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The extent to which the geographic diversity of the US plays a significant role in melanoma incidence and mortality over time has not been precisely characterized. We obtained age-adjusted melanoma data for the 50 states between 2001 and 2019 from the Surveillance, Epidemiology, and End Results registry and performed hierarchical clustering (complete linkage, Euclidean space) to uncover geo-temporal trend groups over 2 decades. While there was a global increase in incidence during this time (b1 = +0.41, P < .0001), there were 6 distinct clusters (by absolute and Z-score) with significantly different temporal trends (analysis of covariance P < .0001). Cluster 2 states had the sharpest increase in incidence with b1 = +0.66, P < .0001. For mortality, the global rate decreased (b1 = -0.03, P = .0003) with 3 and 6 clusters by absolute and Z-scores, respectively (analysis of covariance P < .05). Cluster 1 states exhibited the smallest decline in mortality (b1 = -0.017, P = .008). Mortality to incidence ratios declined (b1 = -0.0037, P < .0001) and harbored 4 and 6 clusters by absolute and Z-score analysis, respectively (analysis of covariance P < .0001). Cluster 4 states had the lowest rate of mortality to incidence ratios decline (b1 = -0.003, P < .0001). These results provide an unprecedented higher dimensional view of melanoma behavior over space and time. With more refined analyses, geospatial studies can uncover local trends which can inform public health agencies to more properly allocate resources.
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BACKGROUND: Although the recent drop in melanoma mortality has been attributed to the introduction of newer therapies, the impact of ongoing public efforts remains unknown. OBJECTIVE: Characterize and model melanoma mortality trends before the era of molecular and immune therapies (1969-2014) in the U.S. and Australia. METHODS: Differential time series analysis based on population-ascertained melanoma mortality rates from the U.S. and Australia. Mortality rates were modeled and compared to the trajectories of ten other cancers. RESULTS: Melanoma mortality rates have been significantly decelerating since the 1970s in both the U.S. (P < .0001) and Australia (P = .0021). Zero acceleration occurred around 2001 (95% CI: 1996, 2008) for the U.S. and 2004 (95% CI: 1999, 2011) for Australia. Male mortality rates decelerated 3x-4x faster than females in both countries. Melanoma mortality followed a similar quadratic function (R2 > 0.9) to 10 other cancers, albeit with a later inflection point (1986 vs 2001) and broader focal width. LIMITATIONS: Absolute mortality data used without further stratification or considering cancer incidence or covariates. CONCLUSION: Melanoma deaths have been decelerating for the past 5 decades, reaching an inflection point around 2001, suggesting that mitigating campaigns were already afoot in both the U.S. and Australia before the advent of modern therapies.
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BACKGROUND: Understanding co-occurrence patterns and prognostic implications of immune-related adverse events is crucial for immunotherapy management. However, previous studies have been limited by sample size and generalisability. In this study, we leveraged a multi-institutional cohort and a population-level database to investigate co-occurrence patterns of and survival outcomes after multi-organ immune-related adverse events among recipients of immune checkpoint inhibitors. METHODS: In this retrospective study, we identified individuals who received immune checkpoint inhibitors between May 31, 2015, and June 29, 2022, from the Massachusetts General Hospital, Brigham and Women's Hospital, and Dana-Farber Cancer Institute (Boston, MA, USA; MGBD cohort), and between April 30, 2010, and Oct 11, 2021, from the independent US population-based TriNetX network. We identified recipients from all datasets using medication codes and names of seven common immune checkpoint inhibitors, and patients were excluded from our analysis if they had incomplete information (eg, diagnosis and medication records) or if they initiated immune checkpoint inhibitor therapy after Oct 11, 2021. Eligible patients from the MGBD cohort were then propensity score matched with recipients of immune checkpoint inhibitors from the TriNetX database (1:2) based on demographic, cancer, and immune checkpoint inhibitor characteristics to facilitate cohort comparability. We applied immune-related adverse event identification rules to identify patients who did and did not have immune-related adverse events in the matched cohorts. To reduce the likelihood of false positives, patients diagnosed with suspected immune-related adverse events within 3 months after chemotherapy were excluded. We performed pairwise correlation analyses, non-negative matrix factorisation, and hierarchical clustering to identify co-occurrence patterns in the MGBD cohort. We conducted landmark overall survival analyses for patient clusters based on predominant immune-related adverse event factors and calculated accompanying hazard ratios (HRs) and 95% CIs, focusing on the 6-month landmark time for primary analyses. We validated our findings using the TriNetX cohort. FINDINGS: We identified 15 246 recipients of immune checkpoint inhibitors from MGBD and 50 503 from TriNetX, of whom 13 086 from MGBD and 26 172 from TriNetX were included in our propensity score-matched cohort. Median follow-up durations were 317 days (IQR 113-712) in patients from MGBD and 249 days (91-616) in patients from TriNetX. After applying immune-related adverse event identification rules, 8704 recipients of immune checkpoint inhibitors were retained from MGBD, of whom 3284 (37·7%) had and 5420 (62·3%) did not have immune-related adverse events, and 18 162 recipients were retained from TriNetX, of whom 5538 (30·5%) had and 12 624 (69·5%) did not have immune-related adverse events. In both cohorts, positive pairwise correlations of immune-related adverse events were commonly observed. Co-occurring immune-related adverse events were decomposed into seven factors across organs, revealing seven distinct patient clusters (endocrine, cutaneous, respiratory, gastrointestinal, hepatic, musculoskeletal, and neurological). In the MGBD cohort, the patient clusters that predominantly had endocrine (HR 0·53 [95% CI 0·40-0·70], p<0·0001) and cutaneous (0·61 [0·46-0·81], p=0·0007) immune-related adverse events had favourable overall survival outcomes at the 6-month landmark timepoint, while the other clusters either had unfavourable (respiratory: 1·60 [1·25-2·03], p=0·0001) or neutral survival outcomes (gastrointestinal: 0·86 [0·67-1·10], p=0·23; musculoskeletal: 0·97 [0·78-1·21], p=0·78; hepatic: 1·20 [0·91-1·59], p=0·19; and neurological: 1·30 [0·97-1·74], p=0·074). Similar results were found in the TriNetX cohort (endocrine: HR 0·75 [95% CI 0·60-0·93], p=0·0078; cutaneous: 0·62 [0·48-0·82], p=0·0007; respiratory: 1·21 [1·00-1·46], p=0·044), except for the neurological cluster having unfavourable (rather than neutral) survival outcomes (1·30 [1·06-1·59], p=0·013). INTERPRETATION: Reliably identifying the immune-related adverse event cluster to which a patient belongs can provide valuable clinical information for prognosticating outcomes of immunotherapy. These insights can be leveraged to counsel patients on the clinical impact of their individual constellation of immune-related adverse events and ultimately develop more personalised surveillance and mitigation strategies. FUNDING: US National Institutes of Health.
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Inhibidores de Puntos de Control Inmunológico , Neoplasias , Humanos , Inhibidores de Puntos de Control Inmunológico/efectos adversos , Estudios Retrospectivos , Femenino , Masculino , Persona de Mediana Edad , Anciano , Neoplasias/tratamiento farmacológico , Neoplasias/inmunologíaAsunto(s)
Melanoma , Proteínas Proto-Oncogénicas B-raf , Humanos , Melanoma/genética , Melanoma/tratamiento farmacológico , Melanoma/inmunología , Proteínas Proto-Oncogénicas B-raf/genética , Mutación , Mitocondrias/genética , Masculino , Femenino , Persona de Mediana Edad , Metástasis de la Neoplasia/genéticaRESUMEN
Cancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal and other cells within the tumor microenvironment (TME). Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize molecular, cellular and spatial properties of TMEs for various malignancies. This study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of TMEs using multiplexed single-cell data. The source code and tutorials are available at https://semenovlab.github.io/SpatialCells. SpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion and metastasis.
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Análisis de la Célula Individual , Programas Informáticos , Microambiente Tumoral , Análisis de la Célula Individual/métodos , Humanos , Neoplasias/patología , Aprendizaje Automático , Biología Computacional/métodosRESUMEN
Chronic inflammation is a major cause of cancer worldwide. Interleukin 33 (IL-33) is a critical initiator of cancer-prone chronic inflammation; however, its induction mechanism by environmental causes of chronic inflammation is unknown. Herein, we demonstrate that Toll-like receptor (TLR)3/4-TBK1-IRF3 pathway activation links environmental insults to IL-33 induction in the skin and pancreas inflammation. An FDA-approved drug library screen identifies pitavastatin to effectively suppress IL-33 expression by blocking TBK1 membrane recruitment/activation through the mevalonate pathway inhibition. Accordingly, pitavastatin prevents chronic pancreatitis and its cancer sequela in an IL-33-dependent manner. The IRF3-IL-33 axis is highly active in chronic pancreatitis and its associated pancreatic cancer in humans. Interestingly, pitavastatin use correlates with a significantly reduced risk of chronic pancreatitis and pancreatic cancer in patients. Our findings demonstrate that blocking the TBK1-IRF3-IL-33 signaling axis suppresses cancer-prone chronic inflammation. Statins present a safe and effective prophylactic strategy to prevent chronic inflammation and its cancer sequela.
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Inhibidores de Hidroximetilglutaril-CoA Reductasas , Factor 3 Regulador del Interferón , Interleucina-33 , Neoplasias Pancreáticas , Proteínas Serina-Treonina Quinasas , Quinolinas , Transducción de Señal , Interleucina-33/metabolismo , Animales , Factor 3 Regulador del Interferón/metabolismo , Humanos , Neoplasias Pancreáticas/prevención & control , Neoplasias Pancreáticas/metabolismo , Neoplasias Pancreáticas/genética , Inhibidores de Hidroximetilglutaril-CoA Reductasas/farmacología , Inhibidores de Hidroximetilglutaril-CoA Reductasas/uso terapéutico , Ratones , Proteínas Serina-Treonina Quinasas/metabolismo , Transducción de Señal/efectos de los fármacos , Quinolinas/farmacología , Quinolinas/uso terapéutico , Inflamación/prevención & control , Inflamación/metabolismo , Pancreatitis Crónica/prevención & control , Pancreatitis Crónica/metabolismo , Receptor Toll-Like 3/metabolismo , Ratones Endogámicos C57BL , Receptor Toll-Like 4/metabolismo , Ácido Mevalónico/metabolismo , Masculino , Femenino , Ratones NoqueadosRESUMEN
Scalable identification of patients with the post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms and the suboptimal accuracy, demographic biases, and underestimation of the PASC diagnosis code (ICD-10 U09.9). In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying research cohorts of PASC patients, defined as a diagnosis of exclusion. We used longitudinal electronic health records (EHR) data from over 295 thousand patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to exclude sequelae that prior conditions can explain. We performed independent chart reviews to tune and validate our precision phenotyping algorithm. Our PASC phenotyping algorithm improves precision and prevalence estimation and reduces bias in identifying Long COVID patients compared to the U09.9 diagnosis code. Our algorithm identified a PASC research cohort of over 24 thousand patients (compared to about 6 thousand when using the U09.9 diagnosis code), with a 79.9 percent precision (compared to 77.8 percent from the U09.9 diagnosis code). Our estimated prevalence of PASC was 22.8 percent, which is close to the national estimates for the region. We also provide an in-depth analysis outlining the clinical attributes, encompassing identified lingering effects by organ, comorbidity profiles, and temporal differences in the risk of PASC. The PASC phenotyping method presented in this study boasts superior precision, accurately gauges the prevalence of PASC without underestimating it, and exhibits less bias in pinpointing Long COVID patients. The PASC cohort derived from our algorithm will serve as a springboard for delving into Long COVID's genetic, metabolomic, and clinical intricacies, surmounting the constraints of recent PASC cohort studies, which were hampered by their limited size and available outcome data.
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Antígeno B7-H1 , Enfermedades del Tejido Conjuntivo , Inhibidores de Puntos de Control Inmunológico , Receptor de Muerte Celular Programada 1 , Humanos , Femenino , Masculino , Persona de Mediana Edad , Receptor de Muerte Celular Programada 1/antagonistas & inhibidores , Enfermedades del Tejido Conjuntivo/tratamiento farmacológico , Enfermedades del Tejido Conjuntivo/mortalidad , Enfermedades del Tejido Conjuntivo/inmunología , Antígeno B7-H1/antagonistas & inhibidores , Anciano , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Inhibidores de Puntos de Control Inmunológico/efectos adversos , Enfermedades Autoinmunes/tratamiento farmacológico , Enfermedades Autoinmunes/mortalidad , Adulto , Estudios de CohortesRESUMEN
With an increasing number of patients eligible for immune checkpoint inhibitors, the incidence of immune-related adverse events (irAEs) is on the rise. Dermatologic immune-related adverse events (D-irAEs) are the most common and earliest to manifest, often with important downstream consequences for the patient. Current guidelines lack clarity in terms of diagnostic criteria for D-irAEs. The goal of this project is to better define D-irAE for the purposes of identification, diagnosis, and future study of this important group of diseases.The objectives of this project were to develop consensus guidance for an approach to D-irAEs including disease definitions and severity grading. Knowing that consensus among oncologists, dermatologists, and irAE subspecialists would be critical for usability, we formed a Dermatologic irAE Disease Definition Panel. The panel was composed of 34 experts, including oncologists, dermatologists, a rheumatologist, and an allergist/immunologist from 22 institutions across the USA and internationally. A modified Delphi consensus process was used, with two rounds of anonymous ratings by panelists and two virtual meetings to discuss areas of controversy. Panelists rated content for usability, appropriateness, and accuracy on 9-point scales in electronic surveys and provided free text comments. A working group aggregated survey responses and incorporated them into revised definitions. Consensus was based on numeric ratings using the RAND/UCLA Appropriateness Method with prespecified definitions.Following revisions based on panelist feedback, all items received consensus in the second round of ratings. Consensus definitions were achieved for 10 core D-irAE diagnoses: ICI-vitiligo, ICI-lichen planus, ICI-psoriasis, ICI-exanthem, ICI-bullous pemphigoid, ICI-Grover's, ICI-eczematous, ICI-eruptive atypical squamous proliferation, ICI-pruritus without rash, and ICI-erosive mucocutaneous. A standard evaluation for D-irAE was also found to reach consensus, with disease-specific exceptions detailed when necessary. Each disorder's description includes further details on disease subtypes, symptoms, supportive exam findings, and three levels of diagnostic certainty (definite, probable, and possible).These consensus-driven disease definitions standardize D-irAE classification in a useable framework for multiple disciplines and will be the foundation for future work. Given consensus on their accuracy and usability from a representative panel group, we anticipate that they can be used broadly across clinical and research settings.
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Exantema , Oncólogos , Humanos , Consenso , Inhibidores de Puntos de Control Inmunológico/efectos adversos , RadioinmunoterapiaRESUMEN
This Viewpoint reviews the evidence for immune checkpoint inhibitor use in the adjuvant setting, discusses the individual and societal risks, benefits, and costs associated with immune checkpoint inhibitors, and highlights the need for more targeted patient selection approaches.
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Melanoma , Neoplasias Cutáneas , Humanos , Melanoma/terapia , Neoplasias Cutáneas/terapia , Adyuvantes Inmunológicos/uso terapéutico , Inmunoterapia , Medición de RiesgoAsunto(s)
Inmunosupresores , Humanos , Estudios Retrospectivos , Inmunosupresores/efectos adversos , Femenino , Masculino , Persona de Mediana Edad , Anciano , Adulto , Erupciones por Medicamentos/etiología , Erupciones por Medicamentos/inmunología , Agentes Inmunomoduladores/efectos adversos , Enfermedades de la Piel/inmunología , Enfermedades de la Piel/inducido químicamenteRESUMEN
BACKGROUND: Cutaneous immune-related adverse events (cirAEs) are the most common toxicities to occur in the setting of immune checkpoint inhibitor (ICI) therapy. Identifying patients who are at increased risk of developing cirAEs may improve quality of life and outcomes. OBJECTIVES: To investigate the influence of cancer type and histology on the development of cirAEs in the setting of ICI therapy and survival outcomes. METHODS: This retrospective cohort study included patients recruited between 1 December 2011 and 30 October 2020. They received ICI from 2011 to 2020 with follow-up of outcomes through October 2021. We identified 3668 recipients of ICI therapy who were seen at Massachusetts General Brigham and Dana-Farber. Of these, 669 developed cirAEs. Records that were incomplete or categories of insufficient sample size were excluded from the study cohort. Multivariate Cox proportional hazards models were used to investigate the impact of cancer organ system and histology on cirAE development, after adjusting for demographics, Charlson Comorbidity Index, ICI type, cancer stage at ICI initiation, and year of ICI initiation. Time-varying Cox proportional hazards modelling was used to examine the impact of cirAE development on mortality. RESULTS: Compared with other nonepithelial cancers (neuroendocrine, leukaemia, lymphoma, myeloma, sarcoma and central nervous system malignancies), cutaneous squamous cell carcinoma [cSCC; hazard ratio (HR) 3.57, P < 0.001], melanoma (HR 2.09, P < 0.001), head and neck adenocarcinoma (HR 2.13, P = 0.009), genitourinary transitional cell carcinoma (HR 2.15, P < 0.001) and genitourinary adenocarcinoma (HR 1.53, P = 0.037) were at significantly higher risk of cirAEs in multivariate analyses. The increased risk of cirAEs translated into an adjusted survival benefit for melanoma (HR 0.37, P < 0.001) and cSCC (HR 0.51, P = 0.011). CONCLUSIONS: The highest rate of cirAEs and subsequent survival benefits were observed in cutaneous malignancies treated with ICI therapies. This study improves our understanding of patients who are at highest risk of developing cirAEs and would, therefore, benefit from appropriate counselling and closer monitoring by their oncologists and dermatologists throughout their ICI therapy. Limitations include its retrospective nature and cohort from one geography.
Cutaneous immune-related adverse events (cirAEs) are the most common complications to occur for oncology patients treated with immune checkpoint inhibitors (ICIs). cirAEs can lead to increased use of healthcare resources and significant morbidity. Identifying patients who are at increased risk of developing cirAEs may improve quality of life and outcomes. In this study, we aimed to investigate the influence of cancer organ system and histology on the development of cirAEs and survival outcomes. To do this, we included a cohort of patients retrospectively between 1 December 2011 and 30 October 2020. We identified 3668 ICI recipients who were seen at Massachusetts General Brigham and Dana-Farber in Boston, Massachusetts. Of these, 669 people developed cirAEs. Multivariate Cox proportional hazards models were used to investigate the impact of cancer organ system and histology on cirAE development, after adjusting for demographics, Charlson Comorbidity Index, ICI type, cancer stage at ICI start, and year of ICI initiation. Time-varying Cox proportional hazards modelling was used to examine the impact of cirAE development on mortality. We found that, compared with other nonepithelial cancers, patients with cutaneous squamous cell carcinoma (cSCC) and melanoma were at significantly higher risk of cirAEs. The increased risk of cirAEs translated into an adjusted survival benefit for melanoma and cSCC. This study improves our understanding of patients who are at highest risk of developing cirAEs those with melanoma and cSCC. Therefore, many patients could benefit from appropriate counselling and close monitoring by their oncologists and dermatologists throughout ICI therapy.
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Inhibidores de Puntos de Control Inmunológico , Humanos , Masculino , Femenino , Estudios Retrospectivos , Persona de Mediana Edad , Anciano , Inhibidores de Puntos de Control Inmunológico/efectos adversos , Neoplasias/tratamiento farmacológico , Neoplasias/patología , Neoplasias/mortalidad , Neoplasias/inmunología , Neoplasias/terapia , Erupciones por Medicamentos/etiología , Erupciones por Medicamentos/patología , Erupciones por Medicamentos/epidemiología , Neoplasias Cutáneas/patología , Neoplasias Cutáneas/mortalidad , Neoplasias Cutáneas/inmunología , Neoplasias Cutáneas/tratamiento farmacológico , AdultoRESUMEN
BACKGROUND: The recent expansion of immunotherapy for stage IIB/IIC melanoma highlights a growing clinical need to identify patients at high risk of metastatic recurrence and, therefore, most likely to benefit from this therapeutic modality. OBJECTIVE: To develop time-to-event risk prediction models for melanoma metastatic recurrence. METHODS: Patients diagnosed with stage I/II primary cutaneous melanoma between 2000 and 2020 at Mass General Brigham and Dana-Farber Cancer Institute were included. Melanoma recurrence date and type were determined by chart review. Thirty clinicopathologic factors were extracted from electronic health records. Three types of time-to-event machine-learning models were evaluated internally and externally in the distant versus locoregional/nonrecurrence prediction. RESULTS: This study included 954 melanomas (155 distant, 163 locoregional, and 636 1:2 matched nonrecurrences). Distant recurrences were associated with worse survival compared to locoregional/nonrecurrences (HR: 6.21, P < .001) and to locoregional recurrences only (HR: 5.79, P < .001). The Gradient Boosting Survival model achieved the best performance (concordance index: 0.816; time-dependent AUC: 0.842; Brier score: 0.103) in the external validation. LIMITATIONS: Retrospective nature and cohort from one geography. CONCLUSIONS: These results suggest that time-to-event machine-learning models can reliably predict the metastatic recurrence from localized melanoma and help identify high-risk patients who are most likely to benefit from immunotherapy.
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Melanoma , Neoplasias Cutáneas , Humanos , Melanoma/patología , Neoplasias Cutáneas/patología , Estudios Retrospectivos , Recurrencia Local de Neoplasia/epidemiología , Recurrencia Local de Neoplasia/patologíaAsunto(s)
Neoplasias , Piel , Humanos , Neoplasias/tratamiento farmacológico , Administración CutáneaRESUMEN
BACKGROUND: Oral tetracyclines (TCNs) are commonly prescribed for acne, but they have been shown to increase the risk of hyperpigmentation, particularly in the setting of sun exposure. OBJECTIVE: We evaluated seasonal trends in TCN-associated hyperpigmentation incidence in addition to Google search trends for hyperpigmentation-related terms. METHODS: We performed a retrospective review of acne patients seen at Massachusetts General Brigham and Women’s Hospital between 1992 and 2022. We calculated the incidence of new hyperpigmentation diagnoses for each drug cohort. We also analyzed search volume of hyperpigmentation-related terms extracted from Google Trends. RESULTS: Seasonal differences in new hyperpigmentation diagnoses were identified among acne patients prescribed doxycycline (P=0.016), with peak incidence in April. In the control group of patients who had never received a TCN, diagnoses peaked in May. There were no significant seasonal differences among patients prescribed minocycline (P=0.885). There was greater search volume for hyperpigmentation-related terms in spring and summer compared to fall and winter (P<0.001). Limitations of this study include its retrospective nature and reliance on prescription and diagnosis coding data. CONCLUSIONS: Our findings support the seasonal periodicity of acne-related hyperpigmentation, underscoring the importance of photoprotection counseling for patients with acne. Additionally, doxycycline may be associated with an earlier onset of hyperpigmentation, suggesting a potential benefit of considering minocycline or other alternatives to doxycycline. J Drugs Dermatol. 2023;22(11):e9-e11 doi:10.36849/JDD.7409e.
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Acné Vulgar , Hiperpigmentación , Humanos , Femenino , Estaciones del Año , Doxiciclina/efectos adversos , Minociclina , Estudios Retrospectivos , Tetraciclina , Antibacterianos/efectos adversos , Acné Vulgar/tratamiento farmacológico , Acné Vulgar/epidemiología , Hiperpigmentación/inducido químicamente , Hiperpigmentación/diagnóstico , Hiperpigmentación/epidemiologíaRESUMEN
Background: Cancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal, and other cells within the tumor microenvironment. Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize the molecular, cellular, and spatial properties of tumor microenvironments for various malignancies. Results: This study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of tumor microenvironments using multiplexed single-cell data. Conclusions: SpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion, and metastasis.