjuvant management of breast cancer. New dose and fractionation schemas have evolved and are available, each with unique risks and rewards. Current efforts are ongoing to tailor radiotherapy to the unique biology of breast cancer. In this review, we discuss our efforts to personalize radiotherapy dosing using genomic data and the implications for future clinical trials. We also explore immune mechanisms that may contribute to a tumor's unique radiation sensitivity or resistance.

Approach to oligometastatic disease in head and neck cancer, on behalf of the GORTEC

Median survival for recurrent/metastatic head and neck squamous cell cancer (HNSCC) patients is about 10 months after first-line best systemic treatment. We aimed to assess current approaches of oligometastatic HNSCC patients by the analysis of current concept and published data (1995–2017) in this population. Five-year survival rates are over 20% in selected patients who undergo metastasis-directed therapy by either surgery or stereotactic irradiation. Human papillomavirus(+) HNSCC patients have more disseminated metastases but respond more favorably and also benefit from ablative treatments. Treatments of oligometastases are expanding rapidly. Unmet needs include revised imaging follow-up strategies to detect metastases earlier, identification of predictive noninvasive biomarkers for treatment guidance, assessment and corrections of biases in current studies and randomized clinical trials.