Atom Efficient Synthesis of Trimethine Cyanines Using Formaldehyde as a Single Carbon Source.

In this work, we present an innovative and atom-efficient synthesis of trimethine cyanines (Cy3) using formaldehyde (FA) as a single-carbon reagent. The widespread application of Cy3 dyes in bioimaging and genomics/proteomics is often limited by synthetic routes plagued with low atom economy and substantial side-product formation. Through systematic investigation, we have developed a practical and efficient synthetic pathway for both symmetric and asymmetric Cy3 derivatives, significantly minimizing resource utilization. Notably, this approach yields water as the byproduct, in alignment with sustainable chemistry principles. Moreover, the efficient one-pot synthesis facilitates the detection of intracellular FA levels, utilizing the fluorescence signal of Cy3 in live cells. It is also possible to detect the endogenous FA in the intestinal tissues. We observed a significant decrease of FA in the small intestine of the inflammatory bowel disease (IBD) mice compared to the healthy mice. This methodological advancement not only enhances the scope of fluorescent dye synthesis but also contributes to the sustainable practices within chemical manufacturing, offering a significant leap forward in the development of environmentally friendly synthetic strategies.

Multiplex imaging of localized prostate tumors reveals altered spatial organization of AR-positive cells in the microenvironment.

Mapping the spatial interactions of cancer, immune, and stromal cell states presents novel opportunities for patient stratification and for advancing immunotherapy. While single-cell studies revealed significant molecular heterogeneity in prostate cancer cells, the impact of spatial stromal cell heterogeneity remains poorly understood. Here, we used cyclic immunofluorescent imaging on whole-tissue sections to uncover novel spatial associations between cancer and stromal cells in low- and high-grade prostate tumors and tumor-adjacent normal tissues. Our results provide a spatial map of single cells and recurrent cellular neighborhoods in the prostate tumor microenvironment of treatment-naive patients. We report unique populations of mast cells that show distinct spatial associations with M2 macrophages and regulatory T cells. Our results show disease-specific neighborhoods that are primarily driven by androgen receptor-positive (AR+) stromal cells and identify inflammatory gene networks active in AR+ prostate stroma.

AxonFinder: Automated segmentation of tumor innervating neuronal fibers.

Neurosignaling is increasingly recognized as a critical factor in cancer progression, where neuronal innervation of primary tumors contributes to the disease's advancement. This study focuses on segmenting individual axons within the prostate tumor microenvironment, which have been challenging to detect and analyze due to their irregular morphologies. We present a novel deep learning-based approach for the automated segmentation of axons, AxonFinder, leveraging a U-Net model with a ResNet-101 encoder, based on a multiplexed imaging approach. Utilizing a dataset of whole-slide images from low-, intermediate-, and high-risk prostate cancer patients, we manually annotated axons to train our model, achieving significant accuracy in detecting axonal structures that were previously hard to segment. Our analysis includes a comprehensive assessment of axon density and morphological features across different CAPRA-S prostate cancer risk categories, providing insights into the correlation between tumor innervation and cancer progression. Our paper suggests the potential utility of neuronal markers in the prognostic assessment of prostate cancer in aiding the pathologist's assessment of tumor sections and advancing our understanding of neurosignaling in the tumor microenvironment.

Exploratory Analyses of Circulating Neoplastic-Immune Hybrid Cells as Prognostic Biomarkers in Advanced Intrahepatic Cholangiocarcinoma.

Existing clinical biomarkers do not reliably predict treatment response or disease progression in patients with advanced intrahepatic cholangiocarcinoma (ICC). Circulating neoplastic-immune hybrid cells (CHCs) have great promise as a blood-based biomarker for patients with advanced ICC. Peripheral blood specimens were longitudinally collected from patients with advanced ICC enrolled in the HELIX-1 phase II clinical trial (NCT04251715). CHCs were identified by co-expression of pan-cytokeratin (CK) and CD45, and levels were correlated to patient clinical disease course. Unsupervised machine learning was then performed to extract their morphological features to compare them across disease courses. Five patients were included in this study, with a median of nine specimens collected per patient. A median of 13.5 CHCs per 50,000 peripheral blood mononuclear cells were identified at baseline, and levels decreased to zero following the initiation of treatment in all patients. Counts remained undetectable in three patients who demonstrated end-of-trial clinical treatment response and conversely increased in two patients with evidence of therapeutic resistance. In the post-trial surveillance period, interval counts increased prior to or at the time of clinical progression in three patients and remain undetectable in one patient with continued long-term disease stability. Using our machine learning platform, treatment-resistant CHCs exhibited upregulation of CK and downregulation of CD45 relative to treatment-responsive CHCs. CHCs represent a promising blood-based biomarker to supplement traditional radiographic and biochemical measures.

Concurrent substance use among cancer patients with and without a history of cannabis use since cancer diagnosis at an NCI-Designated Cancer Center in Florida.

BACKGROUND: Although substance use may have adverse impacts on cancer outcomes, little is known regarding patterns of concurrent substance use with cannabis among cancer patients. Our objective was to examine predictors of concurrent substance use with cannabis among cancer patients since their cancer diagnosis and explore perceptions of cannabis among these patients. METHODS: Patients treated at a National Cancer Institute-designated comprehensive cancer center were invited to participate in an electronic survey regarding medical cannabis from August to November 2021. Survey data were linked to internal data resources including electronic health records and patient intake forms to obtain history of substance use (defined as within at least 3 months of cancer diagnosis) of cigarettes, injection drugs, high levels of alcohol, or clinically unsupervised prescription drugs (total n = 1094). Concurrent substance users were defined as those with any reported substance use and cannabis use at the time of cancer diagnosis. We used descriptive statistics (χ2 or exact tests) to compare groups and estimated adjusted odds ratios (AORs) with 95% confidence intervals (CIs) to identify predictors of substance use among users and nonusers of cannabis. RESULTS: Approximately 45% (n = 489) of the sample reported cannabis use since their cancer diagnosis. Of patients who reported using cannabis, 20% self-reported concurrent polysubstance use, while 8% of cannabis nonusers reported substance use (P < .001). Among patients who use cannabis, those who reported 2 or more self-reported treatment-related symptoms (eg, pain, fatigue) were more likely to have self-reported concurrent substance use (AOR = 3.15, 95% CI = 1.07 to 9.27) compared with those without any symptoms. Among nonusers, those with lower educational background were more likely to have a history of concurrent substance use (AOR = 3.74, 95% CI = 1.57 to 8.92). Patients who use cannabis with concurrent substance use were more likely to report improved sleep (P = .04), increased appetite (P = .03), and treatment of additional medical conditions (P = .04) as perceived benefits of cannabis use. CONCLUSIONS: High symptom burden may be associated with concurrent substance use with cannabis among cancer patients.

An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video).

BACKGROUND: Accurate prediction of pathologic results for early gastric cancer (EGC) based on endoscopic findings is essential in deciding between endoscopic and surgical resection. This study aimed to develop an artificial intelligence (AI) model to assess comprehensive pathologic characteristics of EGC using white-light endoscopic images and videos. METHODS: To train the model, we retrospectively collected 4,336 images and prospectively included 153 videos from patients with EGC who underwent endoscopic or surgical resection. The performance of the model was tested and compared to that of 16 endoscopists (nine experts and seven novices) using a mutually exclusive set of 260 images and 10 videos. Finally, we conducted external validation using 436 images and 89 videos from another institution. RESULTS: After training, the model achieved predictive accuracies of 89.7% for undifferentiated histology, 88.0% for submucosal invasion, 87.9% for lymphovascular invasion (LVI), and 92.7% for lymph node metastasis (LNM), using endoscopic videos. The area under the curve values of the model were 0.992 for undifferentiated histology, 0.902 for submucosal invasion, 0.706 for LVI, and 0.680 for LNM in the test. In addition, the model showed significantly higher accuracy than the experts in predicting undifferentiated histology (92.7% vs. 71.6%), submucosal invasion (87.3% vs. 72.6%), and LNM (87.7% vs. 72.3%). The external validation showed accuracies of 75.6% and 71.9% for undifferentiated histology and submucosal invasion, respectively. CONCLUSIONS: AI may assist endoscopists with high predictive performance for differentiation status and invasion depth of EGC. Further research is needed to improve the detection of LVI and LNM.

Gastric microbiome signature for predicting metachronous recurrence after endoscopic resection of gastric neoplasm.

BACKGROUND: Changes in gastric microbiome are associated with gastric carcinogenesis. Studies on the association between gastric mucosa-associated gastric microbiome (MAM) and metachronous gastric cancer are limited. This study aimed to identify gastric MAM as a predictive factor for metachronous recurrence following endoscopic resection of gastric neoplasms. METHOD: Microbiome analyses were conducted for 81 patients in a prospective cohort to investigate surrogate markers to predict metachronous recurrence. Gastric MAM in non-cancerous corporal biopsy specimens was evaluated using Illumina MiSeq platform targeting 16S ribosomal DNA. RESULTS: Over a median follow-up duration of 53.8 months, 16 metachronous gastric neoplasms developed. Baseline gastric MAM varied with Helicobacter pylori infection status, but was unaffected by initial pathologic diagnosis, presence of atrophic gastritis, intestinal metaplasia, or synchronous lesions. The group with metachronous recurrence did not exhibit distinct phylogenetic diversity compared with the group devoid of recurrence but showed significant difference in ß-diversity. The study population could be classified into two distinct gastrotypes based on baseline gastric MAM: gastrotype 1, Helicobacter-abundant; gastrotype 2: Akkermansia-abundant. Patients in gastrotype 2 showed higher risk of metachronous recurrence than gastrotype (Cox proportional hazard analysis, adjusted hazard ratio [95% confidence interval]: 5.10 [1.09-23.79]). CONCLUSIONS: Gastric cancer patients can be classified into two distinct gastrotype groups by their MAM profiles, which were associated with different risk of metachronous recurrence.

Real-World Application of Artificial Intelligence for Detecting Pathologic Gastric Atypia and Neoplastic Lesions.

PURPOSE: Results of initial endoscopic biopsy of gastric lesions often differ from those of the final pathological diagnosis. We evaluated whether an artificial intelligence-based gastric lesion detection and diagnostic system, ENdoscopy as AI-powered Device Computer Aided Diagnosis for Gastroscopy (ENAD CAD-G), could reduce this discrepancy. MATERIALS AND METHODS: We retrospectively collected 24,948 endoscopic images of early gastric cancers (EGCs), dysplasia, and benign lesions from 9,892 patients who underwent esophagogastroduodenoscopy between 2011 and 2021. The diagnostic performance of ENAD CAD-G was evaluated using the following real-world datasets: patients referred from community clinics with initial biopsy results of atypia (n=154), participants who underwent endoscopic resection for neoplasms (Internal video set, n=140), and participants who underwent endoscopy for screening or suspicion of gastric neoplasm referred from community clinics (External video set, n=296). RESULTS: ENAD CAD-G classified the referred gastric lesions of atypia into EGC (accuracy, 82.47%; 95% confidence interval [CI], 76.46%-88.47%), dysplasia (88.31%; 83.24%-93.39%), and benign lesions (83.12%; 77.20%-89.03%). In the Internal video set, ENAD CAD-G identified dysplasia and EGC with diagnostic accuracies of 88.57% (95% CI, 83.30%-93.84%) and 91.43% (86.79%-96.07%), respectively, compared with an accuracy of 60.71% (52.62%-68.80%) for the initial biopsy results (P<0.001). In the External video set, ENAD CAD-G classified EGC, dysplasia, and benign lesions with diagnostic accuracies of 87.50% (83.73%-91.27%), 90.54% (87.21%-93.87%), and 88.85% (85.27%-92.44%), respectively. CONCLUSIONS: ENAD CAD-G is superior to initial biopsy for the detection and diagnosis of gastric lesions that require endoscopic resection. ENAD CAD-G can assist community endoscopists in identifying gastric lesions that require endoscopic resection.

Trends in alcohol use and alcoholic liver disease in South Korea: a nationwide cohort study.

BACKGROUND: There is a lack of national-level research on alcohol consumption and the epidemiology of alcoholic liver disease (ALD) in South Korea. This study aims to address the critical public health issue of ALD by focusing on its trends, incidence, and outcomes, using nationwide claims data. METHODS: Utilizing National Health Insurance Service data from 2011 to 2017, we calculated the population's overall drinking amount and the incidence of ALD based on ICD-10 diagnosis codes. RESULTS: From 2011 to 2017 in South Korea, social drinking increased from 15.7% to 16.5%, notably rising among women. High-risk drinking remained around 16.4%, decreasing in men aged 20-39 but not decreased in men aged 40-59 and steadily increased in women aged 20-59. The prevalence of ALD in high-risk drinkers (0.97%) was significantly higher than in social drinkers (0.16%). A 3-year follow-up revealed ALD incidence of 1.90% for high-risk drinkers and 0.31% for social drinkers. Women high-risk drinkers had a higher ALD risk ratio (6.08) than men (4.18). The economic burden of ALD was substantial, leading to higher healthcare costs and increased hospitalization. Progression rates to liver cirrhosis and hepatocellular carcinoma (HCC) in ALD patients were 23.3% and 2.8%, respectively, with no gender difference in cirrhosis progression. CONCLUSIONS: The study revealed a concerning rise in alcohol consumption among South Korean women and emphasizes the heightened health risks and economic burdens associated with high-risk drinking, especially concerning ALD and its complications.

4-O-Methylascochlorin Synergistically Enhances 5-Fluorouracil-Induced Apoptosis by Inhibiting the Wnt/ß-Catenin Signaling Pathway in Colorectal Cancer Cells.

4-O-Methyl-ascochlorin (MAC), a derivative of the prenyl-phenol antibiotic ascochlorin extracted from the fungus Ascochyta viciae, shows anticarcinogenic effects on various cancer cells. 5-Fluorouracil (5-FU) is used to treat colorectal cancer (CRC); however, its efficacy must be enhanced. In this study, we investigated the molecular mechanisms by which MAC acts synergistically with 5-FU to inhibit cell proliferation and induce apoptosis in CRC cells. MAC enhanced the cytotoxic effects of 5-FU by suppressing the Akt/mTOR/p70S6K and Wnt/ß-catenin signaling pathways. It also reduced the viability of 5-FU-resistant (5-FU-R) cells. Furthermore, expression of anti-apoptosis-related proteins and cancer stem-like cell (CSC) markers by 5-FU-R cells decreased in response to MAC. Similar to MAC, the knockdown of CTNNB1 induced apoptosis and reduced expression of mRNA encoding CRC markers in 5-FU-R cells. In summary, these results suggest that MAC and other ß-catenin modulators may be useful in overcoming the 5-FU resistance of CRC cells.

Non-canonical deubiquitination of OTUB1 induces IFNγ-mediated cell cycle arrest via regulation of p27 stability.

The deubiquitinase OTUB1, implicated as a potential oncogene in various tumors, lacks clarity in its regulatory mechanism in tumor progression. Our study investigated the effects and underlying mechanisms of OTUB1 on the breast cancer cell cycle and proliferation in IFNγ stimulation. Loss of OTUB1 abrogated IFNγ-induced cell cycle arrest by regulating p27 protein expression, whereas OTUB1 overexpression significantly enhanced p27 expression even without IFNγ treatment. Tyr26 phosphorylation residue of OTUB1 directly bound to p27, modulating its post-translational expression. Furthermore, we identified crucial lysine residues (K134, K153, and K163) for p27 ubiquitination. Src downregulation reduced OTUB1 and p27 expression, suggesting that IFNγ-induced cell cycle arrest is mediated by the Src-OTUB1-p27 signaling pathway. Our findings highlight the pivotal role of OTUB1 in IFNγ-induced p27 expression and cell cycle arrest, offering therapeutic implications.

MIM-CyCIF: masked imaging modeling for enhancing cyclic immunofluorescence (CyCIF) with panel reduction and imputation.

Cyclic Immunofluorescence (CyCIF) can quantify multiple biomarkers, but panel capacity is limited by technical challenges. We propose a computational panel reduction approach that can impute the information content from 25 markers using only 9 markers, learning co-expression and morphological patterns while concurrently increasing speed and panel content and decreasing cost. We demonstrate strong correlations in predictions and generalizability across breast and colorectal cancer, illustrating applicability of our approach to diverse tissue types.

Targeting Heme Oxygenase 2 (HO2) with TiNIR, a Theragnostic Approach for Managing Metastatic Non-Small Cell Lung Cancer.

Despite notable advancements in cancer therapeutics, metastasis remains a primary obstacle impeding a successful prognosis. Our prior study has identified heme oxygenase 2 (HO2) as a promising therapeutic biomarker for the aggressive subsets within tumor. This study aims to systematically evaluate HO2 as a therapeutic target of cancer, with a specific emphasis on its efficacy in addressing cancer metastasis. Through targeted inhibition of HO2 by TiNIR (tumor-initiating cell probe with near infrared), we observed a marked increase in reactive oxygen species. This, in turn, orchestrated the modulation of AKT and cJUN activation, culminating in a substantial attenuation of both proliferation and migration within a metastatic cancer cell model. Furthermore, in a mouse model, clear inhibition of cancer metastasis was unequivocally demonstrated with an HO2 inhibitor administration. These findings underscore the therapeutic promise of targeting HO2 as a strategic intervention to impede cancer metastasis, enhancing the effectiveness of cancer treatments.

Ultra high content analyses of circulating and tumor associated hybrid cells reveal phenotypic heterogeneity.

Persistently high, worldwide mortality from cancer highlights the unresolved challenges of disease surveillance and detection that impact survival. Development of a non-invasive, blood-based biomarker would transform survival from cancer. We demonstrate the functionality of ultra-high content analyses of a newly identified population of tumor cells that are hybrids between neoplastic and immune cells in patient matched tumor and peripheral blood specimens. Using oligonucleotide conjugated antibodies (Ab-oligo) permitting cyclic immunofluorescence (cyCIF), we present analyses of phenotypes among tumor and peripheral blood hybrid cells. Interestingly, the majority of circulating hybrid cell (CHC) subpopulations were not identified in tumor-associated hybrids. These results highlight the efficacy of ultra-high content phenotypic analyses using Ab-oligo based cyCIF applied to both tumor and peripheral blood specimens. The combination of a multiplex phenotypic profiling platform that is gentle enough to analyze blood to detect and evaluate disseminated tumor cells represents a novel approach to exploring novel tumor biology and potential utility for developing the population as a blood-based biomarker in cancer.

The Effect of 3-Dimensional-Printed Sequential Dual Drug-Releasing Patch on the Capsule Formation Around the Silicone Implant in a Rat Model.

BACKGROUND: Implant-based breast reconstruction is associated with increased risk of early infection and late-stage capsular contracture. OBJECTIVES: We evaluated the feasibility of a dual drug-releasing patch that enabled the controlled delivery of antibiotics and immunosuppressants in a temporally and spatially appropriate manner to the implant site. METHODS: The efficacy of a dual drug-releasing patch, which was 3-dimensional-printed (3D-printed) with tissue-derived biomaterial ink, was evaluated in rats with silicone implants. The groups included implant only (n = 10); implant plus bacterial inoculation (n = 14); implant, bacterial inoculation, and patch loaded with gentamycin placed on the ventral side of the implant (n = 10), and implant, bacterial inoculation, and patch loaded with gentamycin and triamcinolone acetonide (n = 9). Histologic and immunohistochemical analyses were performed 8 weeks after implantation. RESULTS: The 2 drugs were sequentially released from the dual drug-releasing patch and exhibited different release profiles. Compared to the animals with bacterial inoculation, those with the antibiotic-only and the dual drug-releasing patch exhibited thinner capsules and lower myofibroblast activity and inflammation, indicating better tissue integration and less foreign body response. These effects were more pronounced with the dual drug-releasing patch than with the antibiotic-only patch. CONCLUSIONS: The 3D-printed dual drug-releasing patch effectively reduced inflammation and capsule formation in a rat model of silicone breast reconstruction. The beneficial effect of the dual drug-releasing patch was better than that of the antibiotic-only patch, indicating its therapeutic potential as a novel approach to preventing capsular contracture while reducing concerns of systemic side effects.

Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy.

Circulating hybrid cells (CHCs) are a newly discovered, tumor-derived cell population found in the peripheral blood of cancer patients and are thought to contribute to tumor metastasis. However, identifying CHCs by immunofluorescence (IF) imaging of patient peripheral blood mononuclear cells (PBMCs) is a time-consuming and subjective process that currently relies on manual annotation by laboratory technicians. Additionally, while IF is relatively easy to apply to tissue sections, its application to PBMC smears presents challenges due to the presence of biological and technical artifacts. To address these challenges, we present a robust image analysis pipeline to automate the detection and analysis of CHCs in IF images. The pipeline incorporates quality control to optimize specimen preparation protocols and remove unwanted artifacts, leverages a ß-variational autoencoder (VAE) to learn meaningful latent representations of single-cell images, and employs a support vector machine (SVM) classifier to achieve human-level CHC detection. We created a rigorously labeled IF CHC data set including nine patients and two disease sites with the assistance of 10 annotators to evaluate the pipeline. We examined annotator variation and bias in CHC detection and provided guidelines to optimize the accuracy of CHC annotation. We found that all annotators agreed on CHC identification for only 65% of the cells in the data set and had a tendency to underestimate CHC counts for regions of interest (ROIs) containing relatively large amounts of cells (>50,000) when using the conventional enumeration method. On the other hand, our proposed approach is unbiased to ROI size. The SVM classifier trained on the ß-VAE embeddings achieved an F1 score of 0.80, matching the average performance of human annotators. Our pipeline enables researchers to explore the role of CHCs in cancer progression and assess their potential as a clinical biomarker for metastasis. Further, we demonstrate that the pipeline can identify discrete cellular phenotypes among PBMCs, highlighting its utility beyond CHCs.

Computed Tomography Radiomics for Preoperative Prediction of Spread Through Air Spaces in the Early Stage of Surgically Resected Lung Adenocarcinomas.

PURPOSE: To assess the added value of radiomics models from preoperative chest CT in predicting the presence of spread through air spaces (STAS) in the early stage of surgically resected lung adenocarcinomas using multiple validation datasets. MATERIALS AND METHODS: This retrospective study included 550 early-stage surgically resected lung adenocarcinomas in 521 patients, classified into training, test, internal validation, and temporal validation sets (n=211, 90, 91, and 158, respectively). Radiomics features were extracted from the segmented tumors on preoperative chest CT, and a radiomics score (Rad-score) was calculated to predict the presence of STAS. Diagnostic performance of the conventional model and the combined model, based on a combination of conventional and radiomics features, for the diagnosis of the presence of STAS were compared using the area under the curve (AUC) of the receiver operating characteristic curve. RESULTS: Rad-score was significantly higher in the STAS-positive group compared to the STAS-negative group in the training, test, internal, and temporal validation sets. The performance of the combined model was significantly higher than that of the conventional model in the training set {AUC: 0.784 [95% confidence interval (CI): 0.722-0.846] vs. AUC: 0.815 (95% CI: 0.759-0.872), p=0.042}. In the temporal validation set, the combined model showed a significantly higher AUC than that of the conventional model (p=0.001). The combined model showed a higher AUC than the conventional model in the test and internal validation sets, albeit with no statistical significance. CONCLUSION: A quantitative CT radiomics model can assist in the non-invasive prediction of the presence of STAS in the early stage of lung adenocarcinomas.

Quantitative multiplex immunohistochemistry reveals inter-patient lymphovascular and immune heterogeneity in primary cutaneous melanoma.

Introduction: Quantitative, multiplexed imaging is revealing complex spatial relationships between phenotypically diverse tumor infiltrating leukocyte populations and their prognostic implications. The underlying mechanisms and tissue structures that determine leukocyte distribution within and around tumor nests, however, remain poorly understood. While presumed players in metastatic dissemination, new preclinical data demonstrates that blood and lymphatic vessels (lymphovasculature) also dictate leukocyte trafficking within tumor microenvironments and thereby impact anti-tumor immunity. Here we interrogate these relationships in primary human cutaneous melanoma. Methods: We established a quantitative, multiplexed imaging platform to simultaneously detect immune infiltrates and tumor-associated vessels in formalin-fixed paraffin embedded patient samples. We performed a discovery, retrospective analysis of 28 treatment-naïve, primary cutaneous melanomas. Results: Here we find that the lymphvasculature and immune infiltrate is heterogenous across patients in treatment naïve, primary melanoma. We categorized five lymphovascular subtypes that differ by functionality and morphology and mapped their localization in and around primary tumors. Interestingly, the localization of specific vessel subtypes, but not overall vessel density, significantly associated with the presence of lymphoid aggregates, regional progression, and intratumoral T cell infiltrates. Discussion: We describe a quantitative platform to enable simultaneous lymphovascular and immune infiltrate analysis and map their spatial relationships in primary melanoma. Our data indicate that tumor-associated vessels exist in different states and that their localization may determine potential for metastasis or immune infiltration. This platform will support future efforts to map tumor-associated lymphovascular evolution across stage, assess its prognostic value, and stratify patients for adjuvant therapy.