Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, with a disease recurrence rate of around 20%. Lymphoid formations, which occur in nonlymphoid tissues during chronic inflammatory, infectious, and immune responses, have been linked with tumor suppression. Lymphoid aggregates potentially enhance the body's antitumor response, offering an avenue for attracting tumor-infiltrating lymphocytes and fostering their coordination. Increasing evidence highlights the role of lymphoid aggregate density in managing tumor invasion and metastasis, with a favorable impact noted on overall and disease-free survival (DFS) across various cancer types. In this study, we present a machine vision model to predict recurrence in different histologic subtypes of PTC using measurements related to peritumoral lymphoid aggregate density. We demonstrated that quantifying peritumoral lymphocytic presence not only is associated with better prognosis but also, along with tumor-infiltrating lymphocytes within the tumor, adds additional prognostic value in the absence of well-known second mutations including TERT. Annotations of peritumoral lymphoid aggregates on 171 well-differentiated PTCs in the Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) data set were used to train a deep-learning model to predict regions of lymphoid aggregates across the entire tissue. The fractional area of the tissue regions covered by these lymphocytes was dichotomized to determine the following 2 risk groups: a significant and low density of peritumoral lymphocytes. DFS prognosticated using these risk groups via the Kaplan-Meier analysis revealed a hazard ratio (HR) of 2.51 (95% CI: 2.36, 2.66), tested on 170 new patients also from the TCGA-THCA data set. The prognostic performance of peritumoral lymphocyte aggregate density was compared against the univariate Kaplan-Meier analysis of DFS using the fractional area of intratumoral lymphocytes within the primary tumor with an HR of 2.04 (95% CI: 1.89, 2.19). Combining the lymphocyte features in and around the tumor yielded a statistically significant improvement in prognostic performance (HR, 3.17 [95% CI: 3.02, 3.32]) on training and were independently evaluated against 62 patients outside TCGA-THCA with an HR of 2.44 (95% CI: 2.19, 2.69). Multivariable Cox regression analysis on the validation set revealed that the density of peritumoral and intratumoral lymphocytes was prognostic independent of histologic subtype with a concordance index of 0.815.

Leptin (LEP) is implicated in the pathogenesis of polycystic ovary syndrome (PCOS). This study investigates the mechanism of LEP in PCOS. The baseline information of 80 PCOS patients and matched controls was analyzed, with serum and follicular fluid (FF) LEP and LEP receptor (LEPR) levels, telomerase activity, and relative telomere length (TL) measured. The correlation of FF LEP with telomerase activity and TL was analyzed. The viability and apoptosis of KGN cells (the ovarian granulosa cells) treated with gradient LEP were assessed. LEP-LEPR interaction was examined. LEPR, c-MYC, and TERT levels and c-MYC protein expression in the TERT promoter region were determined. Nuclear c-MYC translocation was detected. LEP was upregulated in sera and FF of PCOS patients. FF LEP positively-correlated with telomerase activity and TL. Low-concentration LEP facilitated KGN cell proliferation and high-concentration LEP dose-dependently suppressed cell proliferation, promoted apoptosis, upregulated LEPR and increased telomerase activity and relative TL. LEP-LEPR interaction upregulated c-MYC and facilitated its nuclear accumulation. c-MYC enrichment in the TERT promoter region upregulated TERT, altering telomerase activity and TL and inducing cell apoptosis. Briefly, LEP/LEPR activate c-MYC, modulate TERT expression, and increase telomerase activity and TL, thus inducing ovarian granulosa cell apoptosis and participating in PCOS.

Sudden death can be the first symptom of cardiac disease, and establishing a precise postmortem diagnosis is crucial for genetic testing and follow-up of relatives. Arrhythmogenic cardiomyopathy (ACM) is a structural cardiomyopathy that can be challenging to diagnose postmortem because of differences in structural findings and propagation of the disease at the time of death. Cases can have minimal or no structural findings and later be diagnosed according to genotype, known as concealed cardiomyopathy. Postmortem diagnosis often lacks clinical information, whereas antemortem diagnosis is based on paraclinical investigations that cannot be performed after death. However, the entire substrate is available, which is unique to postmortem diagnosis and research and can provide valuable insights when adding new methods. Reactive changes in the heart such as myocardial fibrosis and fat are significant findings. The patterns of these changes in various diseases are not yet fully understood and may be limited by sampling material and conventional microscopic diagnostics. We demonstrate an automated pipeline in QuPath for quantifying postmortem picrosirius red cardiac tissue for collagen, residual myocardium, and adipocytes, by integrating Cellpose into a versatile pipeline. This method was developed and tested using cardiac tissues from autopsied individuals. Cases diagnosed with ACM and age-matched controls were used for validation and testing. This approach is free and easy to implement by other research groups using this as a template. This can potentially lead to the development of quantitative diagnostic criteria for postmortem cardiac diseases, eliminating the need to rely on diagnostic criteria from endomyocardial biopsies that are not applicable to postmortem specimens. We propose that this approach serves as a template for creating a more efficient process for evaluating postmortem cardiac measurements in an unbiased manner, particularly for rare cardiac diseases.

CD248 (Endosialin/TEM-1) is upregulated in cancer, including colorectal cancer (CRC), but its exact role in tumor progression remains to be elucidated. Previous studies have shown that the extracellular domain of CD248 mediates the interaction between tumor cells and extracellular matrix proteins and that interfering with this interaction may reduce tumor invasion and migration activities. We have examined the expression of CD248 in 117 human CRC samples by immunohistochemistry and investigated the association with various clinicopathological features, including the occurrence of metastasis intra-tumoral immune cell density, and overall survival. Out of the 117 specimens analyzed, 76.1% (89/117) exhibited CD248-high stromal expression, while 23.1% (28/117) demonstrated CD248-low stromal expression. Interestingly, we detected the presence of a cleaved form of CD248, which appears to accumulate in the stromal extracellular matrix. A higher metastasis rate (lymph node and distant) was observed in the CD248-low group (21/28, 75.0% versus 44/89, 49.4%, p=0.02). In addition, CD248-low tumors had fewer CD163-positive macrophages and FoxP3-positive regulatory T cells (p<0.05) with no significant difference in CD8-positive T-cell infiltration and PD-L1 expression between the groups (p>0.05). Finally, overall survival was lower in CD248-low tumors than in CD248-high tumors, with 5-year survival rates of 35.7% and 57.3%, respectively (p=0.01). In a multivariate analysis, the hazard ratio of CD248-low tumors versus CD248-high tumors was 1.93 (95% confidence interval: 1.09 - 3.40; p=0.02). Our findings suggest that CD248 stromal expression may influence the TME, impacting tumor behavior and prognosis, and can serve as a promising prognostic biomarker in CRC.

Although lymph node structures may be compromised in severe SARS-CoV-2 infection, the extent and parameters of recovery in convalescing patients remain unclear. Therefore, this study aimed to elucidate the nuances of lymphoid structural recovery and their implications for immunological memory in non-human primates infected with SARS-CoV-2. To do so, we utilized imaging-based spatial transcriptomics to delineate immune cell composition and tissue architecture formation in the lung draining lymph nodes during primary infection, convalescence, and reinfection from COVID-19. We noted the establishment of a germinal center with memory B cell differentiation within lymphoid follicles during convalescence accompanied by contrasting transcriptome patterns indicative of the acquisition of follicular helper T cells versus the loss of regulatory T cells. Additionally, repopulation of germinal center-like B cells was observed in the medullary niche with accumulating plasma cells along with enhanced transcriptional expression of B cell activating factor receptor over the course of reinfection. The spatial transcriptome atlas produced herein enhances our understanding of germinal center formation with immune cell dynamics during COVID-19 convalescence and lymphoid structural recovery with transcriptome dynamics following reinfection. These findings have the potential to inform the optimization of vaccine strategies and the development of precise therapeutic interventions in the spatial context.

Accurate whole-cell segmentation is essential in various biomedical applications, particularly in studying the tumor microenvironment (TME). Despite advancements in machine learning for nuclei segmentation in hematoxylin and eosin (H&E) stained images, there remains a need for effective whole-cell segmentation methods. This study aims to develop a deep learning-based pipeline to automatically segment cells in H&E-stained tissues, thereby advancing the capabilities of pathological image analysis. The Cell Segmentation with Globally Optimized boundaries (CSGO) framework integrates nuclei and membrane segmentation algorithms, followed by post-processing using an energy-based watershed method. Specifically, we employed the You Only Look Once (Yolo) object detection algorithm for nuclei segmentation and U-Net for membrane segmentation. The membrane detection model was trained on a dataset of 7 hepatocellular carcinomas and 11 normal liver tissue patches. The cell segmentation performance was extensively evaluated on five external datasets, including liver, lung, and oral disease cases. CSGO demonstrated superior performance over the state-of-the-art method Cellpose, achieving higher F1 scores ranging from 0.37 to 0.53 at an intersection over union (IoU) threshold of 0.5 in four of the five external datasets, compared to that of Cellpose from 0.21 to 0.36. These results underscore the robustness and accuracy of our approach in various tissue types. A web-based application is available at https://ai.swmed.edu/projects/csgo, providing a user-friendly platform for researchers to apply our method to their own datasets. Our method exhibits remarkable versatility in whole-cell segmentation across diverse cancer subtypes, serving as an accurate and reliable tool to facilitate TME studies. The advancements presented in this study have the potential to significantly enhance the precision and efficiency of pathological image analysis, contributing to better understanding and treatment of cancer.

Acute kidney injury (AKI) and chronic kidney disease (CKD) are considered interconnected syndromes, as AKI episodes may accelerate CKD progression and CKD increases the risk of AKI. Genome-wide association studies (GWAS) may identify novel actionable therapeutic targets. Human genome-wide association studies (GWAS) for AKI or CKD were combined with murine AKI transcriptomics datasets to identify 13 (ACACB, ACSM5, CNDP1, DPEP1, GATM, SLC6A12, AGXT2L1, SLC15A2, CTSS, ICAM1, ITGAX, ITGAM, PPM1J) potentially actionable therapeutic targets to modulate kidney disease severity across species and across the AKI-CKD spectrum. Among them, SLC15A2, encoding the cell membrane proton-coupled peptide transporter 2 (PEPT2), was prioritized for data mining and functional intervention studies in vitro and in vivo because of its known function to transport nephrotoxic drugs such as colistin and the possibility for targeting with small molecules already in clinical use, such as cefadroxil. Data mining disclosed that SLC15A2 was upregulated in the tubulointerstitium of human CKD, including diabetic nephropathy, and the upregulation was localized to proximal tubular cells. Colistin elicited cytotoxicity and a proinflammatory response in cultured human and murine proximal tubular cells that was decreased by concomitant exposure to cefadroxil. In proof-of-concept in vivo studies, cefadroxil protected from colistin nephrotoxicity in mice. The GWAS association of SLC15A2 with human kidney disease may be actionable and related to the modifiable transport of nephrotoxins causing repeated subclinical episodes of AKI and/or chronic nephrotoxicity.

Superficial malignant peripheral nerve sheath tumors (SF-MPNSTs) are rare cancers and can be difficult to distinguish from spindle cell (SCM) or desmoplastic (DM) melanomas. Their biology is poorly understood. We performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) on SF-MPNST (n=8) and compared these to cases of SCM (n=7), DM (n=8), and deep MPNST (D-MPNST, n=8). Immunohistochemical staining for H3K27me3 and PRAME was also performed. SF-MPNST demonstrated intermediate features between D-MPNST and melanoma. Patients were younger than those with melanoma, and older than those with D-MPNST; outcome was worse and better respectively. SF-MPNST tumor mutational burden (TMB) was higher than D-MPNST and lower than melanoma; differences were significant only between SF-MPNST and SCM (p = 0.0454) and between D-MPNST and SCM (p = 0.001, Dunn's Kruskal-Wallis post-hoc test). Despite having an overlapping mutational profile in some common cancer-associated genes, the COSMIC mutational signatures clustered DM and SCM together with ultraviolet light exposure signatures (SBS7a, 7b), and SF- and D-MPNST together with defective DNA base excision repair (SBS30, 36). RNA-seq revealed differentially expressed genes between SF-MPNST and SCM (1670 genes), DM (831 genes), and D-MPNST (614 genes), some of which hold promise for development as immunohistochemical markers (SOX8, PLCH1) or aids (MLPH, CALB2, SOX11, TBX4). H3K27me3 immunoreactivity was diffusely lost in most D-MPNSTs (7/8, 88%), but showed variable and patchy loss in SF-MPNSTs (2/8, 25%). PRAME was entirely negative in the majority (0+ in 20/31, 65%), including 11/15 melanomas, and showed no significant difference between groups (p=0.105, Kruskal-Wallis test). Expression of immune cell transcripts was upregulated in melanomas relative to MPNSTs. Next-generation sequencing revealed multiple differential features between SF- MPNST, D-MPNST, SCM, and DM, including tumor mutation burden, mutational signatures, and differentially expressed genes. These findings help advance our understanding of disease pathogenesis and improve diagnostic modalities.

About 20% of human cancers harbor mutations of genes encoding SWI/SNF (Switch/Sucrose Non-Fermentable) complex subunits. Deficiency of subunits of the complex is present in 10% non-small cell lung cancers (NSCLC; SMARCA4/SMARCA2 deficient), 100% thoracic SMARCA4/A2 deficient undifferentiated tumors (TSADUDT; SMARCA4/A2 deficient), malignant rhabdoid tumor (MRT) and atypical/teratoid tumor (AT/RT) (SMARCB1 deficient), >90% of small cell carcinoma of the ovary, hypercalcemic type (SCCOHT; SMARCA4/SMARCA2 deficient), frequently in undifferentiated/dedifferentiated endometrial carcinoma (UDEC/DDEC; SMARCA4, SMARCA2, SMARCB1, ARID1A/B deficient), 100% SMARCA4 deficient undifferentiated uterine sarcoma (SDUS; SMARCA4 deficient); and in various other tumors from multifarious anatomic sites. Silencing of SWI/SNF gene expression may be genomically or epigenetically driven, causing loss of tumor suppression function or facilitating other oncogenic events. The SWI/SNF deficient tumors share the phenotype of poor or no differentiation, often with a variable component of rhabdoid tumor cells. They present at advanced stages with poor prognosis. Rhabdoid tumor cell phenotype is a useful feature to prompt investigation for this group of tumors. In the thoracic space, the overlap in morphology, immunophenotype, genetics, and epigenetics of SMARCA4/A2 deficient NSCLC and TSADUDT appears more significant. This raises a possible nosological relationship between TSADUDT and SMARCA4/A2 deficient NSCLC. Increased understanding of the genetics, epigenetics, and mechanisms of oncogenesis in these poor prognostic tumors, which are often resistant to conventional treatment, opens a new horizon of therapy for the tumors.

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas arising from peripheral nerves, accounting for 3-5% of soft tissue sarcomas. MPNSTs often recur locally, leading to poor survival. Achieving tumor-free surgical margins is essential to prevent recurrence, but current methods for determining tumor margins are limited, highlighting the need for improved biomarkers. In this study we investigated the degree to which MPNST extends into nerves adjacent to tumors. Alterations to the lipidome of MPNST and adjacent peripheral nerves were assessed using spatial lipidomics. Tissue samples from 5 MPNST patients were analyzed, revealing alterations of the lipid profile extending into the peripheral nerves beyond what was expected based on macroscopic and histological observations. Integration of spatial lipidomics and high-resolution accurate mass profiling identified distinct lipid profiles associated with healthy nerves, connective tissue, and tumors. Notably, histologically normal nerves exhibited myelin degradation and infiltration of pro-tumoral M2 macrophages, particularly near the tumor. Furthermore, aberrant osmium staining patterns and loss of H3K27me3 staining in absence of atypia were observed in a case with tumor recurrence. This exploratory study thereby highlights the changes occurring in the nerves affected by MPNST beyond what is visible on H&E, and provides leads for further biomarker studies, including aberrant osmium staining, to assess resection margins in MPNST.

High pigmentation and the abundance of M2 macrophages have been identified as negative predictors in uveal melanoma (UM). Risk factors associated with UM that are prevalent in high-risk White populations are still present, although less common, in relatively low-risk Asian populations. Research indicates that proangiogenic M2 macrophages and monosomy 3 play significant roles in UM progression. Our aim was to investigate the impact of tumor-associated macrophages in UM and examine their correlation with monosomy 3 and pigmentation. Transmission electron microscopy was used to analyze the morphology of macrophages in UM. Forty UM samples underwent fluorescent in situ hybridization for monosomy 3 identification. Immunohistochemistry was done to assess M2/M1 macrophages on 82 UM tissue samples. IL-10 and IL-12 expressions were quantified in UM serum samples by enzyme-linked immunosorbent assay. The expression of all markers was correlated with pigmentation markers (tyrosinase-related protein 1, tyrosinase-related protein 2, silver protein, and microphthalmia-associated transcription factor). Prognostic outcomes were determined using the Cox proportional hazard model and log-rank tests. Increased expression of M2/M1 macrophages was observed in 31 UM cases, which correlated with the high expression of pigmentation markers. IL-10 concentration was high in UM cases. Monosomy 3 was evident in 50% of UM cases and significantly associated with increased immunoexpression of M2/M1 macrophages and pigmentation markers. Reduced metastasis-free survival was observed in patients with UM with high M2/M1 macrophage expression (P = .001). High pigmentation and increased M2 macrophage density could impact the tumor microenvironment in UM. This could contribute to ineffective antitumor immune responses in patients with UM. Our findings suggest avenues for developing novel therapeutic approaches to counteract these immunosuppressive effects in UM.

Merkel Cell Carcinoma (MCC) is an aggressive cutaneous malignancy with a poor prognosis. One of the major mechanisms of immune evasion in MCC involves downregulation of MHC-I. Anti-PD-1/PD-L1 checkpoint inhibitors (CKIs) have revolutionized treatment for MCC, producing objective responses in ∼50% of patients, and are now standard of care; however, a substantial proportion of patients either fail to respond or develop resistance to CKIs. Given these recent successes, identification of other targetable immune checkpoints in the MCC tumor microenvironment (TME) is of great interest. Additionally, γ-delta (γδ) T cells may play critical roles in the response to MHC-I deficient cancers; therefore, evaluating γδ-T cells as a prognostic biomarker is warranted. We characterized the expression of PD-L1, PD-1, CD3, CD8, LAG-3, MHC-I, and γδ-T cells by IHC in a pre-immunotherapy retrospective cohort of 54 cases of MCC, and quantified expression levels and marker density via HALO. The increased density of LAG-3 and γδ-T cells correlated with other markers of an inflamed TME, with significant positive associations across all six markers (p<.002). Reflective of their putative role in the response to MHC-I suppressed cancers, cases with low HLA-I density showed a trend towards a higher ratio of γδ-T cells:CD3+ T cells (Spearman's r=-0.1582, p=0.21). Importantly, high CD3 density (HR=0.23, p=0.002), LAG-3 density (HR=0.47, p=0.037), γδ-T cell density (HR=0.26, p=0.02), and CD8 density (HR=0.27, p=0.03) showed associations with improved progression-free survival. Conditional tree analysis demonstrated that high CD8 and TCRδ expression were non-significant predictors of improved PFS and OS. Overall, LAG-3 is expressed in MCC infiltrates and is prognostic in pre-immunotherapy MCC, suggesting a potential role for LAG-3 inhibition in MCC. Additionally, CD8 and γδ-T cells may play a critical role in the response to MCC, and γδ-T cell density may represent a novel biomarker in MCC.

Lung squamous cell carcinoma (LUSC), a subtype of non-small cell lung cancer, represents a significant portion of lung cancer cases with distinct histologic patterns impacting prognosis and treatment. The current pathological assessment methods face limitations such as inter-observer variability, necessitating more reliable techniques. This study seeks to predict lymph node metastasis in LUSC using deep learning models applied to histopathology images of primary tumors, offering a more accurate and objective method for diagnosis and prognosis. Whole slide images (WSIs) from the Outdo-LUSC and TCGA-LUSC cohorts were used to train and validate deep-learning models. Multi-instance learning was applied, with patch-level predictions aggregated into WSI-level outcomes. The study employed the ResNet-18 network, transfer learning, and rigorous data preprocessing. To represent WSI features, innovative techniques like patch likelihood histogram (PLH) and bag of words (BoW) were used, followed by training of machine learning classifiers, including the ExtraTrees algorithm. The diagnostic model for lymph node metastasis showed strong performance, particularly using the ExtraTrees algorithm, as demonstrated by receiver operating characteristic (ROC) curves and Grad-CAM visualizations. The signature generated by the ExtraTrees algorithm, named LN_ISLUSCH (lymph node status-related in-situ lung squamous cell carcinoma histopathology), achieved an area under the curve (AUC) of 0.941 (95% CI: 0.926-0.955) in the training set and 0.788 (95% CI: 0.748-0.827) in the test set. Kaplan-Meier analyses confirmed that the LN_ISLUSCH model was a significant prognostic factor (p = 0.02). This study underscores the potential of artificial intelligence in enhancing diagnostic precision in pathology. The LN_ISLUSCH model stands out as a promising tool for predicting lymph node metastasis and prognosis in LUSC. Future studies should focus on larger and more diverse cohorts and explore the integration of additional omics data to further refine predictive accuracy and clinical utility.

Tumor-infiltrating lymphocytes (TILs) and immunoscoring based on densities of CD3+ and CD8+ TILs are both favorable prognostic markers in colorectal cancer (CRC). However, determination of the molecular features of TILs, particularly their immunoproteomic signatures would require the development of large scale in situ spatiotemporal technologies. Recently, a multiplex in situ digital spatial proteomic profiling (DSP) tool GeoMx DSP has been applied to identify biomarkers predictive of therapeutic responses and to understand disease mechanisms and progression. Taking advantage of this tool, we simultaneously characterized the spatial distribution and interactions of 42 immune proteins in tumor cells (TCs), CD3+ T stromal TILs (sTILs), and CD20+ B sTILs using tissue microarrays, and further studied their associations with CD3+ T TILs and immunoscores in CRC. First, our data showed that well-known immune checkpoints, such as PD-L1, PD-L2, and LAG3, were expressed at low levels, whereas some other immune proteins, such as CD11c, CD68, STING, and CD44, were highly expressed. Second, 8 spatial interactions were identified, including 5 interactions between TC and CD20+ B sTILs, 2 interactions between CD3+ T sTILs and CD20+ B sTILs, and 1 interaction among TC, CD3+ T sTILs, and CD20+ B sTILs. Third, the differential immune microlandscape in the spatial compartments was identified in tissues with positive CD3+ T intratumoral TILs and high immunoscores. Collectively, to our knowledge, our study is the first to provide in situ spatial immune characteristics at the proteomic level. Moreover, our findings provide direct evidence supporting the infiltration of CD3+ T sTILs from stoma to TC and shed important insights into better understanding and treating CRC patients related to different immune prognostic markers.

Non-small cell lung cancer (NSCLC) remains a leading cause of global mortality, with current screening and diagnostic methods often lacking in sensitivity and specificity. In our endeavor to develop precise, objective, and easily accessible diagnostic biomarkers for NSCLC, this study aimed to leverage rapidly evolving liquid biopsy techniques in the field of pathology to differentiate NSCLC patients from healthy controls by isolating peripheral blood samples and enriching extracellular vesicles (EVs) containing lung-derived proteins (thyroid transcription factor-1 [TTF-1] and surfactant protein B [SFTPB]), along with the cancer-associated protein CD151 EVs. Additionally, for practical applications, we established a nano-flow cytometry assay to detect plasma EVs readily. NSCLC patients demonstrated significantly reduced counts of TTF-1 EVs and CD151 EVs in plasma compared with healthy controls (P < .0001), whereas SFTPB EVs showed no significant difference (P > .05). Integrated analysis of TTF-1, CD151, and SFTPB EVs yielded an area under the curve values of 0.913 and 0.854 in the discovery and validation cohorts, respectively. Thus, although further validation is essential, the newly developed technologies are of great significance for the robust detection of NSCLC biomarkers.

Precision oncology is driven by biomarkers. For glioblastoma multiforme (GBM), the most common malignant adult primary brain tumor, O-methylguanine-DNA methyltransferase (MGMT) gene promoter methylation is an important prognostic and treatment clinical biomarker. Time-consuming preanalytical steps such as biospecimen storage, fixation, sampling, and processing are sources of data irreproducibility, and all these preanalytical variables are confounded by intratumor heterogeneity of MGMT promoter methylation. To assess the effect of preanalytical variables on GBM DNA methylation, tissue storage/sampling (CryoGrid), sample preparation multisonicator (PIXUL), and 5-methylcytosine DNA immunoprecipitation (Matrix-MeDIP-qPCR/seq) platforms were used. MGMT promoter methylation status assayed by MeDIP-qPCR was validated with methylation-specific polymerase chain reaction. MGMT promoter methylation levels in frozen and formalin-fixed paraffin-embedded sample pairs were not statistically different, confirming the reliability of formalin-fixed paraffin-embedded for MGMT promoter methylation analysis. Warm ex vivo ischemia (up to 4 hours at 37 °C) and 3 cycles of repeated sample thawing and freezing did not statistically impact 5-methylcytosine at MGMT promoter, exon, and enhancer regions, indicating the resistance of DNA methylation to common variations in sample processing conditions that might be encountered in research and clinical settings. Twenty-six percent to 34% of specimens exhibited intratumor heterogeneity in the MGMT DNA promoter methylation. These data demonstrate that variations in sample fixation, ischemia duration and temperature, and DNA methylation assay technique do not have a statistically significant impact on MGMT promoter methylation assessment. However, intratumor methylation heterogeneity underscores the value of multiple biopsies at different GBM geographic tumor sites in the evaluation of MGMT promoter methylation status. Matrix-MeDIP-seq analysis revealed that MGMT promoter methylation status clustered with other differentially methylated genomic loci (eg, HOXA and lncRNAs) that are resilient to variation in the above preanalytical conditions. These observations offer new opportunities to develop more granular data-based epigenetic GBM biomarkers. In this regard, the high-throughput CryoGrid-PIXUL-Matrix toolbox could be useful.

Despite significant improvement in the survival of pediatric patients with cancer, treatment outcomes for high-risk, relapsed, and refractory cancers remain unsatisfactory. Moreover, prolonged survival is frequently associated with long-term adverse effects due to intensive multimodal treatments. Accelerating the progress of pediatric oncology requires both therapeutic advances and strategies to mitigate the long-term cytotoxic side effects, potentially through targeting specific molecular drivers of pediatric malignancies. In this report, we present the results of integrative genomic and transcriptomic profiling of 230 patients with malignant solid tumors (the "primary cohort") and 18 patients with recurrent or otherwise difficult-to-treat nonmalignant conditions (the "secondary cohort"). The integrative workflow for the primary cohort enabled the identification of clinically significant single nucleotide variants, small insertions/deletions, and fusion genes, which were found in 55% and 28% of patients, respectively. For 38% of patients, molecularly informed treatment recommendations were made. In the secondary cohort, known or potentially driving alteration was detected in 89% of cases, including a suspected novel causal gene for patients with inclusion body infantile digital fibromatosis. Furthermore, 47% of findings also brought therapeutic implications for subsequent management. Across both cohorts, changes or refinements to the original histopathological diagnoses were achieved in 4% of cases. Our study demonstrates the efficacy of integrating advanced genomic and transcriptomic analyses to identify therapeutic targets, refine diagnoses, and optimize treatment strategies for challenging pediatric and young adult malignancies and underscores the need for broad implementation of precision oncology in clinical settings.

Pathologic response is an endpoint in many ongoing clinical trials for neoadjuvant regimens, including immune checkpoint blockade and chemotherapy. Whole-slide scanning of glass slides generates high-resolution digital images and allows for remote review and potential measurement with image analysis tools, but concordance of pathologic response assessment on digital scans compared with that on glass slides has yet to be evaluated. Such a validation goes beyond previous concordance studies, which focused on establishing surgical pathology diagnoses, as it requires quantitative assessment of tumor, necrosis, and regression. Further, as pathologic response assessment is being used as an endpoint, such concordance studies have regulatory implications. The purpose of this study was 2-fold, which was as follows: first, to determine the concordance between pathologic response assessed on glass slides and that assessed on digital scans, and second, to determine if pathologists benefited from using measurement tools when determining pathologic response. To that end, hematoxylin and eosin-stained glass slides from 64 non-small cell lung carcinoma specimens were visually assessed for percent residual viable tumor (%RVT). The sensitivity and specificity for digital vs glass reads of pathologic complete response (0% RVT) and major pathologic response (≤10% RVT) were all >95%. When %RVT was considered as a continuous variable, the intraclass correlation coefficient of digital vs glass reads was 0.94. The visual assessments of pathologic response were supported by pathologist annotations of residual tumor and tumor bed areas. In a separate subset of hematoxylin and eosin-stained glass slides, several measurement approaches to quantifying %RVT were performed. Pathologist estimates strongly reflected measured %RVT. This study demonstrates the high level of concordance between glass slides evaluated using light microscopy and digital whole-slide images for pathologic response assessments. Pathologists did not require measurement tools to generate robust %RVT values from slide annotations. These findings have broad implications for improving clinical workflows and multisite clinical trials.

Tumor-associated chronic lung inflammation depends on tumor necrosis factor (TNF)-α to activate several cytokines as part of an inflammatory loop, which plays a critical role in tumor progression in lung adenocarcinoma. High mobility group box 1 (HMGB1) is a cytokine that mediates inflammation. Whether TNF-α-induced inflammation regulates HMGB1 to contribute to tumor progression and promotion in lung adenocarcinoma remains unclear. Thus, human samples and a urethane-induced inflammation-driven lung adenocarcinoma (IDLA) mouse model were used to explore the involvement of HMGB1 in tumorigenesis, tumor progression, and efficacy of anti-programmed cell death protein (PD)-1 immunotherapy. High levels of HMGB1 were observed in human lung adenocarcinoma associated with poor overall survival in patients. HMGB1 upregulation was positively correlated with TNF-α-related inflammation and TIM3 infiltration. TNF-α upregulated intracellular and extracellular HMGB1 expression to contribute to tumor promotion in A549 cells in vitro. Using a urethane-induced IDLA mouse model, we found HMGB1 upregulation was associated with increased TIM3 T cell infiltration. Blocking TNF-α-dependent inflammation downregulated HMGB1 expression and inhibited tumorigenesis in the IDLA. Anti-PD-1 treatment alone did not inhibit tumor growth in the TNF-α-dependent IDLA, whereas anti-PD-1 combined with TNF-α blockade overcame anti-PD-1 immunotherapy resistance. Furthermore, anti-PD-1 combined with anti-HMGB1 also inhibited tumor growth in IDLA, suggesting increased HMGB1 release by TNF-α contributes to the resistance of anti-PD-1 immunotherapy in IDLA. Thus, tumor-associated TNF-α-dependent inflammation upregulated intracellular and extracellular HMGB1 expression in an inflammatory loop, contributing to tumor promotion and anti-PD-1 immunotherapy resistance in lung adenocarcinoma.

Spatial proteomics profiling is an emerging set of technologies that has the potential to elucidate the cell types, interactions, and molecular signatures that make up complex tissue microenvironments, with applications in the study of cancer, immunity, and much more. An emerging technique in the field is Co-Detection-by-indEXing (CODEX), recently renamed as the PhenoCycler system. This is a highly-multiplexed immunofluorescence imaging technology that relies on oligonucleotide-barcoded antibodies and cyclic immunofluorescence to visualize many antibody markers in a single specimen while preserving tissue architecture. Existing PhenoCycler panels are primarily designed for fresh-frozen tissues. Formalin-fixed paraffin-embedded (FFPE) blocks offer several advantages in preclinical research, but few antibody clones have been identified in this setting for PhenoCycler imaging. Here, we present a novel PhenoCycler panel of 28 validated antibodies for murine FFPE tissues. We describe our workflow for selecting and validating clones, barcoding antibodies, designing our panel, and performing multiplex imaging. We further detail our analysis pipeline for comparing marker expressions, clustering and phenotyping single-cell proteomics data, and quantifying spatial relationships. We then apply our panel and analysis protocol to profile the effects of three gene-delivery nanoparticle formulations, in combination with systemic anti-PD1, on the murine melanoma tumor immune microenvironment. Intralesional delivery of genes expressing the costimulatory molecule 4-1BBL and the cytokine IL-12 led to a shift towards intratumoral M1 macrophage polarization and promoted closer associations between intratumoral CD8 T cells and macrophages. Delivery of IFNγ, in addition to 4-1BBL and IL-12, further increased markers of antigen presentation on tumor cells and intratumoral antigen-presenting cells but also promoted greater expression of checkpoint marker PD-L1 and closer associations between intratumoral CD8 T cells and PD-L1-expressing tumor cells. These findings help to explain the benefits of 4-1BBL and IL-12 delivery while offering additional mechanistic insights into the limitations of IFNγ therapeutic efficacy.