Radiation Dermatitis: Radiation-Induced Effects on the Structural and Immunological Barrier Function of the Epidermis.

An important hallmark of radiation dermatitis is the impairment of the mitotic ability of the stem/progenitor cells in the basal cell layers due to radiation-induced DNA damage, leading to suppressed cell renewal in the epidermis. However, this mechanism alone does not adequately explain the complex pathogenesis of radiation-induced skin injury. In this review, we summarize the latest findings on the complex pathogenesis of radiation dermatitis and correlate these with the clinical features of radiation-induced skin reactions. The current studies show that skin exposure to ionizing radiation induces cellular senescence in the epidermal keratinocytes. As part of their epithelial stress response, these senescent keratinocytes secrete pro-inflammatory mediators, thereby triggering skin inflammation. Keratinocyte-derived cytokines and chemokines modulate intercellular communication with the immune cells, activating skin-resident and recruiting skin-infiltrating immune cells within the epidermis and dermis, thereby orchestrating the inflammatory response to radiation-induced tissue damage. The increased expression of specific chemoattractant chemokines leads to increased recruitment of neutrophils into the irradiated skin, where they release cytotoxic granules that are responsible for the exacerbation of an inflammatory state. Moreover, the importance of IL-17-expressing γδ-T cells to the radiation-induced hyperproliferation of keratinocytes was demonstrated, leading to reactive hyperplasia of the epidermis. Radiation-induced, reactive hyperproliferation of the keratinocytes disturbs the fine-tuned keratinization and cornification processes, leading to structural dysfunction of the epidermal barrier. In summary, in response to ionizing radiation, epidermal keratinocytes have important structural and immunoregulatory barrier functions in the skin, coordinating interacting immune responses to eliminate radiation-induced damage and to initiate the healing process.

TCCIA: a comprehensive resource for exploring CircRNA in cancer immunotherapy.

BACKGROUND: Immunotherapies targeting immune checkpoints have gained increasing attention in cancer treatment, emphasizing the need for predictive biomarkers. Circular RNAs (circRNAs) have emerged as critical regulators of tumor immunity, particularly in the PD-1/PD-L1 pathway, and have shown potential in predicting immunotherapy efficacy. Yet, the detailed roles of circRNAs in cancer immunotherapy are not fully understood. While existing databases focus on either circRNA profiles or immunotherapy cohorts, there is currently no platform that enables the exploration of the intricate interplay between circRNAs and anti-tumor immunotherapy. A comprehensive resource combining circRNA profiles, immunotherapy responses, and clinical outcomes is essential to advance our understanding of circRNA-mediated tumor-immune interactions and to develop effective biomarkers. METHODS: To address these gaps, we constructed The Cancer CircRNA Immunome Atlas (TCCIA), the first database that combines circRNA profiles, immunotherapy response data, and clinical outcomes across multicancer types. The construction of TCCIA involved applying standardized preprocessing to the raw sequencing FASTQ files, characterizing circRNA profiles using an ensemble approach based on four established circRNA detection tools, analyzing tumor immunophenotypes, and compiling immunotherapy response data from diverse cohorts treated with immune checkpoint blockades (ICBs). RESULTS: TCCIA encompasses over 4,000 clinical samples obtained from 25 cohorts treated with ICBs along with other treatment modalities. The database provides researchers and clinicians with a cloud-based platform that enables interactive exploration of circRNA data in the context of ICB. The platform offers a range of analytical tools, including browse of identified circRNAs, visualization of circRNA abundance and correlation, association analysis between circRNAs and clinical variables, assessment of the tumor immune microenvironment, exploration of tumor molecular signatures, evaluation of treatment response or prognosis, and identification of altered circRNAs in immunotherapy-sensitive and resistant tumors. To illustrate the utility of TCCIA, we showcase two examples, including circTMTC3 and circMGA, by employing analysis of large-scale melanoma and bladder cancer cohorts, which unveil distinct impacts and clinical implications of different circRNA expression in cancer immunotherapy. CONCLUSIONS: TCCIA represents a significant advancement over existing resources, providing a comprehensive platform to investigate the role of circRNAs in immuno-oncology.

Machine Learning-assisted immunophenotyping of peripheral blood identifies innate immune cells as best predictor of response to induction chemo-immunotherapy in head and neck squamous cell carcinoma - knowledge obtained from the CheckRad-CD8 trial.

PURPOSE: Individual prediction of treatment response is crucial for personalized treatment in multimodal approaches against head-and-neck squamous cell carcinoma (HNSCC). So far, no reliable predictive parameters for treatment schemes containing immunotherapy have been identified. This study aims to predict treatment response to induction chemo-immunotherapy based on the peripheral blood immune status in patients with locally advanced HNSCC. METHODS: The peripheral blood immune phenotype was assessed in whole blood samples in patients treated in the phase II CheckRad-CD8 trial as part of the pre-planned translational research program. Blood samples were analyzed by multicolor flow cytometry before (T1) and after (T2) induction chemo-immunotherapy with cisplatin/docetaxel/durvalumab/tremelimumab. Machine Learning techniques were used to predict pathological complete response (pCR) after induction therapy. RESULTS: The tested classifier methods (LDA, SVM, LR, RF, DT, and XGBoost) allowed a distinct prediction of pCR. Highest accuracy was achieved with a low number of features represented as principal components. Immune parameters obtained from the absolute difference (lT2-T1l) allowed the best prediction of pCR. In general, less than 30 parameters and at most 10 principal components were needed for highly accurate predictions. Across several datasets, cells of the innate immune system such as polymorphonuclear cells, monocytes, and plasmacytoid dendritic cells are most prominent. CONCLUSIONS: Our analyses imply that alterations of the innate immune cell distribution in the peripheral blood following induction chemo-immuno-therapy is highly predictive for pCR in HNSCC.

ArthroRad trial: randomized multicenter single-blinded trial on the effect of low-dose radiotherapy for painful osteoarthritis-final results after 12-month follow-up.

OBJECTIVE: Updated report about the randomized comparison of the effect of radiotherapy on painful osteoarthritis (OA) applying a standard dose vs. a very low dose regime after a follow-up of 1 year. PATIENTS AND METHODS: Patients presenting with OA of the hand/finger and knee joints were included. After randomization (every joint region was randomized separately) the following protocols were applied: (a) standard arm: total dose 3.0 Gy, single fractions of 0.5 Gy twice a week; (b) experimental arm: total dose 0.3 Gy, single fractions of 0.05 Gy twice a week. The dosage was blinded for the patients. For evaluation the scores after 1­year visual analog scale (VAS), Knee Injury and Osteoarthritis Outcome Score-Short Form (KOOS-PS), Short Form Score for the Assessment and Quantification of Chronic Rheumatic Affections of the Hands (SF-SACRAH) and 12-item Short-Form Health Survey (SF-12) were used (for further details: see [1]). RESULTS: The standard dose was applied to 77 hands and 33 knees, the experimental dose was given to 81 hands and 30 knees. After 12 months, the data of 128 hands and 45 knees were available for evaluation. Even after this long time, we observed a favorable response of pain to radiotherapy in both trial arms; however, there were no reasonable statistically significant differences between both arms concerning pain, functional, and quality of life scores. Side effects did not occur. The only prognostic factor was the pain level before radiotherapy. CONCLUSIONS: We found a favorable pain relief and a limited response in the functional and quality of life scores in both treatment arms. The possible effect of low doses such as 0.3 Gy on pain is widely unknown.

Explainable convolutional neural networks for assessing head and neck cancer histopathology.

PURPOSE: Although neural networks have shown remarkable performance in medical image analysis, their translation into clinical practice remains difficult due to their lack of interpretability. An emerging field that addresses this problem is Explainable AI. METHODS: Here, we aimed to investigate the ability of Convolutional Neural Networks (CNNs) to classify head and neck cancer histopathology. To this end, we manually annotated 101 histopathological slides of locally advanced head and neck squamous cell carcinoma. We trained a CNN to classify tumor and non-tumor tissue, and another CNN to semantically segment four classes - tumor, non-tumor, non-specified tissue, and background. We applied Explainable AI techniques, namely Grad-CAM and HR-CAM, to both networks and explored important features that contributed to their decisions. RESULTS: The classification network achieved an accuracy of 89.9% on previously unseen data. Our segmentation network achieved a class-averaged Intersection over Union score of 0.690, and 0.782 for tumor tissue in particular. Explainable AI methods demonstrated that both networks rely on features agreeing with the pathologist's expert opinion. CONCLUSION: Our work suggests that CNNs can predict head and neck cancer with high accuracy. Especially if accompanied by visual explanations, CNNs seem promising for assisting pathologists in the assessment of cancer sections.

Automated Image Analysis of Transmission Electron Micrographs: Nanoscale Evaluation of Radiation-Induced DNA Damage in the Context of Chromatin.

BACKGROUND: Heavy ion irradiation (IR) with high-linear energy transfer (LET) is characterized by a unique depth dose distribution and increased biological effectiveness. Following high-LET IR, localized energy deposition along the particle trajectories induces clustered DNA lesions, leading to low electron density domains (LEDDs). To investigate the spatiotemporal dynamics of DNA repair and chromatin remodeling, we established the automated image analysis of transmission electron micrographs. METHODS: Human fibroblasts were irradiated with high-LET carbon ions or low-LET photons. At 0.1 h, 0.5 h, 5 h, and 24 h post-IR, nanoparticle-labeled repair factors (53BP1, pKu70, pKu80, DNA-PKcs) were visualized using transmission electron microscopy in interphase nuclei to monitor the formation and repair of DNA damage in the chromatin ultrastructure. Using AI-based software tools, advanced image analysis techniques were established to assess the DNA damage pattern following low-LET versus high-LET IR. RESULTS: Low-LET IR induced single DNA lesions throughout the nucleus, and most DNA double-strand breaks (DSBs) were efficiently rejoined with no visible chromatin decondensation. High-LET IR induced clustered DNA damage concentrated along the particle trajectories, resulting in circumscribed LEDDs. Automated image analysis was used to determine the exact number of differently sized nanoparticles, their distance from one another, and their precise location within the micrographs (based on size, shape, and density). Chromatin densities were determined from grayscale features, and nanoparticles were automatically assigned to euchromatin or heterochromatin. High-LET IR-induced LEDDs were delineated using automated segmentation, and the spatial distribution of nanoparticles in relation to segmented LEDDs was determined. CONCLUSIONS: The results of our image analysis suggest that high-LET IR induces chromatin relaxation along particle trajectories, enabling the critical repair of successive DNA damage. Following exposure to different radiation qualities, automated image analysis of nanoparticle-labeled DNA repair proteins in the chromatin ultrastructure enables precise characterization of specific DNA damage patterns.

Radiotherapy combined with docetaxel alters the immune phenotype of HNSCC cells and results in increased surface expression of CD137 and release of HMGB1 of specifically HPV-positive tumor cells.

PURPOSE: Human papilloma virus (HPV) positive head and neck squamous cell carcinoma (HNSCC) tumors respond significantly better to anticancer treatments. It is assumed to be due to a better response to radiotherapy (RT), and presumably to an increased immunogenicity. However, little is known how the immune phenotype of HNSCC tumor cells is modulated by standard treatment, namely by radiochemotherapy (RCT). METHODS: Therefore, we aimed to examine the impact of the HPV status on the immune phenotype of HNSCC cell lines following RCT with 5 × 3Gy or 1 × 19.3Gy and/or docetaxel, by analyzing cell death, release of damage-associated molecular patterns (DAMPs), surface expression of immune checkpoint molecules (ICMs) and the impact on activation of human monocyte-derived dendritic cells (hmDCs). RESULTS: Cell death induction and Hsp70 release following RCT was independent of the HPV status, and RCT significantly increased the expression of the immune suppressive ICMs PD-L1, PD-L2 and HVEM. An immune stimulatory ICM, CD137, was significantly increased following RCT only on HPV-positive cell lines, as well as the release of HMGB1. Although the treatment increased cell death and modulated ICM expression in HNSCC, the hmDCs were not activated after co-incubation with treated tumor cells. CONCLUSION: Our data with the HPV-dependent release of HMGB1 and increased expression of CD137 following RCT provide a hint for increased immunogenicity underlining the better prognosis for HPV positive tumors following RCT.

A comparison between p16-positive head and neck cancer of unknown primary (HPV-HNCUP) and oropharyngeal squamous cell carcinoma (HPV-OPSCC): are they the same disease?

INTRODUCTION: The following study aimed to answer the question if HPV-HNCUP and HPV-OPSCC are the same disease. Propensity score matching (PSM) was used to compare the oncological outcomes of both groups, in particular the 5-year overall survival rate (OS), the 5-year disease specific survival rate (DSS) and the 5-year progression free survival rate (PFS). MATERIALS AND METHODS: Firstly, between January 1st, 2007, and March 31st, 2020 a total of 131 patients were treated with HNCUP at our Department. Out of these, 21 patients with a confirmed positive p16 status were referred to surgery followed by adjuvant therapy. Secondly, between January 1st, 2000, and January 31st, 2017, a total of 1596 patients were treated with an OPSSC at our Department. Out of these, 126 patients with a confirmed positive p16 status were referred to surgery followed by adjuvant therapy. After PSM, 84 patients with HPV-OPSCC and 21 HPV-HNCUP remained in the study for further comparison. RESULTS: The OS was 63.5% (95% CI 39.4-87.6) for HPV-HNCUP and 88.9% (95% CI 90.4-100.0) for HPV-OPSCC patients and therefore, significantly lower for the first mentioned (p = 0.013). The DSS was also significantly impaired for HPV-HNCUP (71.0%, 95% CI 46.3-95.7), in comparison with HPV-OPSCC patients (95.5%, 95% CI 90.4-100.0; p = 0.002). The PFS for HPV-HNCUP patients was lower (75.6%, 95% CI 54.0-97.2) yet not significantly different to HPV-OPSCC (90.4%, 95% CI 83.5-97.3; p = 0.067). CONCLUSIONS: The results presented demonstrate a significant reduced OS and DSS for HPV-HNCUP patients. Accordingly, in our study HPV-HNCUP and HPV-OPSCC are two different entities with a different oncological outcome.

[Highlights of the ASCO and ESMO annual meetings 2022: radiotherapy of head and neck cancer]. / Highlights der ASCO- und ESMO­Jahrestagungen 2022: Strahlentherapie von Kopf­Hals­Tumoren.

At the 2022 annual meetings of the American Society of Clinical Oncology (ASCO) and the European Society for Medical Oncology (ESMO), several studies on radiation therapy for head and neck squamous cell carcinoma (HNSCC) were presented. Among the main topics were new concepts for treatment de-escalation with the goal of reducing side effects. Radiotherapy alone for nasopharyngeal carcinoma with an intermediate-risk profile was found to be noninferior to chemoradiotherapy with cisplatin while improving tolerability. In the phase II DIREKHT trial for adjuvant radiotherapy, individualized deintensification concepts of radiation dose or volume were implemented. Overall, this treatment resulted in excellent levels of locoregional control with a minimal side effects profile. In subgroup analysis, however, an increased locoregional recurrence rate was observed for tumors of the oral cavity. In 2022, as in the previous year, there was a continued focus on the role of immune checkpoint inhibitors in combination with platinum-based chemoradiotherapy in the first-line treatment of locally advanced HNSCC. In the HNSCC-15-132 trial, sequential application of the PD­1 inhibitor pembrolizumab to chemoradiotherapy was not significantly, but numerically superior to concomitant application. The phase III KEYNOTE-412 trial evaluated the efficacy of concomitant and sequential additive pembrolizumab therapy compared to additive placebo in 804 patients with locally advanced HNSCC. The observed benefit in terms of event-free survival in the pembrolizumab group marginally missed statistical significance, probably due to the particular study design. In addition, new 5­year overall survival data from the phase II trial of chemoradiotherapy in combination with the inhibitor of apoptosis proteins (IAP) antagonist xevinapant versus placebo were presented. The xevinapant group continued to demonstrate a significant survival advantage and a sustained response to treatment.

Deep learning for automatic head and neck lymph node level delineation provides expert-level accuracy.

Background: Deep learning-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still underinvestigated in academic literature. In particular, there is no publicly available open-source solution for large-scale autosegmentation of HN_LNL in the research setting. Methods: An expert-delineated cohort of 35 planning CTs was used for training of an nnU-net 3D-fullres/2D-ensemble model for autosegmentation of 20 different HN_LNL. A second cohort acquired at the same institution later in time served as the test set (n = 20). In a completely blinded evaluation, 3 clinical experts rated the quality of deep learning autosegmentations in a head-to-head comparison with expert-created contours. For a subgroup of 10 cases, intraobserver variability was compared to the average deep learning autosegmentation accuracy on the original and recontoured set of expert segmentations. A postprocessing step to adjust craniocaudal boundaries of level autosegmentations to the CT slice plane was introduced and the effect of autocontour consistency with CT slice plane orientation on geometric accuracy and expert rating was investigated. Results: Blinded expert ratings for deep learning segmentations and expert-created contours were not significantly different. Deep learning segmentations with slice plane adjustment were rated numerically higher (mean, 81.0 vs. 79.6, p = 0.185) and deep learning segmentations without slice plane adjustment were rated numerically lower (77.2 vs. 79.6, p = 0.167) than manually drawn contours. In a head-to-head comparison, deep learning segmentations with CT slice plane adjustment were rated significantly better than deep learning contours without slice plane adjustment (81.0 vs. 77.2, p = 0.004). Geometric accuracy of deep learning segmentations was not different from intraobserver variability (mean Dice per level, 0.76 vs. 0.77, p = 0.307). Clinical significance of contour consistency with CT slice plane orientation was not represented by geometric accuracy metrics (volumetric Dice, 0.78 vs. 0.78, p = 0.703). Conclusions: We show that a nnU-net 3D-fullres/2D-ensemble model can be used for highly accurate autodelineation of HN_LNL using only a limited training dataset that is ideally suited for large-scale standardized autodelineation of HN_LNL in the research setting. Geometric accuracy metrics are only an imperfect surrogate for blinded expert rating.

Identification and characterization of circular RNAs as novel putative biomarkers to predict anti-PD-1 monotherapy response in metastatic melanoma patients - Knowledge from two independent international studies.

Melanoma is the most aggressive skin malignancy with high morbidity. Anti-programmed cell death protein 1 (PD-1) monotherapy has been applied in metastatic melanoma. However, still most of the patients do not respond to anti-PD-1 and the availability of the present approved biomarkers therefore is limited. Here we combined the transcriptomic and clinical data of 163 advanced melanoma patients receiving anti-PD-1 from NIH Melanoma Genome Sequencing Project (phs000452, 122 patients) as the training and internal validation cohort, and Melanoma Institute Australia cohort (PRJEB23709, 41 patients) as the external validation cohort, respectively. Circular RNAs (circRNAs) are an evolutionarily conserved novel class of noncoding endogenous RNAs (ncRNAs) found in the eukaryotic transcriptome and were used based on RNAseq data for our analyses. 74,243 circular RNAs (circRNAs) were identified with NCLscan and CIRCexplorer2. Thereof, 70 circRNAs significantly associated with progression-free survival and overall survival. Further, a prognostic circRNAs signature consisting of HSA_CIRCpedia_1497, HSA_CIRCpedia_12559, HSA_CIRCpedia_43640, HSA_CIRCpedia_43070, and HSA_CIRCpedia_21660 could be determined with LASSO regression. This signature was a prognostic factor of overall survival and progression-free survival among the analyzed advanced melanoma patients. The concordance indexes (C-index of OStraining: 0.61, C-index of PFStraining: 0.68) also confirmed its credibility and accuracy. First enrichment analysis indicated that immune response and pathways related to tumor immune microenvironment were enriched. In conclusion, we succeeded to construct and validate novel prognostic circRNAs signature for advanced melanoma patients treated with anti-PD-1 immunotherapy.

Low-dose radiotherapy of osteoarthritis: from biological findings to clinical effects-challenges for future studies.

Osteoarthritis (OA) is one of the most common and socioeconomically relevant diseases, with rising incidence and prevalence especially with regard to an ageing population in the Western world. Over the decades, the scientific perception of OA has shifted from a simple degeneration of cartilage and bone to a multifactorial disease involving various cell types and immunomodulatory factors. Despite a wide range of conventional treatment modalities available, a significant proportion of patients remain treatment refractory. Low-dose radiotherapy (LDRT) has been used for decades in the treatment of patients with inflammatory and/or degenerative diseases and has proven a viable option even in cohorts of patients with a rather poor prognosis. While its justification mainly derives from a vast body of empirical evidence, prospective randomized trials have until now failed to prove the effectiveness of LDRT. Nevertheless, over the decades, adaptions of LDRT treatment modalities have evolved using lower dosages with establishment of different treatment schedules for which definitive clinical proof is still pending. Preclinical research has revealed that the immune system is modulated by LDRT and very recently osteoimmunological mechanisms have been described. Future studies and investigations further elucidating the underlying mechanisms are an essential key to clarify the optimal patient stratification and treatment procedure, considering the patients' inflammatory status, age, and sex. The present review aims not only to present clinical and preclinical knowledge about the mechanistic and beneficial effects of LDRT, but also to emphasize topics that will need to be addressed in future studies. Further, a concise overview of the current status of the underlying radiobiological knowledge of LDRT for clinicians is given, while seeking to stimulate further translational research.

Tumor-specific radiosensitizing effect of the ATM inhibitor AZD0156 in melanoma cells with low toxicity to healthy fibroblasts.

PURPOSE: Despite new treatment options, melanoma continues to have an unfavorable prognosis. DNA damage response (DDR) inhibitors are a promising drug class, especially in combination with chemotherapy (CT) or radiotherapy (RT). Manipulating DNA damage repair during RT is an opportunity to exploit the genomic instability of cancer cells and may lead to radiosensitizing effects in tumors that could improve cancer therapy. METHODS: A panel of melanoma-derived cell lines of different origin were used to investigate toxicity-related clonogenic survival, cell death, and cell cycle distribution after treatment with a kinase inhibitor (KI) against ATM (AZD0156) or ATR (VE-822, berzosertib), irradiation with 2 Gy, or a combination of KI plus ionizing radiation (IR). Two fibroblast cell lines generated from healthy skin tissue were used as controls. RESULTS: Clonogenic survival indicated a clear radiosensitizing effect of the ATM inhibitor (ATMi) AZD0156 in all melanoma cells in a synergistic manner, but not in healthy tissue fibroblasts. In contrast, the ATR inhibitor (ATRi) VE-822 led to additive enhancement of IR-related toxicity in most of the melanoma cells. Both inhibitors mainly increased cell death induction in combination with IR. In healthy fibroblasts, VE-822 plus IR led to higher cell death rates compared to AZD0156. A significant G2/M block was particularly induced in cancer cells when combining AZD0156 with IR. CONCLUSION: ATMi, in contrast to ATRi, resulted in synergistic radiosensitization regarding colony formation in melanoma cancer cells, while healthy tissue fibroblasts were merely affected with respect to cell death induction. In connection with an increased number of melanoma cells in the G2/M phase after ATMi plus IR treatment, ATMi seems to be superior to ATRi in melanoma cancer cell treatments when combined with RT.

Dose-escalated re-irradiation improves outcome in locally recurrent head and neck cancer - Results of a large multicenter analysis.

To determine efficacy and prognostic parameters of definitive re-irradiation of locoregionally recurrent squamous cell carcinoma of the head and neck (HNSCC). MATERIALS AND METHODS: Patients with locoregionally recurrent or second primary HNSCC undergoing re-irradiation with modern radiotherapy technique were eligible for this multicentric retrospective analysis. Main endpoints were overall survival (OS), progression-free survival (PFS) and locoregional control (LC). Univariate analyses were performed using the Kaplan Meier Method (log-rank). For multivariable analysis, Cox regression was used. RESULTS: A total of 253 patients treated between 2009 and 2020 at 16 university hospitals in Germany were included. The median follow up was 27.4 months (range 0.5-130). The median OS and PFS were 13.2 (CI: 10.7 - 15.7) months and 7.9 (CI: 6.7 - 9.1) months, respectively, corresponding to two-year OS and PFS rates of 29 % and 19 %. Rates of locoregional progression and "in-field-failure" were 62 % and 51 % after two years. Multivariable Cox regression analysis identified good ECOG performance status and high radiation dose as independent prognostic parameters for OS. Doses above 50 Gy (EQD2) achieved longer median OS of 17.8 months (vs 11.7 months, p < 0.01) and longer PFS of 9.6 months (vs 6.8 months, p < 0.01). In addition, there was a trend for worse survival in patients with tracheostomy (multivariable, p = 0.061). Concomitant systemic therapy did not significantly impact PFS or OS. CONCLUSION: Re-irradiation of locally recurrent or second primary HNSCC is efficient, especially if doses above 50 Gy (EQD2) are delivered. ECOG performance score was the strongest prognostic parameter for OS and PFS.

Expression of 3q Oncogene SEC62 Predicts Survival in Head and Neck Squamous Cell Carcinoma Patients Treated with Primary Chemoradiation.

Primary chemoradiotherapy (CRT) is an established treatment option for locally advanced head and neck squamous cell carcinomas (HNSCC) usually combining intensity modified radiotherapy with concurrent platinum-based chemotherapy. Though the majority of patients can be cured with this regimen, treatment response is highly heterogeneous and can hardly be predicted. SEC62 represents a metastasis stimulating oncogene that is frequently overexpressed in various cancer entities and is associated with poor outcome. Its role in HNSCC patients undergoing CRT has not been investigated so far. A total of 127 HNSCC patients treated with primary CRT were included in this study. The median follow-up was 5.4 years. Pretherapeutic tissue samples of the primary tumors were used for immunohistochemistry targeting SEC62. SEC62 expression, clinical and histopathological parameters, as well as patient outcome, were correlated in univariate and multivariate survival analyses. High SEC62 expression correlated with a significantly shorter overall survival (p = 0.015) and advanced lymph node metastases (p = 0.024). Further significant predictors of poor overall and progression-free survival included response to therapy (RECIST1.1), nodal status, distant metastases, tobacco consumption, recurrence of disease, and UICC stage. In a multivariate Cox hazard proportional regression analysis, only SEC62 expression (p = 0.046) and response to therapy (p < 0.0001) maintained statistical significance as independent predictors of the patients' overall survival. This study identified SEC62 as an independent prognostic biomarker in HNSCC patients treated with primary CRT. The role of SEC62 as a potential therapeutic target and its interaction with radiation-induced molecular alterations in head and neck cancer cells should further be investigated.

Case report: Patient specific combination of surgery and immunotherapy in advanced squamous cell carcinoma of the head and neck - a case series and review of literature.

Background: Prognosis of patients with recurrent or metastatic head and neck cancer is generally poor. Adjuvant immunotherapy (IT) featuring immune checkpoint inhibition (ICI) is standard of care in advanced stage head and neck squamous cell carcinoma (HNSCC) and cutaneous squamous cell carcinoma (CSCC). ICI response rates in CSCC are described as higher than in HNSCC. IT is constantly shifting into earlier disease stages which confronts the surgeon with immunotherapeutically pre-treated patients. It is therefore becoming increasingly difficult to assess which patients with symptomatic tumor disease and a lack of curative surgical option might benefit from salvage surgery. Case presentations: The following 6 cases describe therapeutic decision-making regarding ICI and (salvage) surgery in patients with advanced stage HNSCC or CSCC. Cases A and B focus on neoadjuvant ICI followed by salvage surgery. In Cases C and D salvage surgery was performed after short-term stabilization with partial response to ICI. The last two cases (Cases E and F) address the surgical approach after failure of ICI. All cases are discussed in the context of the current study landscape and with focus on individual decision-making. For better understanding, a timetable of the clinical course is given for each case. Conclusions: ICI is rapidly expanding its frontiers into the neoadjuvant setting, frequently confronting the surgeon with heavily pretreated patients. Salvage surgery is a viable therapeutic concept despite the rise of systemic treatment options. Decision-making on surgical intervention in case of a salvage surgery remains an individual choice. For neoadjuvant ICI monitoring regarding pathological tumor response or tumor necrosis rate, we suggest correlation between the initial biopsy and the definite tumor resectate in order to increase its significance as a surrogate marker. Scheduling of neoadjuvant ICI should be further investigated, as recent studies indicate better outcomes with shorter time frames.

Differences and Similarities in the Pattern of Early Metabolic and Morphologic Response after Induction Chemo-Immunotherapy versus Induction Chemotherapy Alone in Locally Advanced Squamous Cell Head and Neck Cancer.

Background: In head and neck cancer patients, parameters of metabolic and morphologic response of the tumor to single-cycle induction chemotherapy (IC) with docetaxel, cis- or carboplatin are used to decide the further course of treatment. This study investigated the effect of adding a double immune checkpoint blockade (DICB) of tremelimumab and durvalumab to IC on imaging parameters and their significance with regard to tumor cell remission. Methods: Response variables of 53 patients treated with IC+DICB (ICIT) were compared with those of 104 who received IC alone. Three weeks after one cycle, pathologic and, in some cases, clinical and endoscopic primary tumor responses were evaluated and correlated with a change in 18F-FDG PET and CT/MRI-based maximum-standardized uptake values (SUVmax) before (SUVmaxpre), after treatment (SUVmaxpost) and residually (resSUVmax in % of SUVmaxpre), and in maximum tumor diameter (Dmax) before (Dmaxpre) and after treatment (Dmaxpost) and residually (resD). Results: Reduction of SUVmax and Dmax occurred in both groups; values were SUVmaxpre: 14.4, SUVmaxpost: 6.6, Dmaxpre: 30 mm and Dmaxpost: 23 mm for ICIT versus SUVmaxpre: 16.5, SUVmaxpost: 6.4, Dmaxpre: 21 mm, and Dmaxpost: 16 mm for IC alone (all p < 0.05). ResSUVmax was the best predictor of complete response (IC: AUC: 0.77; ICIT: AUC: 0.76). Metabolic responders with resSUVmax ≤ 40% tended to have a higher rate of CR to ICIT (88%; n = 15/17) than to IC (65%; n = 30/46; p = 0.11). Of the metabolic nonresponders (resSUVmax > 80%), 33% (n = 5/15) achieved a clinical CR to ICIT versus 6% (n = 1/15) to IC (p = 0.01). Conclusions: ICIT and IC quickly induce a response and 18F-FDG PET is the more accurate modality for identifying complete remission. The rate of discrepant response, i.e., pCR with metabolic nonresponse after ICIT was >30%.

Definition of a new blood cell count score for early survival prediction for non-small cell lung cancer patients treated with atezolizumab: Integrated analysis of four multicenter clinical trials.

Importance: Blood cell count test (BCT) is a robust method that provides direct quantification of various types of immune cells to reveal the immune landscape to predict atezolizumab treatment outcomes for clinicians to decide the next phase of treatment. Objective: This study aims to define a new BCTscore model to predict atezolizumab treatment benefits in non-small lung cell cancer (NSCLC) patients. Design Setting and Participants: This study analyzed four international, multicenter clinical trials (OAK, BIRCH, POPLAR, and FIR trials) to conduct post-hoc analyses of NSCLC patients undergoing atezolizumab (anti-PD-L1) single-agent treatment (n = 1,479) or docetaxel single-agent treatment (n = 707). BCT was conducted at three time points: pre-treatment (T1), the first day of treatment cycle 3 (T2), and first day of treatment cycle 5 (T3). Univariate and multivariate Cox regression analyses were conducted to identify early BCT biomarkers to predict atezolizumab treatment outcomes in NSCLC patients. Main Outcomes and Measures: Overall survival (OS) was used as the primary end point, whereas progression-free survival (PFS) according to Response Evaluation Criteria in Solid Tumors (RECIST), clinical benefit (CB), and objective response rate (ORR) were used as secondary end points. Results: The BCT biomarkers of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) at time point T3 and neutrophil-to-monocyte ratio (NMR) at time point T2 with absolute cutoff values of NLR_T3 = 5, PLR_T3 = 180, and NMR_T2 = 6 were identified as strong predictive biomarkers for atezolizumab (Ate)-treated NSCLC patients in comparison with docetaxel (Dtx)-treated patients regarding OS (BCTscore low risk: HR Ate vs. Dtx = 1.54 (95% CI: 1.04-2.27), P = 0.031; high risk: HR Ate vs. Dtx = 0.84 (95% CI: 0.62-1.12), P = 0.235). The identified BCTscore model showed better OS AUC in the OAK (AUC12month = 0.696), BIRCH (AUC12month = 0.672) and POPLAR+FIR studies (AUC12month = 0.727) than that of each of the three single BCT biomarkers. Conclusion and Relevance: The BCTscore model is a valid predictive and prognostic biomarker for early survival prediction in atezolizumab-treated NSCLC patients.