Protocol of the study: Multilevel community-based mental health intervention to address structural inequities and adverse disparate consequences of COVID-19 pandemic on Latinx Immigrants and African refugees.

The NIMH-funded Multilevel Community-Based Mental Health Intervention to Address Structural Inequities and Adverse Disparate Consequences of COVID-19 Pandemic on Latinx Immigrants and African Refugees study aims to advance the science of multilevel interventions to reduce the disparate, adverse mental health, behavioral, and socioeconomic consequences of the COVID-19 pandemic that are a result of complex interactions between underlying structural inequities and barriers to health care. The study tests three nested levels of intervention: 1) an efficacious 4-month advocacy and mutual learning model (Refugee and Immigrant Well-being Project, RIWP); 2) engagement with community-based organizations (CBOs); and 3) structural policy changes enacted in response to the pandemic. This community-based participatory research (CBPR) study builds on long-standing collaboration with five CBOs. By including 240 Latinx immigrants and 60 African refugees recruited from CBO partners who are randomly assigned to treatment-as-usual CBO involvement or the RIWP intervention and a comparison group comprised of a random sample of 300 Latinx immigrants, this mixed methods longitudinal waitlist control group design study with seven time points over 36 months tests the effectiveness of the RIWP intervention and engagement with CBOs to reduce psychological distress, daily stressors, and economic precarity and increase protective factors (social support, access to resources, English proficiency, cultural connectedness). The study also tests the ability of the RIWP intervention and engagement with CBOs to increase access to the direct benefits of structural interventions. This paper reports on the theoretical basis, design, qualitative and quantitative analysis plan, and power for the study.

Measuring culturally and contextually specific distress among Afghan, Iraqi, and Great Lakes African refugees.

Culturally and contextually valid measurement of psychological distress is critical, given the increasing numbers of forcibly displaced people and transnational migration. This study replicates an inductive process that elicited culturally specific expressions, understandings, and idioms of distress among Afghans to develop culturally specific measures of distress for Great Lakes Africans and Iraqis and expands this methodology to include a focus on the contexts of refugees resettled in the United States. To create the measures, we adapted Miller et al.'s (2006) model for the Afghan Symptom Checklist (ASCL) and conducted 18 semistructured qualitative interviews that attended to refugees' multiple settings; the impact of potentially traumatic events initially and postresettlement; and the experiences and impact of resettlement stressors. We tested the newly developed measures and existing ASCL with 280 recently resettled refugees (< 3 years) from Afghanistan, the Great Lakes region of Africa, and Iraq to assess factor structure, reliability, and construct validity. We successfully replicated and adapted a process for creating culturally specific measures of distress to create reliable and valid scales that consider culturally and contextually specific distress among several groups of forcibly displaced people. Our results highlight the salience of individuals' social contexts and how they are manifested as idioms of distress, bringing together two key areas of research: the social construction of mental health and social determinants of mental health. These findings have implications for improving measurement of psychological distress and for developing multilevel interventions that are culturally resonant and address factors beyond the individual level. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Soil microbiome indicators can predict crop growth response to large-scale inoculation with arbuscular mycorrhizal fungi.

Alternative solutions to mineral fertilizers and pesticides that reduce the environmental impact of agriculture are urgently needed. Arbuscular mycorrhizal fungi (AMF) can enhance plant nutrient uptake and reduce plant stress; yet, large-scale field inoculation trials with AMF are missing, and so far, results remain unpredictable. We conducted on-farm experiments in 54 fields in Switzerland and quantified the effects on maize growth. Growth response to AMF inoculation was highly variable, ranging from -12% to +40%. With few soil parameters and mainly soil microbiome indicators, we could successfully predict 86% of the variation in plant growth response to inoculation. The abundance of pathogenic fungi, rather than nutrient availability, best predicted (33%) AMF inoculation success. Our results indicate that soil microbiome indicators offer a sustainable biotechnological perspective to predict inoculation success at the beginning of the growing season. This predictability increases the profitability of microbiome engineering as a tool for sustainable agricultural management.

Comparative computational analysis to distinguish mesenchymal stem cells from fibroblasts.

Introduction: Mesenchymal stem cells (MSCs) are considered to be the most promising stem cell type for cell-based therapies in regenerative medicine. Based on their potential to home to diseased body sites following a therapeutically application, these cells could (i) differentiate then into organ-specific cell types to locally restore injured cells or, most prominently, (ii) foster tissue regeneration including immune modulations more indirectly by secretion of protective growth factors and cytokines. As tissue-resident stem cells of mesenchymal origin, these cells are morphologically and even molecularly- at least concerning the classical marker genes- indistinguishable from similar lineage cells, particularly fibroblasts. Methods: Here we used microarray-based gene expression and global DNA methylation analyses as well as accompanying computational tools in order to specify differences between MSCs and fibroblasts, to further unravel potential identity genes and to highlight MSC signaling pathways with regard to their trophic and immunosuppressive action. Results: We identified 1352 differentially expressed genes, of which in the MSCs there is a strong signature for e.g., KRAS signaling, known to play essential role in stemness maintenance, regulation of coagulation and complement being decisive for resolving inflammatory processes, as well as of wound healing particularly important for their regenerative capacity. Genes upregulated in fibroblasts addressed predominately transcription and biosynthetic processes and mapped morphological features of the tissue. Concerning the cellular identity, we specified the already known HOX code for MSCs, established a potential HOX code for fibroblasts, and linked certain HOX genes to functional cell-type-specific properties. Accompanied methylation profiles revealed numerous regions, especially in HOX genes, being differentially methylated, which might provide additional biomarker potential. Discussion: Conclusively, transcriptomic together with epigenetic signatures can be successfully be used for the definition (cellular identity) of MSCs versus fibroblasts as well as for the determination of the superior functional properties of MSCs, such as their immunomodulatory potential.

The impact of postresettlement stressors and access to health care on health outcomes in recently resettled refugees in the United States.

This mixed-methods study examines mechanisms connecting the deployment of economic, social, and health care resources to emotional distress and physical health outcomes. Examining such mechanisms is critical for informing strategies, policies, and other interventions for reducing health disparities and improving refugee health in the United States and other resettlement contexts. Data for this study were collected as part of a randomized control trial in a mid-sized city in the Southwestern United States. Two-hundred ninety recently resettled (< 3 years) refugee adults from 143 households were enrolled in the study (36.2% Afghan, 32.8% Iraqi/Syrian, and 31.0% Great Lakes African; 52% women). Qualitative interview data were collected via semistructured interviews. A longitudinal structural equation path model of quantitative data from three time points over 12 months tested hypotheses that emerged from qualitative findings. In semistructured interviews, refugees in the United States (a) attributed the development of worse or new physical health problems to postresettlement stressors related to financial instability and limited social support that contributed to their emotional distress and (b) reported several barriers to accessing health care in the United States, including insufficient knowledge of health care resources, inadequate patient-provider communication, and navigating complex American health insurance systems, all of which exacerbated their physical health problems. Guided by these qualitative findings, longitudinal quantitative data revealed that: (a) postmigration stressors were associated with emotional distress and poor self-reported physical health, (b) emotional distress mediated the association between postmigration stressors and global health satisfaction, and (c) emotional distress was negatively associated with global health satisfaction. Findings document stressors refugees experience in the context of the unique environment created by the American health care system and how these stressors contribute to poor physical health through increased emotional distress. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Effect of polishing and denture cleansers on the surface roughness of new-generation denture base materials and their color change after cleansing.

PURPOSE: To evaluate the effect of polishing and denture cleansers on the surface roughness (Ra ) of new-generation denture base materials that are additively, subtractively, and conventionally fabricated, while also assessing their color change after cleansing. MATERIAL AND METHODS: One hundred and fifty disk-shaped specimens (Ø10 × 2 mm) were prepared from five denture base materials (one subtractively manufactured nanographene-reinforced prepolymerized polymethylmethacrylate (PMMA) (SM-GC), one subtractively manufactured prepolymerized PMMA (SM-PM), two additively manufactured denture base resins (AM-DT and AM-ND), and one heat-polymerized PMMA (CV) (n = 30). The Ra of the specimens was measured before and after conventional laboratory polishing, while color coordinates were measured after polishing. Specimens were then divided into three subgroups based on the denture cleanser: distilled water, 1% sodium hypochlorite (NaOCl), and effervescent tablet (n = 10). The Ra and color coordinates were remeasured after nine cleansing cycles over a period of 20 days. The CIEDE2000 formula was used to calculate the color differences (ΔE00 ). Two-way analysis of variance (ANOVA) was used to analyze the Ra values before (n = 30) and after (n = 10) cleansing, while repeated measures ANOVA was used to analyze the Ra of material-time point pairs within each denture cleanser (n = 10). ΔE00 data after denture cleansing was also analyzed by using two-way ANOVA (n = 10) (α = 0.05). RESULTS: Before polishing, Ra varied significantly among the materials. SM-GC and SM-PM had the lowest and AM-ND the highest Ra values (P < 0.001). Polishing significantly reduced Ra of all materials (P < 0.001), and after polishing, Ra differences among materials were nonsignificant (P ≥ 0.072). Regardless of the denture cleanser, the Ra of AM-DT, AM-ND, and CV was the highest before polishing when different time points were considered (P < 0.001). After cleansing, AM-ND had the highest Ra of all the materials, regardless of the cleanser (P ≤ 0.017). AM-DT had higher Ra than SM-PM when distilled water (P = 0.040) and higher Ra than SM-GC, SM-PM, and CV when NaOCl was used (P < 0.001). The type of cleanser significantly influenced the Ra of AM-DT, AM-ND, and CV. For AM-DT, NaOCl led to the highest Ra and the tablet led to the lowest Ra (P ≤ 0.042), while for AM-ND, distilled water led to the lowest Ra (P ≤ 0.024). For CV, the tablet led to lower Ra than distilled water (P = 0.009). Color change varied among the materials. When distilled water was used, SM-GC had higher ΔE00 than SM-PM and AM-DT (P ≤ 0.034). When NaOCl was used, AM-ND had higher ΔE00 than SM-GC, SM-PM, and AM-DT, while CV and SM-GC had higher ΔE00 than SM-PM and AM-DT (P ≤ 0.039). Finally, when the tablet was used, AM-ND and CV had the highest ΔE00 , while AM-DT had lower ΔE00 than SM-GC (P ≤ 0.015). CONCLUSIONS: The tested materials had unacceptable surface roughness (>0.2 µm) before polishing. Roughness decreased significantly after polishing (<0.2 µm). Denture cleansers did not significantly affect the surface roughness of the materials, and roughness remained clinically acceptable after cleansing (<0.2 µm). Considering previously reported color thresholds, AM-ND and CV had unacceptable color change regardless of the denture cleanser, and the effervescent tablet led to perceptible, but acceptable color change for SM-GC, SM-PM, and AM-DT.

The ROCEEH Out of Africa Database (ROAD): A large-scale research database serves as an indispensable tool for human evolutionary studies.

Large scale databases are critical for helping scientists decipher long-term patterns in human evolution. This paper describes the conception and development of such a research database and illustrates how big data can be harnessed to formulate new ideas about the past. The Role of Culture in Early Expansions of Humans (ROCEEH) is a transdisciplinary research center whose aim is to study the origins of culture and the multifaceted aspects of human expansions across Africa and Eurasia over the last three million years. To support its research, the ROCEEH team developed an online tool named the ROCEEH Out of Africa Database (ROAD) and implemented its web-based applications. ROAD integrates geographical data as well as archaeological, paleoanthropological, paleontological and paleobotanical content within a robust chronological framework. In fact, a unique feature of ROAD is its ability to dynamically link scientific data both spatially and temporally, thereby allowing its reuse in ways that were not originally conceived. The data stem from published sources spanning the last 150 years, including those generated by the research team. Descriptions of these data rely on the development of a standardized vocabulary and profit from online explanations of each table and attribute. By synthesizing legacy data, ROAD facilitates the reuse of heritage data in novel ways. Database queries yield structured information in a variety of interoperable formats. By visualizing data on maps, users can explore this vast dataset and develop their own theories. By downloading data, users can conduct further quantitative analyses, for example with Geographic Information Systems, modeling programs and artificial intelligence. In this paper, we demonstrate the innovative nature of ROAD and show how it helps scientists studying human evolution to access datasets from different fields, thereby connecting the social and natural sciences. Because it permits the reuse of "old" data in new ways, ROAD is now an indispensable tool for researchers of human evolution and paleogeography.

Planned adaptation and implementation of the Community Guide recommendations for increasing physical activity in rural community settings: A qualitative study.

Background: The purpose of this paper is to report on the implementation of an evidence-based model, VIVA, which was developed to translate physical activity (PA) recommendations to rural environments and was scaled-up to 12 rural communities across New Mexico. Our longitudinal qualitative research describes processes of planned adaptation in the rural context with an exploration of inner and outer context adaptations that consider important implementation constructs including leadership, partnership and collaboration. Materials & methods: An enhanced version of the RE-AIM framework was used to formulate community-level engagement and process questions essential to implementation science. Qualitative methods, using a thematic approach that included both inductive and deductive coding with attention to processes, was used to explore adaptation at the community level. Data included semi-structured interviews with 17 community leaders at baseline and 10 at follow-up, fieldnotes, and technical assistance tracking forms. Analysis was conducted with NVivo qualitative data analysis software. Results: Analysis demonstrated how planned adaptation of the implementation model was critical to dissemination in rural communities. Understanding and adapting to local context-including geography, culture, economics-is essential for implementation. Inner context constructs, recognized as important across implementation models, including leadership, partnerships and political engagement were found to be key to implementation success. Moreover, we provide concrete examples of the range and complexity of these issues in rural communities, and how these shaped implementation uptake and success. Discussion: Studying processes of planned adaptation in rural contexts will further implementation science efforts to move evidence into practice. It is essential to incorporate planned adaptation to local, community contexts to create models which are simple to encourage adoption, are evidence-based, and are adaptable to local conditions without compromising the integrity of the evidence-based model.

DNA-methylation and genomic copy number in primary tumors and corresponding lymph node metastases in prostate cancer from patients with low and high Gleason score.

Purpose: In prostate cancer, the indication to irradiate the pelvic lymphatic pathways in clinical node-negative patients is solely based on clinical nomograms. To define biological risk patterns of lymphatic spread, we studied DNA-methylation and genomic copy number in primary tumors and corresponding lymph nodes metastases. Methods/Patients: DNA-methylation and genomic copy number profiles of primary tumors (PT) and paired synchronous lymph node metastases (LN) from Gleason Score (GS)-6/7a (n = 20 LN-positive, n = 20 LN-negative) and GS-9/10 patients (LN-positive n = 20) after prostatectomy and lymphonodectomy were analyzed. Results: GS-6/7a pN0 PTs and GS-6/7a pN1 PTs differed in histone H3K27me3/H3K9me3 mediated methylation. PTs compared to LNs, in both, GS-6/7a pN1 and GS-9/10 pN1 patients showed large differences in DNA-methylation mediated by histones H3K4me1/2, in addition to copy number changes of chromosomal regions 11q13.1, 14q11.2 and 15q26.1. Between GS-6/7a pN1 and GS-9/10 pN1 patients, methylation levels differed more when comparing LNs than PTs. 16q21-22.1 was specifically lost in GS-9/10 pN0 PTs. Immune system-related pathways characterized the differences between PTs and LNs in both GS-6/7a pN1 and GS-9/10 pN1 patients. Comparing PTs and LKs between GS-6/7a pN1 and GS-9/10 pN1 patients revealed altered transmembrane and G-protein-coupled receptor signaling. Conclusions: Our data suggest that progression of prostate cancer, including lymphatic spread, is associated with histone-mediated DNA-methylation and we hypothesize a methylation signature predicting lymphatic spread in GS-6/7a patients from primary tumors. Lymphatic spread in GS-6/7a patients, flanked by DNA-methylation and CNA alterations, appears to be more complex than in GS-9/10 patients, in whom the primary tumors already appear to bear lymph node metastasis-enabling alterations.

Systematic in vitro analysis of therapy resistance in glioblastoma cell lines by integration of clonogenic survival data with multi-level molecular data.

Despite intensive basic scientific, translational, and clinical efforts in the last decades, glioblastoma remains a devastating disease with a highly dismal prognosis. Apart from the implementation of temozolomide into the clinical routine, novel treatment approaches have largely failed, emphasizing the need for systematic examination of glioblastoma therapy resistance in order to identify major drivers and thus, potential vulnerabilities for therapeutic intervention. Recently, we provided proof-of-concept for the systematic identification of combined modality radiochemotherapy treatment vulnerabilities via integration of clonogenic survival data upon radio(chemo)therapy with low-density transcriptomic profiling data in a panel of established human glioblastoma cell lines. Here, we expand this approach to multiple molecular levels, including genomic copy number, spectral karyotyping, DNA methylation, and transcriptome data. Correlation of transcriptome data with inherent therapy resistance on the single gene level yielded several candidates that were so far underappreciated in this context and for which clinically approved drugs are readily available, such as the androgen receptor (AR). Gene set enrichment analyses confirmed these results, and identified additional gene sets, including reactive oxygen species detoxification, mammalian target of rapamycin complex 1 (MTORC1) signaling, and ferroptosis/autophagy-related regulatory circuits to be associated with inherent therapy resistance in glioblastoma cells. To identify pharmacologically accessible genes within those gene sets, leading edge analyses were performed yielding candidates with functions in thioredoxin/peroxiredoxin metabolism, glutathione synthesis, chaperoning of proteins, prolyl hydroxylation, proteasome function, and DNA synthesis/repair. Our study thus confirms previously nominated targets for mechanism-based multi-modal glioblastoma therapy, provides proof-of-concept for this workflow of multi-level data integration, and identifies novel candidates for which pharmacological inhibitors are readily available and whose targeting in combination with radio(chemo)therapy deserves further examination. In addition, our study also reveals that the presented workflow requires mRNA expression data, rather than genomic copy number or DNA methylation data, since no stringent correlation between these data levels could be observed. Finally, the data sets generated in the present study, including functional and multi-level molecular data of commonly used glioblastoma cell lines, represent a valuable toolbox for other researchers in the field of glioblastoma therapy resistance.

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

PURPOSE: Identification of molecularly-defined cancer subgroups and targeting tumor-specific vulnerabilities have a strong potential to improve treatment response and patient outcomes but remain an unmet challenge of high clinical relevance, especially in head and neck squamous cell carcinoma (HNSC). EXPERIMENTAL DESIGN: We established a UCHL1-related gene set to identify and molecularly characterize a UCHL1-related subgroup within TCGA-HNSC by integrative analysis of multi-omics data. An extreme gradient boosting model was trained on TCGA-HNSC based on GSVA scores for gene sets of the MSigDB to robustly predict UCHL1-related cancers in other solid tumors and cancer cell lines derived thereof. Potential vulnerabilities of UCHL1-related cancer cells were elucidated by an in-silico drug screening approach. RESULTS: We established a 497-gene set, which stratified the TCGA-HNSC cohort into distinct subgroups with a UCHL1-related or other phenotype. UCHL1-related HNSC were characterized by higher frequencies of genomic alterations, which was also evident for UCHL1-related cancers of other solid tumors predicted by the classification model. These data indicated an impaired maintenance of genomic integrity and vulnerability for DNA-damaging treatment, which was supported by a favorable prognosis of UCHL1-related tumors after radiotherapy, and a higher sensitivity of UCHL1-related cancer cells to irradiation or DNA-damaging compounds (e.g., Oxaliplatin). CONCLUSION: Our study established UCHL1-related cancers as a novel subgroup across most solid tumor entities with a unique molecular phenotype and DNA-damaging treatment as a specific vulnerability, which requires further proof-of-concept in pre-clinical models and future clinical trials.

Measuring Latinx/@ immigrant experiences and mental health: Adaptation of discrimination and historical loss scales.

Migration processes encompass uncertainty, discrimination, racism, stigma, social isolation, lack of access to resources, fear of deportation, and family separation, having a critical impact on the health of Latinx/@ immigrants in the United States. It is essential to accurately measure the ways in which social, legal, economic, and political contexts impact mental health. This article discusses adaptation and use of discrimination and historical loss measures in a multilevel community-based advocacy, learning, and social support intervention (Immigrant Well-Being Project) with Latinx/@ immigrants in New Mexico, using participatory research approaches. Participants (n = 52) were recruited through community partner organizations and completed four qualitative and quantitative interviews over a 12-month period. The present analysis draws on the baseline quantitative data. Results show it is possible to adapt standardized measures of discrimination developed to assess the experiences of other racial/ethnic groups; however, the most common responses involved response options added by our research team. For the historical loss instrument, there was a high frequency of "never" answers for many items, suggesting that they were not relevant for participants or did not capture their experiences of loss. As with the discrimination measures, the items we added resonated the most with participants. The contexts of discrimination and loss for Latinx/@ immigrant populations are complex, thus the tools we use to measure these experiences and their impact on health must account for this complexity. This study contributes to these endeavors through involving community members in the conceptualization and measurement of discrimination and historical loss among Latinx/@ immigrants. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

DeepClassPathway: Molecular pathway aware classification using explainable deep learning.

OBJECTIVE: HPV-associated head and neck cancer is correlated with favorable prognosis; however, its underlying biology is not fully understood. We propose an explainable convolutional neural network (CNN) classifier, DeepClassPathway, that predicts HPV-status and allows patient-specific identification of molecular pathways driving classifier decisions. METHODS: The CNN was trained to classify HPV-status on transcriptome data from 264 (13% HPV-positive) and tested on 85 (25% HPV-positive) head and neck squamous carcinoma patients after transformation into 2D-treemaps representing molecular pathways. Grad-CAM saliency was used to quantify pathways contribution to individual CNN decisions. Model stability was assessed by shuffling pathways within 2D-images. RESULTS: The classification performance of the CNN-ensembles achieved ROC-AUC/PR-AUC of 0.96/0.90 for all treemap variants. Quantification of the averaged pathway saliency heatmaps consistently identified KRAS, spermatogenesis, bile acid metabolism, and inflammation signaling pathways as the four most informative for classifying HPV-positive patients and MYC targets, epithelial-mesenchymal transition, and protein secretion pathways for HPV-negative patients. CONCLUSION: We have developed and applied an explainable CNN classification approach to transcriptome data from an oncology cohort with typical sample size that allows classification while accounting for the importance of molecular pathways in individual-level decisions.

A transcriptomic map of EGFR-induced epithelial-to-mesenchymal transition identifies prognostic and therapeutic targets for head and neck cancer.

BACKGROUND: Epidermal growth factor receptor (EGFR) is both a driver oncogene and a therapeutic target in advanced head and neck squamous cell carcinoma (HNSCC). However, response to EGFR treatment is inconsistent and lacks markers for treatment prediction. This study investigated EGFR-induced epithelial-to-mesenchymal transition (EMT) as a central parameter in tumor progression and identified novel prognostic and therapeutic targets, and a candidate predictive marker for EGFR therapy response. METHODS: Transcriptomic profiles were analyzed by RNA sequencing (RNA-seq) following EGFR-mediated EMT in responsive human HNSCC cell lines. Exclusive genes were extracted via differentially expressed genes (DEGs) and a risk score was determined through forward feature selection and Cox regression models in HNSCC cohorts. Functional characterization of selected prognostic genes was conducted in 2D and 3D cellular models, and findings were validated by immunohistochemistry in primary HNSCC. RESULTS: An EGFR-mediated EMT gene signature composed of n = 171 genes was identified in responsive cell lines and transferred to the TCGA-HNSCC cohort. A 5-gene risk score comprising DDIT4, FADD, ITGB4, NCEH1, and TIMP1 prognosticated overall survival (OS) in TCGA and was confirmed in independent HNSCC cohorts. The EGFR-mediated EMT signature was distinct from EMT hallmark and partial EMT (pEMT) meta-programs with a differing enrichment pattern in single malignant cells. Molecular characterization showed that ITGB4 was upregulated in primary tumors and metastases compared to normal mucosa and correlated with EGFR/MAPK activity in tumor bulk and single malignant cells. Preferential localization of ITGB4 together with its ligand laminin 5 at tumor-stroma interfaces correlated with increased tumor budding in primary HNSCC tissue sections. In vitro, ITGB4 knock-down reduced EGFR-mediated migration and invasion and ITGB4-antagonizing antibody ASC8 impaired 2D and 3D invasion. Furthermore, a logistic regression model defined ITGB4 as a predictive marker of progression-free survival in response to Cetuximab in recurrent metastatic HNSCC patients. CONCLUSIONS: EGFR-mediated EMT conveyed through MAPK activation contributes to HNSCC progression upon induction of migration and invasion. A 5-gene risk score based on a novel EGFR-mediated EMT signature prognosticated survival of HNSCC patients and determined ITGB4 as potential therapeutic and predictive target in patients with strong EGFR-mediated EMT.

Integration of p16/HPV DNA Status with a 24-miRNA-Defined Molecular Phenotype Improves Clinically Relevant Stratification of Head and Neck Cancer Patients.

Human papillomavirus (HPV)-driven head and neck squamous cell carcinomas (HNSCC) generally have a more favourable prognosis. We hypothesized that HPV-associated HNSCC may be identified by an miRNA-signature according to their specific molecular pathogenesis, and be characterized by a unique transcriptome compared to HPV-negative HNSCC. We performed miRNA expression profiling of two p16/HPV DNA characterized HNSCC cohorts of patients treated by adjuvant radio(chemo)therapy (multicentre DKTK-ROG n = 128, single-centre LMU-KKG n = 101). A linear model predicting HPV status built in DKTK-ROG using lasso-regression was tested in LMU-KKG. LMU-KKG tumours (n = 30) were transcriptome profiled for differential gene expression and miRNA-integration. A 24-miRNA signature predicted HPV-status with 94.53% accuracy (AUC: 0.99) in DKTK-ROG, and 86.14% (AUC: 0.86) in LMU-KKG. The prognostic values of 24-miRNA- and p16/HPV DNA status were comparable. Combining p16/HPV DNA and 24-miRNA status allowed patient sub-stratification and identification of an HPV-associated patient subgroup with impaired overall survival. HPV-positive tumours showed downregulated MAPK, Estrogen, EGFR, TGFbeta, WNT signaling activity. miRNA-mRNA integration revealed HPV-specific signaling pathway regulation, including PD-L1 expression/PD-1 checkpoint pathway in cancer in HPV-associated HNSCC. Integration of clinically established p16/HPV DNA with 24-miRNA signature status improved clinically relevant risk stratification, which might be considered for future clinical decision-making with respect to treatment de-escalation in HPV-associated HNSCC.

Simultaneous metabolite MALDI-MSI, whole exome and transcriptome analysis from formalin-fixed paraffin-embedded tissue sections.

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) allows spatial analysis of proteins, metabolites, or small molecules from tissue sections. Here, we present the simultaneous generation and analysis of MALDI-MSI, whole-exome sequencing (WES), and RNA-sequencing data from the same formalin-fixed paraffin-embedded (FFPE) tissue sections. Genomic DNA and total RNA were extracted from (i) untreated, (ii) hematoxylin-eosin (HE) stained, and (iii) MALDI-MSI-analyzed FFPE tissue sections from three head and neck squamous cell carcinomas. MALDI-MSI data were generated by a time-of-flight analyzer prior to preprocessing and visualization. WES data were generated using a low-input protocol followed by detection of single-nucleotide variants (SNVs), tumor mutational burden, and mutational signatures. The transcriptome was determined using 3'-RNA sequencing and was examined for similarities and differences between processing stages. All data met the commonly accepted quality criteria. Besides SNVs commonly identified between differently processed tissues, FFPE-typical artifactual variants were detected. Tumor mutational burden was in the same range for tissues from the same patient and mutational signatures were highly overlapping. Transcriptome profiles showed high levels of correlation. Our data demonstrate that simultaneous molecular profiling of MALDI-MSI-processed FFPE tissue sections at the transcriptome and exome levels is feasible and reliable.

Analysis of genetic variants of frequently mutated genes in human papillomavirus-negative primary head and neck squamous cell carcinoma, resection margins, local recurrences and corresponding circulating cell-free DNA.

BACKGROUND: Head and neck squamous cell carcinoma remains a substantial burden to global health. Despite evolving therapies, 5-year survival is <50% and unlike in other cancers, reliable molecular biomarkers to guide treatment do not exist. METHODS: We performed targeted panel next-generation sequencing to analyse somatic variants from primary and recurrent tumour tissue, corresponding resection margins and cell-free DNA from intra-operatively collected plasma samples from eight patients with human papillomavirus-negative head and neck squamous cell carcinoma. Patients were primarily treated with curative-intent surgery and received subsequent adjuvant treatment. RESULTS: The most frequently mutated gene was TP53. Other mutated genes included NOTCH1, NF1 and CDKN2A among others. A total of 20.8% of variants were shared between primary tumour and resection margin. Out of all the variants detected, 37.5% were shared between cell-free DNA and primary tumour, whereas 12.5% were commonly found in cell-free DNA, primary tumour and resection margin. Mutational profiling was able to distinguish between a locoregional recurrence and a second primary tumour by identifying a different TP53 mutation in the primary tumour compared to the recurrent tumour in addition to private FBXW7 and CTNNB1 mutations. We also identified identical TP53 and PIK3CA mutations in another primary tumour and corresponding recurrence. CONCLUSION: Molecular profiling of cell-free DNA and resection margins has potential applications in clinical practice to guide future treatment decisions.

IL1 Pathway in HPV-Negative HNSCC Cells Is an Indicator of Radioresistance After Photon and Carbon Ion Irradiation Without Functional Involvement.

Background: Treatment of locally advanced HPV-negative head and neck squamous cell carcinoma (HNSCC) with photon radiation is the standard of care but shows only moderate success. Alterations in response toward DNA DSB repair, apoptosis, and senescence are underlying determinants of radioresistance in the tumor cells. Recently, senescence and the associated secretory phenotype (SASP) came into the focus of research and raised the need to identify the tumor-promoting molecular mechanisms of the SASP. The aim of this project was to unravel more of this process and to understand the impact of the IL1 pathway, which plays a major role in SASP. The studies were performed for photon and 12C-ion irradiation, which strongly vary in their effect on radioresistance. Materials and Methods: A panel of five HPV-negative HNSCC cell lines was treated with photon and 12C-ion irradiation and examined for clonogenic survival, DNA DSB repair, and senescence. SASP and IL1 gene expressions were determined by RNA sequencing and activation of the IL1 pathway by ELISA. A functional impact of IL1A and IL1B was examined by specific siRNA knockdown. Results: Cell killing and residual DSBs were higher after 12C-ion than after photon irradiation. 12C-ion induced more senescence with a significant correlation with cell survival. The impact on radioresistance appears to be less than after photon irradiation. The expression of SASP-related genes and the IL1 pathway are strongly induced by both types of irradiation and correlate with radioresistance and senescence, especially IL1A and IL1B which exhibit excellent associations. Surprisingly, knockdown of IL1A and IL1B revealed that the IL1 pathway is functionally not involved in radioresistance, DSB repair, or induction of senescence. Conclusions: IL1A and IL1B are excellent indicators of cellular radioresistance and senescence in HNSCC cells without functional involvement in these processes. Clearly more research is needed to understand the molecular mechanisms of senescence and SASP and its impact on radioresistance.

Integrative analysis of therapy resistance and transcriptomic profiling data in glioblastoma cells identifies sensitization vulnerabilities for combined modality radiochemotherapy.

BACKGROUND: Inherent resistance to radio/chemotherapy is one of the major reasons for early recurrence, treatment failure, and dismal prognosis of glioblastoma. Thus, the identification of resistance driving regulators as prognostic and/or predictive markers as well as potential vulnerabilities for combined modality treatment approaches is of pivotal importance. METHODS: We performed an integrative analysis of treatment resistance and DNA damage response regulator expression in a panel of human glioblastoma cell lines. mRNA expression levels of 38 DNA damage response regulators were analyzed by qRT-PCR. Inherent resistance to radiotherapy (single-shot and fractionated mode) and/or temozolomide treatment was assessed by clonogenic survival assays. Resistance scores were extracted by dimensionality reduction and subjected to correlation analyses with the mRNA expression data. Top-hit candidates with positive correlation coefficients were validated by pharmacological inhibition in clonogenic survival assays and DNA repair analyses via residual γH2AX/53BP1-foci staining. RESULTS: Inherent resistance to single-shot and similarly also to fractionated radiotherapy showed strong positive correlations with mRNA expression levels of known vulnerabilities of GBM, including PARP1, NBN, and BLM, as well as ATR and LIG4-two so far underestimated targets. Inhibition of ATR by AZD-6738 resulted in robust and dose-dependent radiosensitization of glioblastoma cells, whereas LIG4 inhibition by L189 had no noticeable impact. Resistance against temozolomide showed strong positive correlation with mRNA expression levels of MGMT as to be expected. Interestingly, it also correlated with mRNA expression levels of ATM, suggesting a potential role of ATM in the context of temozolomide resistance in glioblastoma cells. ATM inhibition exhibited slight sensitization effects towards temozolomide treatment in MGMT low expressing glioblastoma cells, thus encouraging further characterization. CONCLUSIONS: Here, we describe a systematic approach integrating clonogenic survival data with mRNA expression data of DNA damage response regulators in human glioblastoma cell lines to identify markers of inherent therapy resistance and potential vulnerabilities for targeted sensitization. Our results provide proof-of-concept for the feasibility of this approach, including its limitations. We consider this strategy to be adaptable to other cancer entities as well as other molecular data qualities, and its upscaling potential in terms of model systems and observational data levels deserves further investigation.