The classification of melanocytic gene signatures.

Gene expression profiling technologies have revolutionized cell biology, enabling researchers to identify gene signatures linked to various biological attributes of melanomas, such as pigmentation status, differentiation state, proliferative versus invasive capacity, and disease progression. Although the discovery of gene signatures has significantly enhanced our understanding of melanocytic phenotypes, reconciling the numerous signatures reported across independent studies and different profiling platforms remains a challenge. Current methods for classifying melanocytic gene signatures depend on exact gene overlap and comparison with unstandardized baseline transcriptomes. In this study, we aimed to categorize published gene signatures into clusters based on their similar patterns of expression across clinical cutaneous melanoma specimens. We analyzed nearly 800 melanoma samples from six gene expression repositories and developed a classification framework for gene signatures that is resilient against biases in gene identification across profiling platforms and inconsistencies in baseline standards. Using 39 frequently cited published gene signatures, our analysis revealed seven principal classes of gene signatures that correlate with previously identified phenotypes: Differentiated, Mitotic/MYC, AXL, Amelanotic, Neuro, Hypometabolic, and Invasive. Each class is consistent with the phenotypes that the constituent gene signatures represent, and our classification method does not rely on overlapping genes between signatures. To facilitate broader application, we created WIMMS (what is my melanocytic signature, available at https://wimms.tanlab.org/), a user-friendly web application. WIMMS allows users to categorize any gene signature, determining its relationship to predominantly cited signatures and its representation within the seven principal classes.

The Tumor Microbiome as a Predictor of Outcomes in Patients with Metastatic Melanoma Treated with Immune Checkpoint Inhibitors.

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and its potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICI). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA sequencing (RNA-seq) was conducted on the formalin-fixed, paraffin-embedded and fresh frozen tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival >24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The age of the 71 patients with metastatic melanoma ranged from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy-responsive versus nonresponsive tumors. Responders showed significant enrichment of bacteriophages in the phylum Uroviricota, and nonresponders showed enrichment of several bacteria, including Campylobacter jejuni. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs. SIGNIFICANCE: We analyzed the tumor microbiome and interactions with genes and pathways in metastatic melanoma treated with immunotherapy and identified several microbes associated with immunotherapy response and immune-related gene expression signatures. Machine learning models that combined microbe abundances and gene expression outperformed models using either dataset alone in predicting immunotherapy responses.

Exploring the Landscape of Immune Checkpoint Inhibitor-Induced Adverse Events Through Big Data Mining of Pan-Cancer Clinical Trials.

PURPOSE: Immune checkpoint inhibitors (ICIs) have significantly improved the survival of patients with cancer and provided long-term durable benefit. However, ICI-treated patients develop a range of toxicities known as immune-related adverse events (irAEs), which could compromise clinical benefits from these treatments. As the incidence and spectrum of irAEs differs across cancer types and ICI agents, it is imperative to characterize the incidence and spectrum of irAEs in a pan-cancer cohort to aid clinical management. DESIGN: We queried >400 000 trials registered at ClinicalTrials.gov and retrieved a comprehensive pan-cancer database of 71 087 ICI-treated participants from 19 cancer types and 7 ICI agents. We performed data harmonization and cleaning of these trial results into 293 harmonized adverse event categories using Medical Dictionary for Regulatory Activities. RESULTS: We developed irAExplorer (https://irae.tanlab.org), an interactive database that focuses on adverse events in patients administered with ICIs from big data mining. irAExplorer encompasses 71 087 distinct clinical trial participants from 343 clinical trials across 19 cancer types with well-annotated ICI treatment regimens and harmonized adverse event categories. We demonstrated a few of the irAE analyses through irAExplorer and highlighted some associations between treatment- or cancer-specific irAEs. CONCLUSION: The irAExplorer is a user-friendly resource that offers exploration, validation, and discovery of treatment- or cancer-specific irAEs across pan-cancer cohorts. We envision that irAExplorer can serve as a valuable resource to cross-validate users' internal datasets to increase the robustness of their findings.

A Bioinformatics Tool for Identifying Intratumoral Microbes from the ORIEN Dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10%-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, microbial graph attention (MEGA), to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of nine cancer centers in the Oncology Research Information Exchange Network. This package has three unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2,704 tumor RNA sequencing samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors. SIGNIFICANCE: Studying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep learning tool, MEGA, to refine the organisms that interact with tumors.

Deciphering the Tumor-Immune-Microbe Interactions in HPV-Negative Head and Neck Cancer.

Patients with human papillomavirus-negative head and neck squamous cell carcinoma (HPV-negative HNSCC) have worse outcomes than HPV-positive HNSCC. In our study, we used a published dataset and investigated the microbes enriched in molecularly classified tumor groups. We showed that microbial signatures could distinguish Hypoxia/Immune phenotypes similar to the gene expression signatures. Furthermore, we identified three highly-correlated microbes with immune processes that are crucial for immunotherapy response. The survival of patients in a molecularly heterogenous group shows significant differences based on the co-abundance of the three microbes. Overall, we present evidence that tumor-associated microbiota are critical components of the tumor ecosystem that may impact tumor microenvironment and immunotherapy response. The results of our study warrant future investigation to experimentally validate the conclusions, which have significant impacts on clinical decision-making, such as treatment selection.

The tumor microbiome as a predictor of outcomes in patients with metastatic melanoma treated with immune checkpoint inhibitors.

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICIs). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA-seq was conducted on the formalin-fixed paraffin-embedded (FFPE) tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival ≥24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The 71 patients with metastatic melanoma ranged in age from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy responsive versus non-responsive tumors. Responders showed significant enrichment of several microbes including Fusobacterium nucleatum, and non-responders showed enrichment of fungi, as well as several bacteria. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs.

A bioinformatics tool for identifying intratumoral microbes from the ORIEN dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, MEGA, to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of 9 cancer centers in the Oncology Research Information Exchange Network (ORIEN). This package has 3 unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2704 tumor RNA-seq samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors.

Systematic evaluation of the predictive gene expression signatures of immune checkpoint inhibitors in metastatic melanoma.

Advances in immunotherapy, including immune checkpoint inhibitors (ICIs), have transformed the standard of care for many types of cancer including melanoma. ICIs have improved the overall outcome of melanoma patients; however, a significant proportion of patients suffer from primary or secondary tumor resistance. Therefore, there is an urgent need to develop predictive biomarkers to better select patients for ICI therapy. Numerous biomarkers that predict the response of melanoma to ICIs have been investigated, including biomarker signatures based on genomics or transcriptomics. Most of these predictive biomarkers have not been systematically evaluated across different cohorts to determine the reproducibility of these signatures in metastatic melanoma. We evaluated 28 previously published predictive biomarkers of ICIs based on gene expression signatures in eight previously published studies with available RNA-sequencing data in public repositories. We found that signatures related to IFN-γ-responsive genes, T and B cell markers, and chemokines in the tumor immune microenvironment are generally predictive of response to ICIs in these patients. In addition, we identified that these predictive biomarkers have higher predictive values in on-treatment samples as compared to pretreatment samples in metastatic melanoma. The most frequently overlapping genes among the top 18 predictive signatures were CXCL10, CXCL9, PRF1, RANTES, IFNG, HLA-DRA, GZMB, and CD8A. From gene set enrichment analysis and cell type deconvolution, we estimated that the tumors of responders were enriched with infiltrating cytotoxic T-cells and other immune cells and the upregulation of genes related to interferon-γ signaling. Conversely, the tumors of non-responders were enriched with stromal-related cell types such as fibroblasts and myofibroblasts, as well as enrichment with T helper 17 cell types across all cohorts. In summary, our approach of validating and integrating multi-omics data can help guide future biomarker development in the field of ICIs and serve the quest for a more personalized therapeutic approach for melanoma patients.

Knowledge and tools to enhance resilience of beef grazing systems for sustainable animal protein production.

Ruminant livestock provides meat and dairy products that sustain health and livelihood for much of the world's population. Grazing lands that support ruminant livestock provide numerous ecosystem services, including provision of food, water, and genetic resources; climate and water regulation; support of soil formation; nutrient cycling; and cultural services. In the U.S. southern Great Plains, beef production on pastures, rangelands, and hay is a major economic activity. The region's climate is characterized by extremes of heat and cold and extremes of drought and flooding. Grazing lands occupy a large portion of the region's land, significantly affecting carbon, nitrogen, and water budgets. To understand vulnerabilities and enhance resilience of beef production, a multi-institutional Coordinated Agricultural Project (CAP), the "grazing CAP," was established. Integrative research and extension spanning biophysical, socioeconomic, and agricultural disciplines address management effects on productivity and environmental footprints of production systems. Knowledge and tools being developed will allow farmers and ranchers to evaluate risks and increase resilience to dynamic conditions. The knowledge and tools developed will also have relevance to grazing lands in semiarid and subhumid regions of the world.

Quantifying phosphorus levels in soils, plants, surface water, and shallow groundwater associated with bahiagrass-based pastures.

BACKGROUND, AIM, AND SCOPE: Recent assessments of water quality status have identified eutrophication as one of the major causes of water quality 'impairment' not only in the USA but also around the world. In most cases, eutrophication has accelerated by increased inputs of phosphorus due to intensification of crop and animal production systems since the early 1990 s. Despite substantial measurements using both laboratory and field techniques, little is known about the spatial and temporal variability of phosphorus dynamics across landscapes, especially in agricultural landscapes with cow-calf operations. Critical to determining environmental balance and accountability is an understanding of phosphorus excreted by animals, phosphorus removal by plants, acceptable losses of phosphorus within the manure management and crop production systems into soil and waters, and export of phosphorus off-farm. Further research effort on optimizing forage-based cow-calf operations to improve pasture sustainability and protect water quality is therefore warranted. We hypothesized that properly managed cow-calf operations in subtropical agroecosystem would not be major contributors to excess loads of phosphorus in surface and ground water. To verify our hypothesis, we examined the comparative concentrations of total phosphorus among soils, forage, surface water, and groundwater beneath bahiagrass-based pastures with cow-calf operations in central Florida, USA. MATERIALS AND METHODS: Soil samples were collected at 0-20; 20-40, 40-60, and 60-100 cm across the landscape (top slope, middle slope, and bottom slope) of 8 ha pasture in the fall and spring of 2004 to 2006. Forage availability and phosphorus uptake of bahiagrass were also measured from the top slope, middle slope, and bottom slope. Bi-weekly (2004-2006) groundwater and surface water samples were taken from wells located at top slope, middle slope, and bottom slope, and from the runoff/seepage area. Concentrations of phosphorus in soils, forage, surface water, and shallow groundwater beneath a bahiagrass-based pasture and forage availability at four different landscape positions and soil depth (for soil samples only) in 2004, 2005, and 2006 were analyzed statistically following a two-way analysis of variance using the SAS PROC general linear models model. Where the F-test indicated a significant (p

Profile of the bovine acute-phase response following an intravenous bolus-dose lipopolysaccharide challenge.

Our objective was to characterize further the acute-phase response following endotoxin (i.e. lipopolysaccharide; LPS) exposure in the bovine. Nine pure-bred Angus castrated males (i.e. steers; average body weight=299+/-5 kg) were used in a randomized complete block design in environmentally controlled chambers, set at thermoneutral level, to characterize the acute physiological, endocrine, immune, and acute-phase protein responses following an i.v. bolus administration of 2.5 microg of LPS/kg body weight. One day before administration of LPS, all steers were fitted with an indwelling jugular vein catheter for serial blood collection. Blood samples were collected at 30-min intervals from -2 h to 8 h relative to the LPS challenge (time 0), and serum was harvested and stored at -80 degrees C until analyzed for concentrations of cortisol, pro-inflammatory cytokines, and acute-phase proteins. Indicators of thermal status (i.e. rectal temperature, ruminal temperature, respiration rate, sweat rate, and skin temperatures) were measured at 30-min intervals from -1 h to 6 h relative to the challenge. Endotoxin exposure increased (P<0.05) serum concentrations of cortisol, tumor necrosis factor-alpha (TNF-alpha), interleukin 1-beta (IL-1beta), IL-6, interferon-gamma (IFN-gamma), and serum amyloid A. Respiration rate, rectal temperature, and rump skin temperature also were increased (P<0.05) following LPS administration. Endotoxin exposure dramatically decreased ear skin temperature (P=0.002), but tended to increase (P<0.10) ruminal temperature, shoulder skin temperature, and shoulder sweat rate. Serum concentrations of acid soluble protein, alpha-acid glycoprotein, IL-4 and IL-2, and rump sweat rate were not altered (P>0.24) by the challenge. To our knowledge, this report is the most complete characterization of the bovine acute-phase response to a bolus-dose endotoxin challenge conducted under thermoneutral conditions and should provide foundation data for future research.

Land application of carbonatic lake-dredged materials: effects on soil quality and forage productivity.

The ability to reuse carbonatic lake-dredged materials (CLDM) for agricultural purposes is important because it reduces offshore disposal and provides an alternative to disposal of the materials in landfills that are already overtaxed. A four-year (2001 to 2005) study on land application of CLDM as an option for disposal was conducted on a beef cattle pasture in south central Florida. The objectives of this study were (i) to assess CLDM as a soil amendment to improve quality of sandy soils in most subtropical beef cattle pastures and (ii) to determine the effect of CLDM on productivity and nutritive values of bahiagrass (BG, Paspalum notatum Flügge) in subtropical beef cattle pasture. The five treatment combinations arranged in randomized complete block design were represented by plots with different ratios (R) of natural soil (NS) to CLDM: R1 (1000 g kg(-1):0 g kg(-1)); R2 (750 g kg(-1):250 g kg(-1)); R3 (500 g kg(-1):500 g kg(-1)); R4 (250 g kg(-1):750 g kg(-1)); and R5 (0 g kg(-1):1000 g kg(-1)). Addition of CLDM had significant (p < or = 0.001) effects on soil quality and favorable influence on forage establishment and nutritive values. Compared with the control plots (0 g kg(-1)), the soils in plots amended with CLDM exhibited (i) lower penetration resistance, (ii) an increase in soil pH and exchangeable cations (Ca and Mg), and (iii) decrease in the levels of soil trace metals (Mn, Cu, Fe, Zn, and Si). Results disclosed consistently and significantly (p < or = 0.001) higher BG biomass production (forage yield = -106.3x(2) + 1015.8x - 39.2; R(2) = 0.99**) and crude protein content (CP = 1.24x + 6.48; R(2) = 0.94**) from plots amended with CLDM than those of BG planted on plots with no CLDM treatment.

Assessing the efficacy of dredged materials from Lake Panasoffkee, Florida: implication to environment and agriculture. Part 2: pasture establishment and forage productivity.

BACKGROUND, AIMS AND SCOPE: Current dredged material disposal alternatives have several limitations. Options for dealing with dredged materials include leaving them alone, capping them with clean sediments, placing them in confined facilities, disposing of them at upland sites, treating them chemically, or using them for wetlands creation or other beneficial uses The ability to reuse lake-dredge materials (LDM) for agricultural purposes is important because it reduces the need for offshore disposal and provides an alternative to disposal of the materials in landfills. Often these materials can be obtained at little or no cost to the farmers or landowners. Thus, forage production offers an alternative to waste management since nutrients in the LDM are recycled into crops that are not directly consumed by humans. The objective of this study (Part 2) were to: (1) assess dredge materials from Lake Panasoffkee, Florida as a soil amendment to establish bahiagrass (BG) in a subtropical beef cattle pasture in Sumter County, Florida; and (2) determine the effect of LDM application on the crude protein (CP) and nutrient uptake of BG. This series of two papers aims at providing assessment of the efficacy of lake-dredged materials especially its implication to environment (soil quality, Part 1) and agriculture (forage quality and pasture establishment, Part 2). METHODS: The experimental treatments that were evaluated consisted of different ratios of natural soil (NS) to LDM: LDM0 (100% NS:0% LDM); LDM25 (75% NS:25% LDM); LDM50 (50% NS:50% LDM); LDM75 (25% NS:75% LDM); and LDM100 (0% NS:100% LDM). Bahiagrass plots at its early establishment were cut to a 5-cm stubble height on Julian days 112 and harvested to the same stubble height on Julian days 238 and on Julian days 546 following the double-ring method. Field layout was based on the principle of a completely randomized block design with four replications. Plant samples harvested at 546 Julian days were ground to pass through a 1-mm mesh screen in a Wiley mill. Ground forage was analyzed for crude protein. Ground forage samples were also analyzed for tissue P, K, Ca, Mg, Mn, Cu, Fe, Al, and Mo concentrations using an ICP spectroscopy. The effects of dredged materials addition on forage yield and on crude protein and nutrient uptake that were taken at 546 Julian days were analyzed statistically following the PROC ANOVA procedures. RESULTS AND DISCUSSION: Part 1 of this study demonstrated that the heavy and trace metal contents of LDM were below the probable effect levels and threshold effect levels. As such, the agricultural or livestock industry could utilize these LDM to produce forages. Resuits showed consistently and significantly (p < 0.001) higher BG biomass production and CP from plots amended with LDM than those of BG planted on plots with 0% LDM. Forage yield of BG during its establishment increased linearly (Forage Yield = 1724.3 + 25.64*LDM; R2 = 0.83; p < or = 0.0001) with increasing rates of LDM application. The CP of BG also varied significantly with varying levels of LDM applications. The tissues of BG with 100% LDM had the greatest CP content while the lowest CP content was from the control plots (LDM0). The CP of BG increased linearly with increasing rates of LDM application. The crude protein response to BG application can be described by a linear equation: Crude Protein = 10.38 + 0.052*LDM; R2 = 0.85 p < or = 0.0001. Addition of LDM had increased the levels of Ca by about 1811% when compared with the level of soil Ca among plots with no LDM application. Liming the field could have some direct and indirect effects on the chemical status of the soils. The physiological functions performed by Ca in plants are not clearly defined, but it has been suggested that Ca favors the formation of and increases the protein content of mitochondria. CONCLUSIONS: Beneficial uses of dredged materials from LP, Florida are both economical and environmental. Often these materials can be obtained at little or no cost to the farmers or landowners. Results showed that dredged materials can be used as soil amendments (lime and fertilizer) for early establishment of BG in beef cattle pastures. Environmentally, dredging of sediments that are rich in CaCO3 should restore the 19.4-sq km LP by removing natural sediments from the lake bottom to improve the fishery, water quality, and navigation of the lake. The nutritional uptake of BG grown in unfertile sandy soils of Sumter County was enhanced significantly (p < or = 0.001) by LDM addition. Uptake of TKN, TP, K, Ca, and Mg were remarkably increased as a result of LDM. RECOMMENDATION AND OUTLOOK: Land application of LDM from LP may not only provide substantial benefits that will enhance the environment, community, and society in south Florida, but also in other parts of the world especially those areas with forage-based beef cattle pastures and similar climatic conditions. The heavy and trace metal contents of these materials were below the PEL and TEL (see Part 1). As such, the agricultural or livestock industry could utilize these LDM to produce forages. LDM should be regarded as a beneficial resource, as a part of the ecological system. Although our results have demonstrated the favorable and beneficial effects of added LDM on the early establishment of BG in pasture fields., further studies are still needed not only in pastures of south Florida, but also in other areas with subtropical or tropical climatic conditions to determine whether the environmental and ecological implications of LDM application are satisfied over the longer term.

Assessing the efficacy of dredged materials from Lake Panasoffkee, Florida: implication to environment and agriculture. Part 1: Soil and environmental quality aspect.

BACKGROUND, AIMS AND SCOPE: Dredged materials because of its variable but unique physical and chemical properties are often viewed by society and regulators as pollutants, but many have used these materials in coastal nourishment, land or wetland creation, construction materials, and for soil improvement as a soil amendment. Environmental impact assessment is an important pre-requisite to many dredging initiatives. The ability to reuse lake-dredge materials (LDM) for agricultural purposes is important because it reduces the need for off-shore disposal and provides an alternative to disposal of the materials in landfills. Additional research on disposal options of dredged materials are much needed to supply information on criteria testing and evaluation of the physical and chemical impacts of dredged materials at a disposal site, as well as information on many other aspects of dredging and dredged material disposal. While preliminary efforts are underway to provide information to establish criteria for land disposal, testing procedures for possible land disposal of contaminated sediments are still in their developing stage. The objective of this study (Part 1) was to quantify the effect of applied LDM from Lake Panasoffkee (LP), Florida on soil physico-chemical properties (soil quality) at the disposal site. This series of two papers aims at providing assessment of the efficacy of lake-dredged materials from LP especially its implication to environment (soil quality, Part 1) and agriculture (forage quality and pasture establishment, Part 2). METHODS: The experimental treatments that were evaluated consisted of different ratios of natural soil (NS) to LDM: LDM0 (100% NS:0% LDM); LDM25 (75% NS:25% LDM); LDM50 (50% NS:50% LDM); LDM75 (25% NS:75% LDM); and LDM100 (0% NS:100% LDM). Field layout was based on the principle of a completely randomized block design with four replications. The Mehlich 1 method (0.05 N HCl in 0.025 N H2SO4) was used for chemical extraction of soil. Soil P and other exchangeable cations (Ca, Mg, K, Al, and Fe) were analyzed using an Inductively Coupled Plasma (ICP) Spectroscopy. The effects of dredged materials addition on soil quality and compaction were analyzed statistically following the PROC ANOVA procedures. RESULTS AND DISCUSSION: Sediments that were dredged from LP have high CaCO3 content (82%) and when these materials were incorporated into existing topsoil they would have the same favorable effects as liming the field. Thus, sediments with high CaCO3 may improve the physical and chemical conditions of subtropical sandy pastures. The heavy and trace metal contents of LDM were below the probable effect levels (PEL) and threshold effect levels (TEL). Average values for Pb, Zn, As, Cu, Hg, Se, Cd, and Ni of 5.2 +/- 1.3, 7.0 +/- 0.6, 4.4 +/- 0.1, 8.7 +/- 1.2, 0.01 +/- 0.02, 0.02 +/- 0.02, 2.5 +/- 0.1, and 14.6 +/- 6.4 mg kg(-1), respectively, were below the TEL and the PEL. TEL represents the concentrations of sediment-associated contaminants that are considered to cause significant hazards to aquatic organisms, while, PEL represents the lower limit of the range of the contaminant concentrations that are usually or always associated with adverse biological effects. As such, the agricultural or livestock industry could utilize these LDM to produce forages. LDM should be regarded as a beneficial resource, as a part of the ecological system. Addition of LDM had significant (p < or = 0.001) effects on soil physico-chemical properties and soil quality. Compared with the control plots, the soils in plots amended with LDM exhibited: (1) lower degree of soil compaction; (2) an increase in soil pH, Ca, and Mg; (3) decrease in the levels of soil Mn, Cu, Fe, Zn, and Si; and (4) no significant change in the level of Na in the soil. Results have shown the favorable influence that LDM had on soil compaction. The treatment x year interaction effect was not significant, but the average soil compaction varied widely (p < or = 0.001) with LDM application. In 2002 and 2003, soil compaction of plots was lowered significantly as a result of LDM additions. The least compacted soils in 2002 and 2003 were observed from plots with LDM75 with mean soil compaction of 300 x 10(3) and 350 x 10(3) Pa, respectively. CONCLUSION: Beneficial uses of dredged materials from LP, Florida are both economical and environmental. Often these materials can be obtained at little or no cost to the farmers or landowners in south Florida. Environmentally, dredging of sediments that are rich in CaCO3 should restore the 19.4-sq km LP by removing natural sediments from the lake bottom to improve the fishery, water quality, and navigation of the lake. The bottom sediment materials from lakes, river, and navigational channels usually are composed of upland soil enriched with nutrients and organic matter. These materials should be regarded as a beneficial resource to be used productively and not to be discarded as spoil materials. RECOMMENDATION AND OUTLOOK: Land application of LDM from LP may not only provide substantial benefits that will enhance the environment, community, and society in south Florida, but also in other parts of the world especially those areas having tropical and subtropical climate with forage-based beef cattle pastures. The heavy and trace metal contents of LDM from LP were below the PEL and TEL. As such, the agricultural or livestock industry could utilize these LDM to produce forages (Part 2 of this study). LDM should be regarded as a beneficial resource, as a part of the ecological system. Further studies are still needed to determine whether the environmental and ecological implications of LDM application are satisfied over the longer term.