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The evolutionary processes that drive universal therapeutic resistance in adult patients with diffuse glioma remain unclear.sup.1,2. Here we analysed temporally separated DNA-sequencing data and matched clinical annotation from 222 adult patients with glioma. By analysing mutations and copy numbers across the three major subtypes of diffuse glioma, we found that driver genes detected at the initial stage of disease were retained at recurrence, whereas there was little evidence of recurrence-specific gene alterations. Treatment with alkylating agents resulted in a hypermutator phenotype at different rates across the glioma subtypes, and hypermutation was not associated with differences in overall survival. Acquired aneuploidy was frequently detected in recurrent gliomas and was characterized by IDH mutation but without co-deletion of chromosome arms 1p/19q, and further converged with acquired alterations in the cell cycle and poor outcomes. The clonal architecture of each tumour remained similar over time, but the presence of subclonal selection was associated with decreased survival. Finally, there were no differences in the levels of immunoediting between initial and recurrent gliomas. Collectively, our results suggest that the strongest selective pressures occur during early glioma development and that current therapies shape this evolution in a largely stochastic manner. The GLASS Consortium studies the evolutionary trajectories of 222 patients with a diffuse glioma to aid in our understanding of tumour progression and treatment failure, Author(s): Floris P. Barthel [sup.1] [sup.2] , Kevin C. Johnson [sup.1] , Frederick S. Varn [sup.1] , Anzhela D. Moskalik [sup.1] , Georgette Tanner [sup.3] , Emre Kocakavuk [sup.1] [sup.4] [...]

Despite aggressive multimodal treatment, glioblastoma (GBM), a grade IV primary brain tumor, still portends a poor prognosis with a median overall survival of 12–16 months. The complexity of GBM treatment mainly lies in the inter- and intra-tumoral heterogeneity, which largely contributes to the treatment-refractory and recurrent nature of GBM. By paving the road towards the development of personalized medicine for GBM patients, the cancer genome atlas classification scheme of GBM into distinct transcriptional subtypes has been considered an invaluable approach to overcoming this heterogeneity. Among the identified transcriptional subtypes, the mesenchymal subtype has been found associated with more aggressive, invasive, angiogenic, hypoxic, necrotic, inflammatory, and multitherapy-resistant features than other transcriptional subtypes. Accordingly, mesenchymal GBM patients were found to exhibit worse prognosis than other subtypes when patients with high transcriptional heterogeneity were excluded. Furthermore, identification of the master mesenchymal regulators and their downstream signaling pathways has not only increased our understanding of the complex regulatory transcriptional networks of mesenchymal GBM, but also has generated a list of potent inhibitors for clinical trials. Importantly, the mesenchymal transition of GBM has been found to be tightly associated with treatment-induced phenotypic changes in recurrence. Together, these findings indicate that elucidating the governing and plastic transcriptomic natures of mesenchymal GBM is critical in order to develop novel and selective therapeutic strategies that can improve both patient care and clinical outcomes. Thus, the focus of our review will be on the recent advances in the understanding of the transcriptome of mesenchymal GBM and discuss microenvironmental, metabolic, and treatment-related factors as critical components through which the mesenchymal signature may be acquired. We also take into consideration the transcriptomic plasticity of GBM to discuss the future perspectives in employing selective therapeutic strategies against mesenchymal GBM. [ABSTRACT FROM AUTHOR]

Background: Lung cancer is associated with the highest mortality rate of all cancer types, and the most common histologic subtype of lung cancer is adenocarcinoma. To apply more effective therapeutic treatment, molecular markers that are able to predict the recurrence risk of patients with adenocarcinoma are critically needed. Mutations in TP53 tumor suppressor gene have been found in approximately 50% of lung adenocarcinoma cases, but the presence of a TP53 mutation does not always associate with increased mortality. Methods: The Cancer Genome Atlas RNA sequencing data of lung adenocarcinoma were used to define a novel gene signature for P53 deficiency. This signature was then used to calculate a sample-specific P53 deficiency score based on a patient's transcriptomic profile and tested in four independent lung adenocarcinoma microarray datasets. Results: In all datasets, P53 deficiency score was a significant predictor for recurrence-free survival where high P53 deficiency score was associated with poor survival. The score was prognostic even after adjusting for several key clinical variables including age, tumor stage, smoking status, and P53 mutation status. Furthermore, the score was able to predict recurrence-free survival in patients with stage I adenocarcinoma and was also associated with smoking status. Conclusions: The P53 deficiency score was a better predictor of recurrence-free survival compared with P53 mutation status and provided additional prognostic values to established clinical factors. Impact: The P53 deficiency score can be used to stratify early-stage patients into subgroups based on their risk of recurrence for aiding physicians to decide personalized therapeutic treatment. [ABSTRACT FROM AUTHOR]

Background: Neoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor's disease pathology. Developing genomic clinical assays that accurately categorize responders from non-responders can provide patients with the most effective therapy for their individual disease.Methods: We applied our previously developed E2F4 genomic signature to predict neoadjuvant chemotherapy response in breast cancer. E2F4 individual regulatory activity scores were calculated for 1129 patient samples across 5 independent breast cancer neoadjuvant chemotherapy datasets. Accuracy of the E2F4 signature in predicting neoadjuvant chemotherapy response was compared to that of the Oncotype DX and MammaPrint predictive signatures.Results: In all datasets, E2F4 activity level was an accurate predictor of neoadjuvant chemotherapy response, with high E2F4 scores predictive of achieving pathologic complete response and low scores predictive of residual disease. These results remained significant even after stratifying patients by estrogen receptor (ER) status, tumor stage, and breast cancer molecular subtypes. Compared to the Oncotype DX and MammaPrint signatures, our E2F4 signature achieved similar performance in predicting neoadjuvant chemotherapy response, though all signatures performed better in ER+ tumors compared to ER- ones. The accuracy of our signature was reproducible across datasets and was maintained when refined from a 199-gene signature down to a clinic-friendly 33-gene panel.Conclusion: Overall, we show that our E2F4 signature is accurate in predicting patient response to neoadjuvant chemotherapy. As this signature is more refined and comparable in performance to other clinically available gene expression assays in the prediction of neoadjuvant chemotherapy response, it should be considered when evaluating potential treatment options. [ABSTRACT FROM AUTHOR]

The role of the immune system in shaping cancer development and patient prognosis has recently become an area of intense focus in industry and academia. Harnessing the adaptive arm of the immune system for tumour eradication has shown great promise in a variety of tumour types. Differences between tissues, however, necessitate a greater understanding of the adaptive immunity programmes that are active within each tumour type. In breast cancer, adaptive immune programmes play diverse roles depending on the cellular infiltration found in each tumour. Cytotoxic T lymphocytes and T helper type 1 cells can induce tumour eradication, whereas regulatory T cells and T helper type 2 cells are known to be involved in tumour-promoting immunosuppressive responses. Complicating these matters, heterogeneous expression of hormone receptors and growth factors in different tumours leads to disparate, patient-specific adaptive immune responses. Despite this non-conformity in adaptive immune behaviours, encouraging basic and clinical results have been observed that suggest a role for immunotherapeutic approaches in breast cancer. Here, we review the literature pertaining to the adaptive immune response in breast cancer, summarize the primary findings relating to the breast tumour's biology, and discuss potential clinical immunotherapies. [ABSTRACT FROM AUTHOR]

The regulatory architecture of breast cancer is extraordinarily complex and gene misregulation can occur at many levels, with transcriptional malfunction being a major cause. This dysfunctional process typically involves additional regulatory modulators including DNA methylation. Thus, the interplay between transcription factor (TF) binding and DNA methylation are two components of a cancer regulatory interactome presumed to display correlated signals. As proof of concept, we performed a systematic motif-based in silico analysis to infer all potential TFs that are involved in breast cancer prognosis through an association with DNA methylation changes. Using breast cancer DNA methylation and clinical data derived from The Cancer Genome Atlas (TCGA), we carried out a systematic inference of TFs whose misregulation underlie different clinical subtypes of breast cancer. Our analysis identified TFs known to be associated with clinical outcomes of p53 and ER (estrogen receptor) subtypes of breast cancer, while also predicting new TFs that may also be involved. Furthermore, our results suggest that misregulation in breast cancer can be caused by the binding of alternative factors to the binding sites of TFs whose activity has been ablated. Overall, this study provides a comprehensive analysis that links DNA methylation to TF binding to patient prognosis. [ABSTRACT FROM AUTHOR]

Background: Patient gene expression information has recently become a clinical feature used to evaluate breast cancer prognosis. The emergence of prognostic gene sets that take advantage of these data has led to a rich library of information that can be used to characterize the molecular nature of a patient's cancer. Identifying robust gene sets that are consistently predictive of a patient's clinical outcome has become one of the main challenges in the field. Methods: We inputted our previously established BASE algorithm with patient gene expression data and gene sets from MSigDB to develop the gene set activity score (GSAS), a metric that quantitatively assesses a gene set's activity level in a given patient. We utilized this metric, along with patient time-to-event data, to perform survival analyses to identify the gene sets that were significantly correlated with patient survival. We then performed cross-dataset analyses to identify robust prognostic gene sets and to classify patients by metastasis status. Additionally, we created a gene set network based on component gene overlap to explore the relationship between gene sets derived from MSigDB. We developed a novel gene set based on this network's topology and applied the GSAS metric to characterize its role in patient survival. Results: Using the GSAS metric, we identified 120 gene sets that were significantly associated with patient survival in all datasets tested. The gene overlap network analysis yielded a novel gene set enriched in genes shared by the robustly predictive gene sets. This gene set was highly correlated to patient survival when used alone. Most interestingly, removal of the genes in this gene set from the gene pool on MSigDB resulted in a large reduction in the number of predictive gene sets, suggesting a prominent role for these genes in breast cancer progression. Conclusions: The GSAS metric provided a useful medium by which we systematically investigated how gene sets from MSigDB relate to breast cancer patient survival. We used this metric to identify predictive gene sets and to construct a novel gene set containing genes heavily involved in cancer progression. [ABSTRACT FROM AUTHOR]

The factors driving therapy resistance in diffuse glioma remain poorly understood. To identify treatment-associated cellular and genetic changes, we analyzed RNA and/or DNA sequencing data from the temporally separated tumor pairs of 304 adult patients with isocitrate dehydrogenase (IDH)-wild-type and IDH-mutant glioma. Tumors recurred in distinct manners that were dependent on IDH mutation status and attributable to changes in histological feature composition, somatic alterations, and microenvironment interactions. Hypermutation and acquired CDKN2A deletions were associated with an increase in proliferating neoplastic cells at recurrence in both glioma subtypes, reflecting active tumor growth. IDH-wild-type tumors were more invasive at recurrence, and their neoplastic cells exhibited increased expression of neuronal signaling programs that reflected a possible role for neuronal interactions in promoting glioma progression. Mesenchymal transition was associated with the presence of a myeloid cell state defined by specific ligand-receptor interactions with neoplastic cells. Collectively, these recurrence-associated phenotypes represent potential targets to alter disease progression. [Display omitted] • Longitudinal glioma evolution follows an IDH mutation-dependent trajectory • Hypermutation and CDKN2A deletions underlie increased proliferation at recurrence • Recurrent IDH-wild-type neoplastic cells up-regulate neuronal signaling programs • Mesenchymal transitions associate with distinct myeloid cell interactions Integrating longitudinal transcriptomic and genomic data from paired diffuse glioma samples with complementary single-cell RNA-seq and multiplex immunofluorescence datasets reveals recurrence-associated genetic and microenvironmental changes that are dependent on IDH mutation status. [ABSTRACT FROM AUTHOR]

Glioblastoma is the most common primary malignant brain tumor in adults, with a median survival of just over 1 year. The failure of available treatments to achieve remission in patients with glioblastoma (GBM) has been attributed to the presence of cancer stem cells (CSCs), which are thought to play a central role in tumor development and progression and serve as a treatment‐resistant cell repository capable of driving tumor recurrence. In fact, the property of “stemness” itself may be responsible for treatment resistance. In this study, we identify a novel long noncoding RNA (lncRNA), cancer stem cell‐associated distal enhancer of SOX2 (CASCADES), that functions as an epigenetic regulator in glioma CSCs (GSCs). CASCADES is expressed in isocitrate dehydrogenase (IDH)‐wild‐type GBM and is significantly enriched in GSCs. Knockdown of CASCADES in GSCs results in differentiation towards a neuronal lineage in a cell‐ and cancer‐specific manner. Bioinformatics analysis reveals that CASCADES functions as a super‐enhancer‐associated lncRNA epigenetic regulator of SOX2. Our findings identify CASCADES as a critical regulator of stemness in GSCs that represents a novel epigenetic and therapeutic target for disrupting the CSC compartment in glioblastoma. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors have shown great potential in treating solid tumors, inducing durable remission and prolonged survival time in responders. Despite their promise, a large fraction of patients remains unresponsive to these treatments highlighting the need for biomarkers that can predict patient sensitivity. Pre-treatment gene expression profiles for patients receiving immune checkpoint inhibitors have recently become available, establishing a new medium by which to discover biomarkers that predict therapy response. In this study, we mined for transcriptomic correlates of response by applying immune cell-derived gene expression signatures to publicly available datasets containing matched gene expression and response efficacy information. These datasets were comprised of urothelial carcinoma patients receiving anti-PD-L1 (n = 25), melanoma patients receiving anti-PD-1 (n = 28), and melanoma patients receiving anti-CTLA-4 (n = 42). We identified one signature, derived from a subpopulation of B cells, with scores that were significantly and reproducibly elevated in patients experiencing clinical benefit following therapy targeting the PD-1/PD-L1 axis and were additionally elevated in patients responsive to anti-CTLA-4 therapy. Multivariate models revealed that this signature was associated with response independent of other response-predictive biomarkers, including tumor mutation burden. Functional annotation of the signature revealed it to be associated with features indicative of an immunologically active microenvironment, including B and T cell activation as well as antigen presentation activity. The preliminary findings presented detail a transcriptomic signature associated with response to multiple checkpoint inhibitors and suggest novel biological associations that warrant further investigation. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer is one of the leading causes of cancer-related death in the world. Lung adenocarcinoma, the most common type of non-small cell lung cancer, has been well characterized as having a dense lymphocytic infiltrate, suggesting that the immune system plays an active role in shaping this cancer's growth and development. Despite these findings, our understanding of how this infiltrate affects patient prognosis and its association with lung adenocarcinoma-specific clinical factors remains limited. To address these questions, we inferred the infiltration level of six distinct immune cell types from a series of four lung adenocarcinoma gene expression datasets. We found that naive B cell, CD8+ T cell, and myeloid cell-derived expression signals of immune infiltration were significantly predictive of patient survival in multiple independent datasets, with B cell and CD8+ T cell infiltration associated with prolonged prognosis and myeloid cell infiltration associated with shorter survival. These associations remained significant even after accounting for additional clinical variables. Patients stratified by smoking status exhibited decreased CD8+ T cell infiltration and altered prognostic associations, suggesting potential immunosuppressive mechanisms in smokers. Survival analyses accounting for immune checkpoint gene expression and cellular immune infiltrate indicated checkpoint protein-specific modulatory effects on CD8+ T cell and B cell function that may be associated with patient sensitivity to immunotherapy. Together, these analyses identified reproducible associations that can be used to better characterize the role of immune infiltration in lung adenocarcinoma and demonstrate the utility in using computational approaches to systematically characterize tissue-specific tumor-immune interactions. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia (AML) is a hematopoietic disorder initiated by the leukemogenic transformation of myeloid cells into leukemia stem cells (LSCs). Preexisting gene expression programs in LSCs can be used to assess their transcriptional similarity to hematopoietic cell types. While this relationship has previously been examined on a small scale, an analysis that systematically investigates this relationship throughout the hematopoietic hierarchy has yet to be implemented. We developed an integrative approach to assess the similarity between AML patient tumor profiles and a collection of 232 murine hematopoietic gene expression profiles compiled by the Immunological Genome Project. The resulting lineage similarity scores (LSS) were correlated with patient survival to assess the relationship between hematopoietic similarity and patient prognosis. This analysis demonstrated that patient tumor similarity to immature hematopoietic cell types correlated with poor survival. As a proof of concept, we highlighted one cell type identified by our analysis, the short-term reconstituting stem cell, whose LSSs were significantly correlated with patient prognosis across multiple datasets, and showed distinct patterns in patients stratified by traditional clinical variables. Finally, we validated our use of murine profiles by demonstrating similar results when applying our method to human profiles. [ABSTRACT FROM AUTHOR]

Sporadic gliomas in companion dogs provide a window on the interaction between tumorigenic mechanisms and host environment. We compared the molecular profiles of canine gliomas with those of human pediatric and adult gliomas to characterize evolutionarily conserved mammalian mutational processes in gliomagenesis. Employing whole-genome, exome, transcriptome, and methylation sequencing of 83 canine gliomas, we found alterations shared between canine and human gliomas such as the receptor tyrosine kinases, TP53 and cell-cycle pathways, and IDH1 R132. Canine gliomas showed high similarity with human pediatric gliomas per robust aneuploidy, mutational rates, relative timing of mutations, and DNA-methylation patterns. Our cross-species comparative genomic analysis provides unique insights into glioma etiology and the chronology of glioma-causing somatic alterations. • Genomic, epigenomic, and transcriptomic characterization of sporadic glioma in dogs • Somatic alterations in canine glioma converge with human glioma drivers • Canine glioma resemble pediatric human glioma by mutation rate and DNA methylation • Microenvironment similarity between canine and human pediatric and adult glioma Amin et al. characterize the molecular landscape of canine gliomas and compare it with that of human pediatric and adult gliomas, revealing high similarity between human pediatric and canine gliomas. The cross-species analysis identifies conserved glioma drivers and aneuploidy as a hallmark of high-grade disease. [ABSTRACT FROM AUTHOR]