Emerging power of proteomics for delineation of intrinsic tumor subtypes and resistance mechanisms to anti-cancer therapies

Introduction: Despite extreme genetic heterogeneity, tumors often show similar alterations in the expression, stability, and activation of proteins important in oncogenic signaling pathways. Thus, classifying tumor samples according to shared proteomic features may help facilitate the identification of cancer subtypes predictive of therapeutic responses and prognostic for patient outcomes. Meanwhile, understanding mechanisms of intrinsic and acquired resistance to anti-cancer therapies at the protein level may prove crucial to devising reversal strategies.

Areas covered: Herein, we review recent advances in quantitative proteomic technology and their applications in studies to identify intrinsic tumor subtypes of various tumors, to illuminate mechanistic aspects of pharmacological and oncogenic adaptations, and to highlight interaction targets for anti-cancer compounds and cancer-addicted proteins.

Expert commentary: Quantitative proteomic technologies are being successfully employed to classify tumor samples into distinct intrinsic subtypes, to improve existing DNA/RNA based classification methods, and to evaluate the activation status of key signaling pathways.     

Genetic and epigenetic heterogeneity of epithelial ovarian cancer and the clinical implications for molecular targeted therapy

Epithelial ovarian cancer (EOC) is the most lethal gynaecological malignancy, and tumoural heterogeneity (TH) has been blamed for treatment failure. The genomic and epigenomic atlas of EOC varies significantly with tumour histotype, grade, stage, sensitivity to chemotherapy and prognosis. Rapidly accumulating knowledge about the genetic and epigenetic events that control TH in EOC has facilitated the development of molecular‐targeted therapy. Poly (ADP‐ribose) polymerase (PARP) inhibitors, designed to target homologous recombination, are poised to change how breast cancer susceptibility gene (BRCA)‐related ovarian cancer is treated. Epigenetic treatment regimens being tested in clinical or preclinical studies could provide promising novel treatment approaches and hope for improving patient survival.     

云南水稻地方品种月亮谷的群体多样性分析

月亮谷是云南元阳梯田种植历史悠久、种植面积最大的优良水稻地方品种之一,当地少数民族具有引种或换种的稻作习惯。为揭示这种稻作习惯对月亮谷群体遗传多样性的影响,本研究对该品种群体内和群体间进行了遗传多样性的比较和分析,目的是为更好地了解月亮谷的群体遗传结构,为持久利用地方品种提供理论依据。首先采用分层随机取样的策略从元阳梯田不同海拔获得24个原位栽培群体,采用形态指数分类法和抗病性测定对24个群体共720个单株样品的月亮谷进行形态学分类和稻瘟病抗性鉴定,并分析了这些单株材料在48个SSR位点的遗传多样性。研究结果表明,形态上月亮谷属于栽培稻的籼稻类型,其群体对稻瘟病具中抗水平,但无论是在群体内还是群体间,均普遍表现出明显差异,说明不同来源的月亮谷存在抗病功能表型上的变异;遗传多样性分析显示,48对SSR引物共检测出91个多态位点,多态性位点百分率为77.08%,Nei多样性指数平均值为0.064,变幅为0~0.4302。24个群体之间的遗传相似系数在0.9753~0.9866之间,群体内个体之间的遗传相似系数在0.86~1.00之间;AMOVA分析显示,以地理村寨作为自然居群单位,居群间的变异为3.36%,居群内群体间的变异为33.15%,居群内的变异为63.49%;聚类分析显示,村寨群体间的遗传多样性与村寨间的地理空间距离有一定相关性。     

Genome Characteristics,Phylogeny and Varying Host Specificity of Polish Kra and Ros Isolates of Tomato torrado virus

The genome sequences of two Polish Kra and Ros isolates of Tomato torrado virus (ToTV) were determined and compared with data of previously described ToTV isolates and other Torradovirus members. Whole‐genome sequence comparisons revealed 97.0–99.6% nucleotide sequence identities and close relatedness, with other known ToTV isolates. The high homology between Kra, Ros and Wal'03 ToTVs is likely responsible for the similar symptoms observed on infected plants. However, the symptoms differed in intensity and various host specificity. We report that Kra ToTV caused a milder expression of symptoms on Solanum tuberosum than Wal'03. We hypothesize this may be a result of the significant variability observed within the 3′‐UTR of RNA1 of Kra as well as of Ros ToTV isolates. In the light of this fact, potato may be considered an indicator plant for distinguishing Kra and Wal'03 ToTV isolates.     

生境异质性对鼎湖山常绿阔叶林群落功能多样性的影响

物种共存机制一直以来是群落生态学的研究热点。为了探讨异质生境条件下鼎湖山常绿阔叶林群落功能多样性变化,找到其变化的主要环境驱动因子,该研究利用位于鼎湖山20 hm~2监测样地第2次群落调查数据并选择代表不同生境(海拔和地形)的27个样方(20 m×20 m),于2013年夏季在样地内所选样方中测定所有胸径≥1 cm树种的叶片功能性状。所测性状包括形态学性状(比叶面积、叶片干物质含量、叶面积以及叶片长宽比)和化学计量学性状(叶片碳、氮、磷的含量),结合地形和土壤数据并通过分析功能多样性随环境梯度的变化,探讨了环境过滤和竞争在鼎湖山群落物种共存中的相对重要性。结果表明:功能分歧度和群落权重平均值与环境因素关系密切,尤其是海拔、凹凸度和土壤养分。环境条件较好区域(微尺度高海拔、高凹凸度和土壤养分含量)的植物采取统一的养分有效保存(低SLA,高LDMC)的适应策略(功能分歧度低),环境过滤所起作用更强;植物在相反的环境条件下,采取快速生长策略(高SLA,低LDMC),能够更好地适应环境的变化,且性状变化是多样的(功能分歧度高),在该条件下竞争作用更为显著。叶面积和叶片氮含量的分歧度在环境条件较好的区域增大,这与其他功能性状不一致,说明不同生态位轴(环境因素)影响不同性状的分歧度变化,并且在局域尺度上植物为了更好地适应环境变化采取了多样的适应策略。     

The impact of rate heterogeneity on inference of phylogenetic models of trait evolution

Rates of trait evolution are known to vary across phylogenies; however, standard evolutionary models assume a homogeneous process of trait change. These simple methods are widely applied in small‐scale phylogenetic studies, whereas models of rate heterogeneity are not, so the prevalence and patterns of potential rate variation in groups up to hundreds of species remain unclear. The extent to which trait evolution is modelled accurately on a given phylogeny is also largely unknown because studies typically lack absolute model fit tests. We investigated these issues by applying both rate‐static and variable‐rates methods on (i) body mass data for 88 avian clades of 10–318 species, and (ii) data simulated under a range of rate‐heterogeneity scenarios. Our results show that rate heterogeneity is present across small‐scaled avian clades, and consequently applying only standard single‐process models prompts inaccurate inferences about the generating evolutionary process. Specifically, these approaches underestimate rate variation, and systematically mislabel temporal trends in trait evolution. Conversely, variable‐rates approaches have superior relative fit (they are the best model) and absolute fit (they describe the data well). We show that rate changes such as single internal branch variations, rate decreases and early bursts are hard to detect, even by variable‐rates models. We also use recently developed absolute adequacy tests to highlight misleading conclusions based on relative fit alone (e.g. a consistent preference for constrained evolution when isolated terminal branch rate increases are present). This work highlights the potential for robust inferences about trait evolution when fitting flexible models in conjunction with tests for absolute model fit.     

The constant philopater hypothesis: a new life history invariant for dispersal evolution

Surprising invariance relationships have emerged from the study of social interaction, whereby a cancelling‐out of multiple partial effects of genetic, ecological or demographic parameters means that they have no net impact upon the evolution of a social behaviour. Such invariants play a pivotal role in the study of social adaptation: on the one hand, they provide theoretical hypotheses that can be empirically tested; and, on the other hand, they provide benchmark frameworks against which new theoretical developments can be understood. Here we derive a novel invariant for dispersal evolution: the ‘constant philopater hypothesis’ (CPH). Specifically, we find that, irrespective of variation in maternal fecundity, all mothers are favoured to produce exactly the same number of philopatric offspring, with high‐fecundity mothers investing proportionally more, and low‐fecundity mothers investing proportionally less, into dispersing offspring. This result holds for female and male dispersal, under haploid, diploid and haplodiploid modes of inheritance, irrespective of the sex ratio, local resource availability and whether mother or offspring controls the latter's dispersal propensity. We explore the implications of this result for evolutionary conflict of interests – and the exchange and withholding of contextual information – both within and between families, and we show that the CPH is the fundamental invariant that underpins and explains a wider family of invariance relationships that emerge from the study of social evolution.     

Oncogenic Regulation of Extracellular Vesicle Proteome and Heterogeneity

Mutational and epigenetic driver events profoundly alter intercellular communication pathways in cancer. This effect includes deregulated release, molecular composition, and biological activity of extracellular vesicles (EVs), membranous cellular fragments ranging from a few microns to less than 100 nm in diameter and filled with bioactive molecular cargo (proteins, lipids, and nucleic acids). While EVs are usually classified on the basis of their physical properties and biogenetic mechanisms, recent analyses of their proteome suggest a larger than expected molecular diversity, a notion that is also supported by multicolour nano‐flow cytometry and other emerging technology platforms designed to analyze single EVs. Both protein composition and EV diversity are markedly altered by oncogenic transformation, epithelial to mesenchymal transition, and differentiation of cancer stem cells. Interestingly, only a subset of EVs released from mutant cells may carry oncogenic proteins (e.g., EGFRvIII), hence, these EVs are often referred to as “oncosomes”. Indeed, oncogenic transformation alters the repertoire of EV‐associated proteins, increases the presence of pro‐invasive cargo, and alters the composition of distinct EV populations. Molecular profiling of single EVs may reveal a more intricate effect of transforming events on the architecture of EV populations in cancer and shed new light on their biological role and diagnostic utility.     

A global assessment of primate responses to landscape structure

Land‐use change modifies the spatial structure of terrestrial landscapes, potentially shaping the distribution, abundance and diversity of remaining species assemblages. Non‐human primates can be particularly vulnerable to landscape disturbances, but our understanding of this topic is far from complete. Here we reviewed all available studies on primates' responses to landscape structure. We found 34 studies of 71 primate species (24 genera and 10 families) that used a landscape approach. Most studies (82%) were from Neotropical forests, with howler monkeys being the most frequently studied taxon (56% of studies). All studies but one used a site‐landscape or a patch‐landscape study design, and frequently (34% of studies) measured landscape variables within a given radius from the edge of focal patches. Altogether, the 34 studies reported 188 responses to 17 landscape‐scale metrics. However, the majority of the studies (62%) quantified landscape predictors within a single spatial scale, potentially missing significant primate–landscape responses. To assess such responses accurately, landscape metrics need to be measured at the optimal scale, i.e. the spatial extent at which the primate–landscape relationship is strongest (so‐called ‘scale of effect’). Only 21% of studies calculated the scale of effect through multiscale approaches. Interestingly, the vast majority of studies that do not assess the scale of effect mainly reported null effects of landscape structure on primates, while most of the studies based on optimal scales found significant responses. These significant responses were primarily to landscape composition variables rather than landscape configuration variables. In particular, primates generally show positive responses to increasing forest cover, landscape quality indices and matrix permeability. By contrast, primates show weak responses to landscape configuration. In addition, half of the studies showing significant responses to landscape configuration metrics did not control for the effect of forest cover. As configuration metrics are often correlated with forest cover, this means that documented configuration effects may simply be driven by landscape‐scale forest loss. Our findings suggest that forest loss (not fragmentation) is a major threat to primates, and thus, preventing deforestation (e.g. through creation of reserves) and increasing forest cover through restoration is critically needed to mitigate the impact of land‐use change on our closest relatives. Increasing matrix functionality can also be critical, for instance by promoting anthropogenic land covers that are similar to primates' habitat.     

Transcriptional Heterogeneity of Beta Cells in the Intact Pancreas

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