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Several papers have recently raised the occurrence of some problems with between-group Principal Component Analysis (bgPCA). This method inflates the differences between the groups, and can even display completely artificial differences when none exist, for example when applied to random numbers tables with many variables (columns) and few individuals (rows). Lately, cross-validation has been proposed as a way to circumvent this problem. Here we present some tools and several functions of the ade4 package for the R statistical software to compute a bgPCA, test the presence of statistically significant groups, perform a cross-validation of this analysis and compute associated statistics. We also describe how to use these functions to avoid running into the spurious groups problem. Several examples, including a real data set and random numbers tables, are used to validate this approach in various experimental and numerical conditions. The integrated framework of the duality diagram, as implemented in ade4, allows to extend this approach to other multivariate analysis methods beyond principal component analysis, which could prove useful in the case of other types of variables. The R code and the real data table used to make the computations and graphs of this paper are available as supplementary material. [ABSTRACT FROM AUTHOR]

The rationale for therapeutic targeting of Vδ2+ γδ T cells in breast cancer is strongly supported by in vitro and murine preclinical investigations, characterizing them as potent breast tumor cell killers and source of Th1-related cytokines, backing cytotoxic αβ T cells. Nonetheless, insights regarding Vδ2+ γδ T cell phenotypic alterations in human breast cancers are still lacking. This paucity of information is partly due to the challenging scarcity of these cells in surgical specimens. αβ T cell phenotypic alterations occurring in the tumor bed are detectable in the periphery and correlate with adverse clinical outcomes. Thus, we sought to determine through an exploratory study whether Vδ2+ γδ T cells phenotypic changes can be detected within breast cancer patients’ peripheral blood, along with association with tumor progression. By using mass cytometry, we quantified 130 immune variables from untreated breast cancer patients’ peripheral blood. Supervised analyses and dimensionality reduction algorithms evidenced circulating Vδ2+ γδ T cell phenotypic alterations already established at diagnosis. Foremost, terminally differentiated Vδ2+ γδ T cells displaying phenotypes of exhausted senescent T cells associated with lymph node involvement. Thereby, our results support Vδ2+ γδ T cells implication in breast cancer pathogenesis and progression, besides shedding light on liquid biopsies to monitor surrogate markers of tumor-infiltrating Vδ2+ γδ T cell antitumor activity.

The objective of the study was to identify all parallel design randomised controlled trials (RCTs) comparing treatments for eczema in recent dermatology literature that have failed to report a between-group analysis. The GREAT database (www.greatdatabase.org.uk) was searched to identify parallel group RCTs comparing two or more interventions published in the English language in the last decade, 2004 to 2013. The primary outcome was the number of studies that had not reported a between-group analysis for any of the outcomes. Where possible we re-analysed the data to determine whether a between-group analysis would have given a different conclusion to that reported. Out of a total of 304 RCTs in the study period, 173 (56.9%) met the inclusion criteria. Of the 173 eligible studies, 12 (6.9%) had not conducted a between-group analysis for any of the reported outcomes. There was no clear improvement over time. Five of the eight studies that were re-analysed yielded non-significant between-group differences yet reported significant within-group comparisons. All but one of the 12 studies implied that the experimental intervention was successful despite not undertaking any between-group comparisons. Although the proportion of all RCTs that fail to report an appropriate between-group analysis is small, the fact that any scientist who purports to compare one treatment against another then chooses to omit the key comparison statistic is worrying.

Analysis of between-group differences using canonical variates assumes equality of population covariance matrices. Sometimes these matrices are sufficiently different for the null hypothesis of equality to be rejected, but there exist some common features which should be exploited in any analysis. The common principal component model is often suitable in such circumstances, and this model is shown to be appropriate in a practical example. Two methods for between-group analysis are proposed when this model replaces the equal dispersion matrix assumption. One method is by extension of the two-stage approach to canonical variate analysis using sequential principal component analyses as described by Campbell and Atchley (1981). The second method is by definition of a distance function between populations satisfying the common principal component model, followed by metric scaling of the resulting between-populations distance matrix. The two methods are compared with each other and with ordinary canonical variate analysis on the previously introduced data set. [ABSTRACT FROM AUTHOR]

Simple Summary: Vδ2+ γδ T cells have potent antitumor properties both in vitro and in murine preclinical models of breast cancers. However, in the context of human breast cancer, there is a lack of information for potential phenotypic alterations of this crucial immune cell subset. This is partly due to Vδ2+ γδ T cells scarcity in surgical specimens. To break this deadlock, we assessed Vδ2+ γδ T cell phenotypes using untreated breast cancer patients' peripheral blood, so-called minimally invasive "liquid biopsy". We show that circulating Vδ2+ γδ T cell phenotypic alterations are already established at diagnosis and related to tumor progression. Notably, terminally differentiated Vδ2+ γδ T cells expressing canonical markers of replicative senescence and exhaustion were significantly associated with tumor-draining lymph node invasion. Our results shed light on the interest of using liquid biopsy to monitor rare events and support Vδ2+ γδ T cell involvement in breast cancer pathogenesis and progression. The rationale for therapeutic targeting of Vδ2+ γδ T cells in breast cancer is strongly supported by in vitro and murine preclinical investigations, characterizing them as potent breast tumor cell killers and source of Th1-related cytokines, backing cytotoxic αβ T cells. Nonetheless, insights regarding Vδ2+ γδ T cell phenotypic alterations in human breast cancers are still lacking. This paucity of information is partly due to the challenging scarcity of these cells in surgical specimens. αβ T cell phenotypic alterations occurring in the tumor bed are detectable in the periphery and correlate with adverse clinical outcomes. Thus, we sought to determine through an exploratory study whether Vδ2+ γδ T cells phenotypic changes can be detected within breast cancer patients' peripheral blood, along with association with tumor progression. By using mass cytometry, we quantified 130 immune variables from untreated breast cancer patients' peripheral blood. Supervised analyses and dimensionality reduction algorithms evidenced circulating Vδ2+ γδ T cell phenotypic alterations already established at diagnosis. Foremost, terminally differentiated Vδ2+ γδ T cells displaying phenotypes of exhausted senescent T cells associated with lymph node involvement. Thereby, our results support Vδ2+ γδ T cells implication in breast cancer pathogenesis and progression, besides shedding light on liquid biopsies to monitor surrogate markers of tumor-infiltrating Vδ2+ γδ T cell antitumor activity. [ABSTRACT FROM AUTHOR]

The objective of the study was to identify all parallel design randomised controlled trials (RCTs) comparing treatments for eczema in recent dermatology literature that have failed to report a between-group analysis. The GREAT database (www.greatdatabase.org.uk) was searched to identify parallel group RCTs comparing two or more interventions published in the English language in the last decade, 2004 to 2013. The primary outcome was the number of studies that had not reported a between-group analysis for any of the outcomes. Where possible we re-analysed the data to determine whether a between-group analysis would have given a different conclusion to that reported. Out of a total of 304 RCTs in the study period, 173 (56.9%) met the inclusion criteria. Of the 173 eligible studies, 12 (6.9%) had not conducted a between-group analysis for any of the reported outcomes. There was no clear improvement over time. Five of the eight studies that were re-analysed yielded non-significant between-group differences yet reported significant within-group comparisons. All but one of the 12 studies implied that the experimental intervention was successful despite not undertaking any between-group comparisons. Although the proportion of all RCTs that fail to report an appropriate between-group analysis is small, the fact that any scientist who purports to compare one treatment against another then chooses to omit the key comparison statistic is worrying.