spatialGE: A user-friendly web application to democratize spatial transcriptomics analysis.

Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, its potential is often underutilized due to the advanced data analysis and programming skills required. To address this, we present spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provides a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enables comparative analysis among samples and supports various ST technologies. We demonstrate the utility of spatialGE through its application in studying the tumor microenvironment of melanoma brain metastasis and Merkel cell carcinoma. Our results highlight the ability of spatialGE to identify spatial gene expression patterns and enrichments, providing valuable insights into the tumor microenvironment and its utility in democratizing ST data analysis for the wider scientific community.

Pre-existing skin-resident CD8 and gd T cell circuits mediate immune response in Merkel cell carcinoma and predict immunotherapy efficacy.

Merkel cell carcinoma (MCC) is an aggressive neuroendocrine skin cancer with a ~50% response rate to immune checkpoint blockade (ICB) therapy. To identify predictive biomarkers, we integrated bulk and single-cell RNA-seq with spatial transcriptomics from a cohort of 186 samples from 116 patients, including bulk RNA-seq from 14 matched pairs pre- and post-ICB. In non-responders, tumors show evidence of increased tumor proliferation, neuronal stem cell markers, and IL-1. Responders have increased type I/II interferons and pre-existing tissue resident (Trm) CD8 or Vd1 gd T cells that functionally converge with overlapping antigen-specific transcriptional programs and clonal expansion of public TCRs. Spatial transcriptomics demonstrated co-localization of T cells with B and dendritic cells, which supply chemokines and co-stimulation. Lastly, ICB significantly increased clonal expansion or recruitment of Trm and Vd1 cells in tumors specifically in responders, underscoring their therapeutic importance. These data identify potential clinically actionable biomarkers and therapeutic targets for MCC.

Impact of insomnia on ovarian cancer risk and survival: a Mendelian randomization study.

BACKGROUND: Insomnia is the most common sleep disorder in patients with epithelial ovarian cancer (EOC). We investigated the causal association between genetically predicted insomnia and EOC risk and survival through a two-sample Mendelian randomization (MR) study. METHODS: Insomnia was proxied using genetic variants identified in a genome-wide association study (GWAS) meta-analysis of UK Biobank and 23andMe. Using genetic associations with EOC risk and overall survival from the Ovarian Cancer Association Consortium (OCAC) GWAS in 66,450 women (over 11,000 cases with clinical follow-up), we performed Iterative Mendelian Randomization and Pleiotropy (IMRP) analysis followed by a set of sensitivity analyses. Genetic associations with survival and response to treatment in ovarian cancer study of The Cancer Genome Atlas (TCGA) were estimated controlling for chemotherapy and clinical factors. FINDINGS: Insomnia was associated with higher risk of endometrioid EOC (OR = 1.60, 95% CI 1.05-2.45) and lower risk of high-grade serous EOC (HGSOC) and clear cell EOC (OR = 0.79 and 0.48, 95% CI 0.63-1.00 and 0.27-0.86, respectively). In survival analysis, insomnia was associated with shorter survival of invasive EOC (OR = 1.45, 95% CI 1.13-1.87) and HGSOC (OR = 1.4, 95% CI 1.04-1.89), which was attenuated after adjustment for body mass index and reproductive age. Insomnia was associated with reduced survival in TCGA HGSOC cases who received standard chemotherapy (OR = 2.48, 95% CI 1.13-5.42), but was attenuated after adjustment for clinical factors. INTERPRETATION: This study supports the impact of insomnia on EOC risk and survival, suggesting treatments targeting insomnia could be pivotal for prevention and improving patient survival. FUNDING: National Institutes of Health, National Cancer Institute. Full funding details are provided in acknowledgments.

Spectrum of somatic mutational features of colorectal tumors in ancestrally diverse populations.

Ancestrally diverse and admixed populations, including the Hispanic/Latino/a/x/e community, are underrepresented in cancer genetic and genomic studies. Leveraging the Latino Colorectal Cancer Consortium, we analyzed whole exome sequencing data on tumor/normal pairs from 718 individuals with colorectal cancer (128 Latino, 469 non-Latino) to map somatic mutational features by ethnicity and genetic ancestry. Global proportions of African, East Asian, European, and Native American ancestries were estimated using ADMIXTURE. Associations between global genetic ancestry and somatic mutational features across genes were examined using logistic regression. TP53 , APC , and KRAS were the most recurrently mutated genes. Compared to non-Latino individuals, tumors from Latino individuals had fewer KRAS (OR=0.64, 95%CI=0.41-0.97, p=0.037) and PIK3CA mutations (OR=0.55, 95%CI=0.31-0.98, p=0.043). Genetic ancestry was associated with presence of somatic mutations in 39 genes (FDR-adjusted LRT p<0.05). Among these genes, a 10% increase in African ancestry was associated with significantly higher odds of mutation in KNCN (OR=1.34, 95%CI=1.09-1.66, p=5.74×10 -3 ) and TMEM184B (OR=1.53, 95%CI=1.10-2.12, p=0.011). Among RMGs, we found evidence of association between genetic ancestry and mutation status in CDC27 (LRT p=0.0084) and between SMAD2 mutation status and AFR ancestry (OR=1.14, 95%CI=1.00-1.30, p=0.046). Ancestry was not associated with tumor mutational burden. Individuals with above-average Native American ancestry had a lower frequency of microsatellite instable (MSI-H) vs microsatellite stable tumors (OR=0.45, 95%CI=0.21-0.99, p=0.048). Our findings provide new knowledge about the relationship between ancestral haplotypes and somatic mutational profiles that may be useful in developing precision medicine approaches and provide additional insight into genomic contributions to cancer disparities. Significance: Our data in ancestrally diverse populations adds essential information to characterize mutational features in the colorectal cancer genome. These results will help enhance equity in the development of precision medicine strategies.

Lifetime Exposure to Cigarette Smoke, B-Cell Tumor Immune Infiltration, and Immunoglobulin Abundance in Ovarian Tumors.

BACKGROUND: Cigarette smoke exposure has been linked to systemic immune dysfunction, including for B-cell and immunoglobulin (Ig) production, and poor outcomes in patients with ovarian cancer. No study has evaluated the impact of smoke exposure across the life-course on B-cell infiltration and Ig abundance in ovarian tumors. METHODS: We measured markers of B and plasma cells and Ig isotypes using multiplex immunofluorescence on 395 ovarian cancer tumors in the Nurses' Health Study (NHS)/NHSII. We conducted beta-binomial analyses evaluating odds ratios (OR) and 95% confidence intervals (CI) for positivity of immune markers by cigarette exposure among cases and Cox proportional hazards models to evaluate hazard ratios (HR) and 95% CI for developing tumors with low (

WITHDRAWN: Impact of spatial clustering of cytotoxic and tumor infiltrating lymphocytes on overall survival in women with high grade serous ovarian cancer.

The authors have withdrawn their manuscript owing to incorrect handling of multiple measures in the survival analyses. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

Statistical analysis of single-cell protein data.

Immune modulation is considered a hallmark of cancer initiation and progression, with immune cell density being consistently associated with clinical outcomes of individuals with cancer. Multiplex immunofluorescence (mIF) microscopy combined with automated image analysis is a novel and increasingly used technique that allows for the assessment and visualization of the tumor microenvironment (TME). Recently, application of this new technology to tissue microarrays (TMAs) or whole tissue sections from large cancer studies has been used to characterize different cell populations in the TME with enhanced reproducibility and accuracy. Generally, mIF data has been used to examine the presence and abundance of immune cells in the tumor and stroma compartments; however, this aggregate measure assumes uniform patterns of immune cells throughout the TME and overlooks spatial heterogeneity. Recently, the spatial contexture of the TME has been explored with a variety of statistical methods. In this PSB workshop, speakers will present some of the state-of-the-art statistical methods for assessing the TIME from mIF data.

Modeling phenotypic heterogeneity towards evolutionarily inspired osteosarcoma therapy.

Osteosarcoma is the most common bone sarcoma in children and young adults. While universally delivered, chemotherapy only benefits roughly half of patients with localized disease. Increasingly, intratumoral heterogeneity is recognized as a source of therapeutic resistance. In this study, we develop and evaluate an in vitro model of osteosarcoma heterogeneity based on phenotype and genotype. Cancer cell populations vary in their environment-specific growth rates and in their sensitivity to chemotherapy. We present the genotypic and phenotypic characterization of an osteosarcoma cell line panel with a focus on co-cultures of the most phenotypically divergent cell lines, 143B and SAOS2. Modest environmental (pH, glutamine) or chemical perturbations dramatically shift the success and composition of cell lines. We demonstrate that in nutrient rich culture conditions 143B outcompetes SAOS2. But, under nutrient deprivation or conventional chemotherapy, SAOS2 growth can be favored in spheroids. Importantly, when the simplest heterogeneity state is evaluated, a two-cell line coculture, perturbations that affect the faster growing cell line have only a modest effect on final spheroid size. Thus the only evaluated therapies to eliminate the spheroids were by switching therapies from a first strike to a second strike. This extensively characterized, widely available system, can be modeled and scaled to allow for improved strategies to anticipate resistance in osteosarcoma due to heterogeneity.

Increased spatial coupling of integrin and collagen IV in the immunoresistant clear cell renal cell carcinoma tumor microenvironment.

Background: Immunotherapy (IO) has improved survival for patients with advanced clear cell renal cell carcinoma (ccRCC), but resistance to therapy develops in most patients. We use cellular-resolution spatial transcriptomics in patients with IO naïve and IO exposed primary ccRCC tumors to better understand IO resistance. Spatial molecular imaging (SMI) was obtained for tumor and adjacent stroma samples. Spatial gene set enrichment analysis (GSEA) and autocorrelation (coupling with high expression) of ligand-receptor transcript pairs were assessed. Multiplex immunofluorescence (mIF) validation was used for significant autocorrelative findings and the cancer genome atlas (TCGA) and the clinical proteomic tumor analysis consortium (CPTAC) databases were queried to assess bulk RNA expression and proteomic correlates. Results: 21 patient samples underwent SMI. Viable tumors following IO harbored more stromal CD8+ T cells and neutrophils than IO naïve tumors. YES1 was significantly upregulated in IO exposed tumor cells. The epithelial-mesenchymal transition pathway was enriched on spatial GSEA and the associated transcript pair COL4A1-ITGAV had significantly higher autocorrelation in the stroma. Fibroblasts, tumor cells, and endothelium had the relative highest expression. More integrin αV+ cells were seen in IO exposed stroma on mIF validation. Compared to other cancers in TCGA, ccRCC tumors have the highest expression of both COL4A1 and ITGAV. In CPTAC, collagen IV protein was more abundant in advanced stages of disease. Conclusions: On spatial transcriptomics, COL4A1 and ITGAV were more autocorrelated in IO-exposed stroma compared to IO-naïve tumors, with high expression amongst fibroblasts, tumor cells, and endothelium. Integrin represents a potential therapeutic target in IO treated ccRCC.

Gene partners of the EWSR1 fusion may represent molecularly distinct entities.

EWSR1 fusions are highly promiscuous and are associated with unique malignancies, clinical phenotypes, and molecular subtypes. However, rare fusion partners (RFP) of EWSR1 has not been well described. Here, we conducted a cross-sectional, retrospective study of 1,140 unique tumors harboring EWSR1 fusions. We identified 64 unique fusion partners. RFPs were identified more often in adults than children. Alterations in cell cycle control and DNA damage response genes as driving the differences between fusion partners. Potentially clinically actionable genomic variants were more prevalent in tumors harboring RFP than common fusions. While the data presented here is limited, tumors harboring RFP of EWSR1 may represent molecularly distinct entities and may benefit from further molecular testing to identify targeted therapeutic options.

Integrating pharmacogenomic testing into paired germline and somatic genomic testing in patients with cancer.

Precision medicine has revolutionized clinical care for patients with cancer through the development of targeted therapy, identification of inherited cancer predisposition syndromes and the use of pharmacogenetics to optimize pharmacotherapy for anticancer drugs and supportive care medications. While germline (patient) and somatic (tumor) genomic testing have evolved separately, recent interest in paired germline/somatic testing has led to an increase in integrated genomic testing workflows. However, paired germline/somatic testing has generally lacked the incorporation of germline pharmacogenomics. Integrating pharmacogenomics into paired germline/somatic genomic testing would be an efficient method for increasing access to pharmacogenomic testing. In this perspective, the authors argue for the benefits of implementing a comprehensive approach integrating somatic and germline testing that is inclusive of pharmacogenomics in clinical practice.

Associations between prediagnostic aspirin use and ovarian tumor gene expression.

BACKGROUND: Aspirin use has been associated with reduced ovarian cancer risk, yet the underlying biological mechanisms are not fully understood. To gain mechanistic insights, we assessed the association between prediagnosis low and regular-dose aspirin use and gene expression profiles in ovarian tumors. METHODS: RNA sequencing was performed on high-grade serous, poorly differentiated, and high-grade endometrioid ovarian cancer tumors from the Nurses' Health Study (NHS), NHSII, and New England Case-Control Study (n = 92 cases for low, 153 cases for regular-dose aspirin). Linear regression identified differentially expressed genes associated with aspirin use, adjusted for birth decade and cohort. False discovery rates (FDR) were used to account for multiple testing and gene set enrichment analysis was used to identify biological pathways. RESULTS: No individual genes were significantly differentially expressed in ovarian tumors in low or regular-dose aspirin users accounting for multiple comparisons. However, current versus never use of low-dose aspirin was associated with upregulation of immune pathways (e.g., allograft rejection, FDR = 5.8 × 10-10 ; interferon-gamma response, FDR = 2.0 × 10-4 ) and downregulation of estrogen response pathways (e.g., estrogen response late, FDR = 4.9 × 10-8 ). Ovarian tumors from current regular aspirin users versus never users were also associated with upregulation in interferon pathways (FDR <1.5 × 10-4 ) and downregulation of multiple extracellular matrix (ECM) architecture pathways (e.g., ECM organization, 4.7 × 10-8 ). CONCLUSION: Our results suggest low and regular-dose aspirin may impair ovarian tumorigenesis in part via enhancing adaptive immune response and decreasing metastatic potential supporting the likely differential effects on ovarian carcinogenesis and progression by dose of aspirin.

The relationship of lifetime history of depression on the ovarian tumor immune microenvironment.

BACKGROUND: Depression is associated with a higher ovarian cancer risk. Prior work suggests that depression can lead to systemic immune suppression, which could potentially alter the anti-tumor immune response. METHODS: We evaluated the association of pre-diagnosis depression with features of the anti-tumor immune response, including T and B cells and immunoglobulins, among women with ovarian tumor tissue collected in three studies, the Nurses' Health Study (NHS; n = 237), NHSII (n = 137) and New England Case-Control Study (NECC; n = 215). Women reporting depressive symptoms above a clinically relevant cut-point, antidepressant use, or physician diagnosis of depression at any time prior to diagnosis of ovarian cancer were considered to have pre-diagnosis depression. Multiplex immunofluorescence was performed on tumor tissue microarrays to measure immune cell infiltration. In pooled analyses, we estimated odds ratios (OR) and 95% confidence intervals (CI) for the positivity of tumor immune cells using a beta-binomial model comparing those with and without depression. We used Bonferroni corrections to adjust for multiple comparisons. RESULTS: We observed no statistically significant association between depression status and any immune markers at the Bonferroni corrected p-value of 0.0045; however, several immune markers were significant at a nominal p-value of 0.05. Specifically, there were increased odds of having recently activated cytotoxic (CD3+CD8+CD69+) and exhausted-like T cells (CD3+Lag3+) in tumors of women with vs. without depression (OR = 1.36, 95 %CI = 1.09-1.69 and OR = 1.24, 95 %CI = 1.01-1.53, respectively). Associations were comparable when considering high grade serous tumors only (comparable ORs = 1.33, 95 %CI = 1.05-1.69 and OR = 1.25, 95 %CI = 0.99-1.58, respectively). There were decreased odds of having tumor infiltrating plasma cells (CD138+) in women with vs. without depression (OR = 0.54, 95 %CI = 0.33-0.90), which was similar among high grade serous carcinomas, although not statistically significant. Depression was also related to decreased odds of having naïve and memory B cells (CD20+: OR = 0.54, 95 %CI = 0.30-0.98) and increased odds of IgG (OR = 1.22, 95 %CI = 0.97-1.53) in high grade serous carcinomas. CONCLUSION: Our results provide suggestive evidence that depression may influence ovarian cancer outcomes through changes in the tumor immune microenvironment, including increasing T cell activation and exhaustion and reducing antibody-producing B cells. Further studies with clinical measures of depression and larger samples are needed to confirm these results.

A harmonized resource of integrated prostate cancer clinical, -omic, and signature features.

Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses across multiple, independent patient cohorts. In addition, derived features, such as estimates of cell composition, risk scores, and androgen receptor (AR) scores, can be used to develop novel hypotheses leveraging existing multi-omic datasets. The full potential of such data is yet to be realized as independent datasets exist in different repositories, have been processed using different pipelines, and derived and clinical features are often not provided or  not standardized. Here, we present the curatedPCaData R package, a harmonized data resource representing >2900 primary tumor, >200 normal tissue, and >500 metastatic PCa samples across 19 datasets processed using standardized pipelines with updated gene annotations. We show that meta-analysis across harmonized studies has great potential for robust and clinically meaningful insights. curatedPCaData is an open and accessible community resource with code made available for reproducibility.

Statistical Methods for Integrative Clustering of Multi-omics Data.

Cancers are heterogeneous diseases caused by accumulated mutations or abnormal alterations at multi-levels of biological processes including genomics, epigenomics, transcriptomics, and proteomics. There is a great clinical interest in identifying cancer molecular subtypes for disease prognosis and personalized medicine. Integrative clustering is a powerful unsupervised learning method that has been increasingly used to identify cancer molecular subtypes using multi-omics data including somatic mutations, DNA copy numbers, DNA methylation, and gene expression. Integrative clustering methods are generally classified into model-based or nonparametric approaches. In this chapter, we will give an overview of the frequently used model-based methods, including iCluster, iClusterPlus, and iClusterBayes, and the nonparametric method, integrative nonnegative matrix factorization (intNMF). We will use the integrative analyses of uveal melanoma and lower-grade glioma to illustrate these representative methods. Finally, we will discuss the strengths and limitations of these representative methods and give suggestions for performing integrative analyses of cancer multi-omics data in practice.

Measurement of Ovarian Tumor Immune Profiles by Multiplex Immunohistochemistry: Implications for Epidemiologic Studies.

BACKGROUND: Despite the immunogenic nature of many ovarian tumors, treatment with immune checkpoint therapies has not led to substantial improvements in ovarian cancer survival. To advance population-level research on the ovarian tumor immune microenvironment, it is critical to understand methodologic issues related to measurement of immune cells on tissue microarrays (TMA) using multiplex immunofluorescence (mIF) assays. METHODS: In two prospective cohorts, we collected formalin-fixed, paraffin-embedded ovarian tumors from 486 cases and created seven TMAs. We measured T cells, including several sub-populations, and immune checkpoint markers on the TMAs using two mIF panels. We used Spearman correlations, Fisher exact tests, and multivariable-adjusted beta-binomial models to evaluate factors related to immune cell measurements in TMA tumor cores. RESULTS: Between-core correlations of intratumoral immune markers ranged from 0.52 to 0.72, with more common markers (e.g., CD3+, CD3+CD8+) having higher correlations. Correlations of immune cell markers between the whole core, tumor area, and stromal area were high (range 0.69-0.97). In multivariable-adjusted models, odds of T-cell positivity were lower in clear cell and mucinous versus type II tumors (ORs, 0.13-0.48) and, for several sub-populations, were lower in older tissue (sample age > 30 versus ≤ 10 years; OR, 0.11-0.32). CONCLUSIONS: Overall, high correlations between cores for immune markers measured via mIF support the use of TMAs in studying ovarian tumor immune infiltration, although very old samples may have reduced antigenicity. IMPACT: Future epidemiologic studies should evaluate differences in the tumor immune response by histotype and identify modifiable factors that may alter the tumor immune microenvironment.

PARP1 and POLD2 as prognostic biomarkers for multiple myeloma in autologous stem cell transplant.

Multiple Myeloma (MM) is an incurable plasma cell malignancy often treated by autologous stem cell transplant (ASCT). Clinical response to ASCT has been associated with DNA repair efficiency. Here we interrogated the role of the base excision DNA repair (BER) pathway in MM response to ASCT. Across 450 clinical samples and six disease stages, expression levels of genes in the BER pathway were found to be highly upregulated during the development of MM. In a separate cohort of 559 patients with MM treated with ASCT, expression of BER pathway members MPG and PARP3 was positively associated with overall survival (OS) while expression of PARP1, POLD1, and POLD2 was negatively associated with OS. In a validation cohort of 356 patients with MM treated with ASCT, PARP1 and POLD2 findings were replicated. In patients with MM who never received ASCT (n=319), PARP1 and POLD2 were not associated with OS, suggesting that the prognostic effect of these genes may be treatment-dependent. In preclinical models of MM, synergy was observed in anti-tumor activity when poly (ADPribose) polymerase (PARP) inhibitors (olaparib, talazoparib) were used in combination with melphalan. The negative prognosis associated with PARP1 and POLD2 expression along with the apparent melphalan-sensitizing effect of PARP inhibition may suggest this pathway as a potential biomarker in patients with MM in the setting of ASCT. Further understanding of the role of the BER pathway in MM is vital to improve therapeutic strategies related to ASCT.

Predictors of residual disease after debulking surgery in advanced stage ovarian cancer.

Objective: Optimal debulking with no macroscopic residual disease strongly predicts ovarian cancer survival. The ability to predict likelihood of optimal debulking, which may be partially dependent on tumor biology, could inform clinical decision-making regarding use of neoadjuvant chemotherapy. Thus, we developed a prediction model including epidemiological factors and tumor markers of residual disease after primary debulking surgery. Methods: Univariate analyses examined associations of 11 pre-diagnosis epidemiologic factors (n=593) and 24 tumor markers (n=204) with debulking status among incident, high-stage, epithelial ovarian cancer cases from the Nurses' Health Studies and New England Case Control study. We used Bayesian model averaging (BMA) to develop prediction models of optimal debulking with 5x5-fold cross-validation and calculated the area under the curve (AUC). Results: Current aspirin use was associated with lower odds of optimal debulking compared to never use (OR=0.52, 95%CI=0.31-0.86) and two tissue markers, ADRB2 (OR=2.21, 95%CI=1.23-4.41) and FAP (OR=1.91, 95%CI=1.24-3.05) were associated with increased odds of optimal debulking. The BMA selected aspirin, parity, and menopausal status as the epidemiologic/clinical predictors with the posterior effect probability ≥20%. While the prediction model with epidemiologic/clinical predictors had low performance (average AUC=0.49), the model adding tissue biomarkers showed improved, but weak, performance (average AUC=0.62). Conclusions: Addition of ovarian tumor tissue markers to our multivariable prediction models based on epidemiologic/clinical data slightly improved the model performance, suggesting debulking status may be in part driven by tumor characteristics. Larger studies are warranted to identify those at high risk of poor surgical outcomes informing personalized treatment.

Pilot Study in Investigating Material Financial Toxicity Markers by Age in Cancer Patients.

Purpose: Studies have shown that financial toxicity can reduce survival, decrease quality of life, and reduce compliance with treatments. The aim of this retrospective study was to investigate material markers of financial toxicity, including insurance coverage, financial assistance, and balances due among adolescent and young adult (AYA) (18-39), adult (40-64), and senior adult (>65) patients with a sarcoma diagnosis after the Affordable Care Act became effective. Methods: This study performed a retrospective analysis of possible indicators within the material domain of financial toxicity in sarcoma patients, a common diagnosis in young adult patients. Indicators of financial toxicity included: insurance status and number of insurances, charity care, accessing financing options, or having an unpaid balance referred to a collection's agency. Results: The cumulative charges per patient were similar between AYA, adult, and senior adult populations at an average of $194,329 (standard deviation [SD] = $321,425), $236,724 (SD = $368,345), and $188,030 (SD = $271,191), respectively. AYA patients were more likely than adult and senior adult patients to have Medicaid coverage (income-based government insurance) (22.1% vs. 8.4% vs. 1.2%), receive charity care (5.3% vs. 2.6% vs. 1.2%), or have a balance referred to a collection's agency (9.2% vs. 5.8% vs. 1.2%). Conclusions: This study suggests that younger cancer patients are more likely to suffer material financial strain and additional financial resources may need to be made available to ensure they can receive care without an increase of financial toxicity markers and undue financial stress.

A phase I trial of metformin in combination with vincristine, irinotecan, and temozolomide in children with relapsed or refractory solid and central nervous system tumors: A report from the national pediatric cancer foundation.

BACKGROUND: Patients with relapsed and refractory solid and central nervous system (CNS) tumors have poor outcomes and need novel therapeutic options. Vincristine, irinotecan, and temozolomide (VIT) is a common chemotherapy regimen in relapsed pediatric tumors with an established toxicity profile. Metformin shows preclinical anti-cancer activity through multiple pathways. METHODS: The objective of this Phase I trial was to establish the maximum tolerated dose (MTD) and recommended Phase II dose (RP2D) of metformin in combination with VIT in children with relapsed and refractory solid and CNS tumors. A 3 + 3 design was used to test the addition of metformin at five dose levels (666, 999, 1333, 1666, and 2000 mg/m2 /day). Therapy toxicity, pharmacokinetics, and radiologic response to treatment were evaluated. RESULTS: Twenty-six patients (median age 13 years, range 2-18 years) were enrolled with 22 evaluable for toxicity. The most common diagnoses were Ewing sarcoma (n = 8), rhabdomyosarcoma (n = 3) and atypical teratoid/rhabdoid tumor (n = 3). The MTD was exceeded at Dose Level 5 due to two dose-limiting toxicities; both were Grade 3 diarrhea requiring prolonged hospitalization and intravenous fluids. The MTD was not determined due to study closure with less than six patients enrolled at Dose Level 4. Frequently observed toxicities were gastrointestinal (most notably diarrhea) and hematologic. Amongst 16 patients evaluable for best overall response, there was one complete response (Ewing sarcoma), three partial responses (Ewing sarcoma, glioblastoma multiforme, and alveolar rhabdomyosarcoma), and five patients with stable disease. CONCLUSIONS: The MTD of VIT with metformin was not determined due to premature study closure. We recommend an RP2D of Dose Level 4, 1666 mg/m2 /day. Radiographic responses were seen in multiple tumor types. Further evaluation for efficacy could be investigated in a Phase II trial.