Fungivorous nematodes drive microbial diversity and carbon cycling in soil.

Soil bacteria and fungi mediate terrestrial biogeochemical cycling, but we know relatively little about how trophic interactions influence their community composition, diversity, and function. Specifically, it is unclear how consumer populations affect the activity of microbial taxa they consume, and therefore the interaction of those taxa with other members of the microbial community. Due to its extreme diversity, studying trophic dynamics in soil is a complex feat. Seeking to address these challenges, we performed a microcosm-based consumer manipulation experiment to determine the impact of a common fungal-feeding nematode (Aphelenchus avenae) on soil microbial community composition, diversity, and activity (e.g., C cycling parameters). Fungivory decreased fungal and bacterial α-diversity and stimulated C and N cycling, possibly via cascading impacts of fungivory on bacterial communities. Our results present experimental evidence that soil trophic dynamics are intimately linked with microbial diversity and function, factors that are key in understanding global patterns in biogeochemical cycling.

Soil microbial succession following surface mining is governed primarily by deterministic factors.

Understanding the successional dynamics governing soil microbial community assembly following disturbance can aid in developing remediation strategies for disturbed land. However, the influences shaping microbial communities during succession following soil disturbance remain only partially understood. One example of a severe disturbance to soil is surface mining for natural resources, which displaces communities and changes the physical and chemical soil environment. These changes may alter community composition through selective pressure on microbial taxa (i.e. deterministic processes). Dispersal and ecological drift may also shape communities following disturbance (i.e. stochastic processes). Here, the relative influence of stochastic and deterministic processes on microbial community succession was investigated using a chronosequence of reclaimed surface mines ranging from 2-32 years post-reclamation. Sequencing of bacterial and fungal ribosomal gene amplicons coupled with a linear modeling approach revealed that following mine reclamation, while bacterial communities are modestly influenced by stochastic factors, the influence of deterministic factors was ∼7 × greater. Fungal communities were influenced only by deterministic factors. Soil organic matter, texture, and pH emerged as the most influential environmental factors on both bacterial and fungal communities. Our results suggest that management of deterministic soil characteristics over a sufficient time period could increase the microbial diversity and productivity of mine soils.

Mitoxantrone-Induced Cardiotoxicity in Acute Myeloid Leukemia-A Velocity Vector Imaging Analysis.

BACKGROUND: The purpose of this investigation was to: (1) determine incidence and predictors of mitoxantrone-induced early cardiotoxicity and (2) study left ventricular mechanics before and after receiving mitoxantrone. METHOD AND RESULTS: We retrospectively analyzed 80 subjects diagnosed with acute myeloid leukemia (AML) who underwent chemotherapy with bolus high-dose mitoxantrone. Echocardiographic measurements were taken at baseline and at a median interval of 55 days after receiving mitoxantrone. Thirty-five (44%) of the patients developed clinically defined early cardiotoxicity, 29 (36%) of which developed heart failure. There was a significant decrease in the ejection fraction (EF) not only in the cardiotoxicity group (17.6 ± 14.8%, P < 0.001) but also in the noncardiotoxicity group (5.3 ± 8.4%, P < 0.001). Decrease in global longitudinal strain (GLS) (-3.7 ± 4.5, P < 0.001 vs. -2.4 ± 4.3, P = 0.01) and global circumferential strain (GCS) (-5.6 ± 9, P = 0.003 vs. -5.3 ± 8.7, P < 0.001) was significant in both the cardiotoxicity and noncardiotoxicity group, respectively. A multivariate model including baseline left ventricular end-systolic diameter, baseline pre-E/A ratio, and baseline pre-E/e' ratio was found to be the best-fitted model for prediction of mitoxantrone-induced early clinical cardiotoxicity. CONCLUSION: High-dose mitoxantrone therapy is associated with an excellent remission rate but with a significantly increased risk of clinical and subclinical early cardiotoxicity and heart failure. Mitoxantrone-induced systolic dysfunction is evident from reduction in EF, increase in Tei index, and significant reduction in GLS and GCS. Baseline impaired ventricular relaxation evident from higher E/e' ratio and lower E/A ratio independently predicts increased risk of mitoxantrone-induced early cardiotoxicity.

Molecular response of the axillary lymph node microenvironment to metastatic colonization.

Breast stroma plays an active role in tumorigenesis, undergoing both phenotypic and molecular changes that facilitate and promote tumor development and growth. The metastatic microenvironment also plays a role in successful colonization; however, genetic changes in these secondary microenvironments are not well described. To improve understanding of molecular changes associated with metastatic colonization, gene expression patterns from lymph node tissues from women with at least one positive, as well as one negative node, were compared. Lymph node tissue was microdissected and hybridized to U133A 2.0 gene expression arrays. Differential expression was detected using Partek(®) Genomics Suite™ 6.6 with FDR <0.05 and >2-fold change defining significance. Twenty-two genes were differentially expressed, 14 genes, including AZGP1, FOXA1 and PIP, were expressed at significantly higher levels in colonized lymph nodes and eight genes, such as CXCL2 and HPGDS, were expressed at significantly higher levels in non-metastatic lymph nodes. Thus, lymph node tissues harboring metastases have different gene expression patterns from those without metastases. Many differentially expressed genes are involved in cellular proliferation and survival, immune function and mesenchymal-epithelial transition, suggesting that repression of immune response and restoration of an epithelial phenotype in the host tissue are critical for successful establishment of lymph node metastases.

Effect of ASCO/CAP guidelines for determining ER status on molecular subtype.

BACKGROUND: Determination of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status is standard for predicting prognosis and determining treatment options for patients with breast cancer. In 2010, the American Society of Clinical Oncology (ASCO) and College of American Pathologists (CAP) issued guidelines that tumors with ≥1% positively staining cells should be considered ER positive. Here, we determined how this cutoff relates to molecular subtype. METHODS: Clinicopathological characteristics were compared between ER-negative, ER-positive, and low-ER-staining (1-10%) tumors using chi-square analysis with P<0.05 defining statistical significance. Gene expression data were generated for 26 low-ER-staining tumors, and their intrinsic subtype determined. Immunohistochemistry (IHC)-defined surrogate subtypes, using the threshold of positivity defined by ASCO/CAP guidelines, were compared with molecular subtypes. RESULTS: Low-ER-staining tumors were clinicopathologically more similar to ER-negative than to ER-positive tumors; 88% of low-staining tumors were basal like or HER2 enriched. Only those tumors expressing 10% ER-positive cells were classified as luminal A subtype. CONCLUSIONS: Under ASCO/CAP guidelines, tumors with 1-10% ER staining would be classified as ER positive, yet most are basal like or HER2 enriched and have pathological features similar to ER-negative tumors. Clinical trials seeking to treat tumors of ER-negative basal-like and/or HER2-enriched subtypes should thus not preclude enrollment based solely on results of ER immunohistochemistry. As ER status is a critical element in the choice of treatments for patients with breast cancer, it is imperative that the most effective method for classifying tumors be developed.

Speckle echocardiographic left atrial strain and stiffness index as predictors of maintenance of sinus rhythm after cardioversion for atrial fibrillation: a prospective study.

BACKGROUND: Echocardiographic left atrial (LA) strain parameters have been associated with atrial fibrillation (AF) in prior studies. Our goal was to determine if strain measures [peak systolic longitudinal strain (LAS) and stiffness index (LASt)] changed after cardioversion (CV); and their relation to AF recurrence. METHODS AND RESULTS: 46 participants with persistent AF and 41 age-matched participants with no AF were recruited. LAS and LASt were measured before and immediately after CV using 2D speckle tracking imaging (2DSI). Maintenance of sinus rhythm was assessed over a 6-month follow up. Mean LAS was lower, and mean LASt higher, in participants with AF before CV as compared to control group (11.9±1.0 vs 35.7±1.7, p<0.01 and 1.31±0.17 vs 0.23±0.01, p<0.01, respectively). There was an increase in the mean LAS immediately after CV (11.9±1.0 vs 15.9±1.3, p<0.01), whereas mean LASt did not change significantly after CV (p=0.62). Although neither LAS nor LASt were independently associated with AF recurrence during the follow-up period, change in LAS after cardioversion (post-CV LAS-pre-CV LAS) was significantly higher among individuals who remained in sinus rhythm when compared to individuals with recurrent AF (3.6±1.1 vs 0.4±0.8, p=0.02). CONCLUSIONS: LAS and LASt differed between participants with and without AF, irrespective of the rhythm at the time of echocardiographic assessment. Baseline LAS and LASt were not associated with AF recurrence. However, change in LAS after CV may be a useful predictor of recurrent arrhythmia.

Genomic (in)stability of the breast tumor microenvironment.

The breast tumor microenvironment plays an active role in tumorigenesis. Molecular alterations have been identified in tumor-associated stroma; however, there is considerable debate as to whether the stroma is characterized by genomic instability or whether detection of chromosomal alterations reflects technological artifact rather than the true genomic content of the tumor microenvironment. Thus, breast stroma specimens from 112 women undergoing reductive mammoplasty (n = 7), prophylactic mastectomy (n = 6), or mastectomy for a breast disease (n = 99) were frozen in optimal cutting temperature medium. Allelic imbalance (AI) analysis was conducted using a panel of 52 microsatellite markers in 484 stromal specimens from 98 women, of which 92% had no detectable AI events. When compared with previously generated AI data from 77 formalin-fixed, paraffin-embedded (FFPE) stroma specimens, 42% of which harbored at least one detectable AI event, the frequency of AI in the FFPE specimens (4.62%) was significantly higher (P < 0.001) than that found in frozen specimens (0.45%). This comparison of AI between FFPE and research-grade specimens suggests that past reports of AI in breast stroma reflect artifact in the archival specimens caused by formalin-fixation, paraffin-embedding and tissue storage. Furthermore, SNP data were generated from a subset of 86 stromal specimens using SNP arrays and copy number alterations were identified using Partek Genomics Suite. For 95% of the specimens, no detectable copy number alterations were found and the 11 changes that were detected were small and not shared between specimens. These data, therefore, support a model in which the tumor microenvironment is genetically stable.

Differential gene expression in primary breast tumors associated with lymph node metastasis.

Lymph node status remains one of the most useful prognostic indicators in breast cancer; however, current methods to assess nodal status disrupt the lymphatic system and may lead to secondary complications. Identification of molecular signatures discriminating lymph node-positive from lymph node-negative primary tumors would allow for stratification of patients requiring surgical assesment of lymph nodes. Primary breast tumors from women with negative (n = 41) and positive (n = 35) lymph node status matched for possible confounding factors were subjected to laser microdissection and gene expression data generated. Although ANOVA analysis (P < .001, fold-change >1.5) revealed 13 differentially expressed genes, hierarchical clustering classified 90% of node-negative but only 66% of node-positive tumors correctly. The inability to derive molecular profiles of metastasis in primary tumors may reflect tumor heterogeneity, paucity of cells within the primary tumor with metastatic potential, influence of the microenvironment, or inherited host susceptibility to metastasis.

Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors.

Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (well-differentiated tumors) and less favorable (poorly-differentiated tumors) outcome groups. The current system of tumor grading, however, is subjective and a large proportion of tumors are characterized as intermediate-grade tumors, making determination of optimal treatments difficult. To determine whether molecular profiles can discriminate breast disease by grade, patterns and levels of allelic imbalance (AI) at 26 chromosomal regions frequently altered in breast disease were examined in 185 laser microdissected specimens representing well-differentiated (grade 1; n = 55), moderately-differentiated (grade 2; n = 71), and poorly-differentiated (grade 3; n = 59) stage I-IV breast tumors. Overall levels of AI were significantly higher in grade 3 compared to grade 1 tumors (P < 0.05). Grades 1 and 3 showed distinct genetic profiles--grade 1 tumors were associated with large deletions of chromosome 16q22, while alterations at 9p21, 11q23, 13q14, 17p13.1 and 17q12 were characteristics of grade 3 carcinomas. In general, levels and patterns of AI in grade 2 carcinomas were intermediate between grade 1 and grade 3 tumors. Patterns of AI accurately categorized approximately 70% of samples into high- or low-grade disease groups, suggesting that the majority of breast tumors have genetic profiles consistent with high- or low-grade, and that molecular signatures of breast tumors can be useful for more accurate characterization of invasive breast cancer.