Relationship Based Leadership: The Development of Leader Member Exchange Theory

Despite several studies on leadership, there still is no clear understanding of what leadership is and how it can be achieved. Traditional classification of leadership theories has been either on the basis of traits, behaviour or situation. The focus of these approaches has been primarily on the characteristics of the manager or the supervisor that make him or her effective in leadership situations. This typology of leadership does not specifically explain the influence of the follower characteristics or the leader relationship with the subordinate. LMX is one such leader relationship theory. It is not very clear as to where the LMX theory fits in the overall context of different leadership approaches. This paper discusses the LMX Theory in the context of the vast literature on Leadership, its evolution and practical utility for leadership development in organizations

Integrating 'Mindful Living' for a Peaceful Life

In times gone by, people were concerned primarily with survival-avoiding death by starvation, disease, or violence. Though many of us are not subject to such stressors these days, one is stressed due to the faster pace of life. Small stressors from each or all of these add up to a bigger one over a period of time. We ignore the stress we experience despite the physical or mental symptoms of stress that our body throws at us. Instead of focusing on solutions for the symptoms or causes of our stress, we tend to turn a blind eye and make ourselves ever busier to continue as ‘normal’ and ‘achieve more’ in our lives. The answer to managing this stress in our lives lies in practicing the technique of mindful living. Mindful living does not guarantee that we will not have any problems in life. But it can certainly make us aware that it is none but us who are responsible for our own happiness or unhappiness

Indian Perspectives on Mindful Leadership

It is generally believed that mindfulness has its roots in the ancient Eastern tradition of Buddhism. However, there is ample evidence that ancient Hindu texts stress mediation, silent contemplation, and acceptance of things as they are, which is the essence of mindfulness. Upanishads, a collection of Indian religious and philosophical thoughts written probably between 800 BCE to 500 BCE – describe meditation, often suggesting the use of a chant or a mantra. Mindfulness practice in Hindu tradition emphasizes silent meditation – with or without chants or mantras – to calm the mind. Mindfulness enhances directed awareness allows for examining problems or issues from different perspectives and stimulates wider thought. The mindfulness approach calms the mind, can enhance insight, and clears the mind from experiencing ‘a-ha’ moments. A mindful approach by leaders when dealing with issues at hand helps team members relax, creates safer spaces for creative exploration, allows for deeper understanding, and supports problem-solving through the generation of innovative and creative ideas. The mindfulness leadership approach aids flexibility and thought clarity. Other advantages of a mindful leadership approach include leading by example, appreciation and recognition of team efforts, humility, openness to feedback, awareness of own thoughts, emotions, speech, and behavior, ability to read people's situations and ask relevant questions, intuitiveness, receptiveness to change, willingness to adapt, willingness to change, ability to effectively engage with employees and situation

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation