Gating strategy for the detection of different immune cell subsets from malignant ascites of ovarian cancer patients.

Cells collected from ascites were stained with a 9-color flow cytometry panel and analyzed in an X-20 Fortessa flow cytometer. (A) The gating strategy is depicted starting with the detection of lymphocytes, followed by live cells and CD3+ T cells that are separated according to CD4 and CD8 expression. (B) Fluorescence-minus-one (FMO) staining is shown for the different markers analyzed on CD4+ and CD8+ T cells. (PDF)</p

Ascitic fluid cell CDR3β motifs associated with prognosis.

(A) Examples of CD4+ T cell receptor (TCR) motifs associated with different prognoses. (B) Examples of CD8+ TCR motifs associated with different prognoses. The figures show the logo and phylogenetic tree of the clustered CDR3β peptides for each motif. The phylogenetic tree also includes peptides found as the best hit from McPAS; the complete set of motifs associated with excellent or poor/worst prognosis is shown in S7A Table. (C) Association networks constructed to form the cluster of motifs associated with response to platinum therapy. Nodes in the networks indicate individual patients; the color of the node indicates prognosis. Edges in the networks indicate an association between a pair of samples if they share GLIPH specificity groups associated with prognosis. The networks validated the statistical algorithm used to identify prognosis-associated specificity groups.</p

Increased T cell receptor productive rearrangements in ascites of patients with <i>BRCA1/2</i> tumor mutations.

(PDF)</p

Difference in T cell receptor (TCR) characteristics between ascites of patients grouped in Cluster A and ascites of patients grouped in the remaining clusters (others).

(PDF)</p

A prospective study of the adaptive changes in the gut microbiome during standard-of-care chemoradiotherapy for gynecologic cancers.

BackgroundA diverse and abundant gut microbiome can improve cancer patients' treatment response; however, the effect of pelvic chemoradiotherapy (CRT) on gut diversity and composition is unclear. The purpose of this prospective study was to identify changes in the diversity and composition of the gut microbiome during and after pelvic CRT.Materials and methodsRectal swabs from 58 women with cervical, vaginal, or vulvar cancer from two institutions were prospectively analyzed before CRT (baseline), during CRT (weeks 1, 3, and 5), and at first follow-up (week 12) using 16Sv4 rRNA gene sequencing of the V4 hypervariable region of the bacterial 16S rRNA marker gene. 42 of these patients received antibiotics during the study period. Observed operational taxonomic units (OTUs; representative of richness) and Shannon, Simpson, Inverse Simpson, and Fisher diversity indices were used to characterize alpha (within-sample) diversity. Changes over time were assessed using a paired t-test, repeated measures ANOVA, and linear mixed modeling. Compositional changes in specific bacteria over time were evaluated using linear discriminant analysis effect size.ResultsGut microbiome richness and diversity levels continually decreased throughout CRT (mean Shannon diversity index, 2.52 vs. 2.91; all P ConclusionAfter CRT, the diversity of the gut microbiomes in this population tended to return to baseline levels by the 12 week follow-up period, but structure and composition remained significantly altered. These changes should be considered when designing studies to analyze the gut microbiome in patients who receive pelvic CRT for gynecologic cancers

Difference in flow subset (expressed as a percentage of CD3+ live lymphocytes) between ascites of patients grouped in Cluster A and ascites of patients grouped in the remaining clusters (others).

(PDF)</p