Transcriptional gene signatures : passing the restriction point for routine clinical implementation

Uncontrolled cell growth and cell division are central to the process of tumorigenesis and a number of gene expression signatures have been developed based on genes that are involved in the cell cycle. Notably, gene expression signatures are used extensively in breast cancer research to examine the disease at a molecular level to describe tumour progression, treatment response and patients’ survival. The subject of this thesis is to explore the potential prognostic capacity of gene expression signatures in breast cancer and additionally, determine the prognostic capacity of a transcriptomic cell cycle activity (CCS) signature within variety of cancer types. Several breast cancer gene expression signatures have emerged and been validated over the past two decades in large retrospective clinical trials. Although the clinical impact of these signatures has been clearly demonstrated, breast cancer therapeutic guidelines are still established on the basis of immunohistochemical markers (IHC) such as estrogen (ER), progesterone (PR), human epidermal growth factor 2 (HER2) and the proliferation marker Ki67. In Study I, the additional prognostic information derived from the combination of gene expression signatures and IHC/Ki67 was investigated in two Swedish breast cancer cohorts. Cohort I is comprised of 621 individuals with primary breast cancer tumours diagnosed between 1997 and 2005 in Stockholm region of Sweden. Cohort II consists of 484 individuals with primary breast tumours who diagnosed and received primary therapy in the Uppsala region of Sweden between 1987 and 1989. In Cohort I, Recurrence score (RS) and PAM50 gene expression signatures added prognostic information beyond Ki67 and IHC subtypes while only IHC subtypes provided additional prognostic information to all gene expression signatures with the exception of PAM50 gene signature in this cohort. Similar results were observed in Cohort II. The ability of gene expression signatures to provide prognostic and treatment predictive information has been tested in primary breast tumours; however, their capability to provide similar information in the metastatic breast cancer (MBC) patients has not been investigated. In Study II, the prognostic capacity of gene expression signatures in breast cancer was evaluated in the metastatic setting in a Swedish multicenter randomized clinical trial known as “TEX” with 304 patients diagnosed with advanced locoregional or distant breast cancer relapse. A large number of tumours were classified into intermediate or high4 risk groups by all gene expression signatures. PAM50 was the only gene expression signature that provided prognostic information from lymph node (LN) metastases. In Study III, the prognostic and treatment-specific potential of CCND1 amplification was assessed in two breast cancer cohorts with 1965 and 340 patients, respectively. In the combined cohort, patients with CCND1-amplified tumours show worse survival in ER+/HER2-/LN-, luminal A and luminal B subtypes. Moreover, luminal A subtype with CCND1-amplified tumours shared similar gene expression changes with and luminal B subtype. In Study IV, the DNA mutations and chromosome arm-level aneuploidy within tumours with different cell cycle activity (CCS) were explored. We showed that cell cycle activity varied broadly among and within different cancer types. Two well-known oncogenes (TP53 and PIK3CA) exhibit the highest rate of mutations within different CCS groups. Furthermore, chromosomal arm level aberrations present in all CCS groups with a higher number of gains in 7p, 20q whereas deletions were more frequent within 17p and 8p arms. In the survival analysis, patients with higher CCS tumours show worse Progression-free interval relative to low and intermediate CCS groups. In conclusions, we have shown that PAM50 and RS gene expression signatures can add prognostic information to Ki67 and IHC subtypes; however, IHC subtypes did not add any prognostic information to PAM50 signature. Moreover, PAM50 gene expression signature can provide prognostic information from LN metastases in MBC patients. Additionally, CCND1 gene amplification has the potential to stratify patients with worse survival outcome within good-prognosis luminal A subtype tumours. Finally, we have demonstrated that CCS can provide independent prognostic information across cancer types

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

The 5-Hydroxymethylcytosine Landscape of Prostate Cancer

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease. SIGNIFICANCE: In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880.publishedVersionPeer reviewe

B cell-related gene signature and cancer immunotherapy response

BackgroundB lymphocytes have multifaceted functions in the tumour microenvironment, and their prognostic role in human cancers is controversial. Here we aimed to identify tumour microenvironmental factors that influence the prognostic effects of B cells.MethodsWe conducted a gene expression analysis of 3585 patients for whom the clinical outcome information was available. We further investigated the clinical relevance for predicting immunotherapy response.ResultsWe identified a novel B cell-related gene (BCR) signature consisting of nine cytokine signalling genes whose high expression could diminish the beneficial impact of B cells on patient prognosis. In triple-negative breast cancer, higher B cell abundance was associated with favourable survival only when the BCR signature was low (HR = 0.68, p = 0.0046). By contrast, B cell abundance had no impact on prognosis when the BCR signature was high (HR = 0.93, p = 0.80). This pattern was consistently observed across multiple cancer types including lung, colorectal, and melanoma. Further, the BCR signature predicted response to immune checkpoint blockade in metastatic melanoma and compared favourably with the established markers.ConclusionsThe prognostic impact of tumour-infiltrating B cells depends on the status of cytokine signalling genes, which together could predict response to cancer immunotherapy

Main component of soft tissue artifact of the upper-limbs with respect to different functional, daily life and sports movements.

Soft tissue artifact (STA) is the main source of error in kinematic estimation of human movements based on skin markers. Our objective was to determine the components of marker displacements that best describe STA of the shoulder and arm (i.e. clavicle, scapula and humerus). Four participants performed arm flexion and rotation, a daily-life and a sports movement. Three pins with reflective markers were inserted into the clavicle, scapula and humerus. In addition, up to seven skin markers were stuck on each segment. STA was described with a modal approach: individual marker displacements or marker-cluster (i.e. translations, rotations, homotheties and stretches) relative to the local segment coordinate system defined by markers secured to the pins. The modes were then ranked according to the percentage of total STA energy that they explained. Both individual skin marker displacements and marker-cluster geometrical transformations were task-, location-, segment- and subject-specific. However, 85% of the total STA energy was systematically explained by the rigid transformations (i.e. translations and rotations of the marker-cluster). In conclusion, large joint dislocations and limited efficiency of least squares bone pose estimators are expected for the computation of upper limb joint kinematics from skin markers. Future developments shall consider the rigid transformations of marker-clusters in the implementation of an STA model to reduce its effects on kinematics estimation

Reclassifying tumour cell cycle activity in terms of its tissue of origin

Genomic alterations resulting in loss of control over the cell cycle is a fundamental hallmark of human malignancies. Whilst pan-cancer studies have broadly assessed tumour genomics and their impact on oncogenic pathways, analyses taking the baseline signalling levels in normal tissue into account are lacking. To this end, we aimed to reclassify the cell cycle activity of tumours in terms of their tissue of origin and determine if any common DNA mutations, chromosome arm-level changes or signalling pathways contribute to an increase in baseline corrected cell cycle activity. Combining normal tissue and pan-cancer data from over 13,000 samples we demonstrate that tumours of gynaecological origin show the highest levels of corrected cell cycle activity, partially owing to hormonal signalling and gene expression changes. We also show that normal and tumour tissues can be separated into groups (quadrants) of low/high cell cycle activity and propose the hypothesis of an upper limit on these activity levels in tumours.Published versionThis work was supported by the Iris, Stig och Gerry Castenbäcks Stiftelse for cancer research (N.P.T.); the King Gustaf V Jubilee Foundation (N.P.T.); the Stockholm Cancer Society (Cancerföreningen i Stockholm to L.S.L.); the Swedish Cancer Society (Cancerfonden, N.P.T. grant number: 200802; L.S.L. grant number: 190140); the Swedish Research Council (Vetenskapsrådet, grant number 2020-02466 to L.S.L); the Swedish Research Council for Health, Working life and Welfare, (FORTE, grant number 2019-00477 to L.S.L.); ALF medicine (grant number LS2018-1157 to L.S.L.) and the Gösta Milton Donation Fund (Stiftelsen Gösta Miltons donationsfond, to L.S.L. Open access funding provided by Karolinska Institute

The long-term prognostic and predictive capacity of cyclin D1 gene amplification in 2305 breast tumours

Abstract Background Use of cyclin D1 (CCND1) gene amplification as a breast cancer biomarker has been hampered by conflicting assessments of the relationship between cyclin D1 protein levels and patient survival. Here, we aimed to clarify its prognostic and treatment predictive potential through comprehensive long-term survival analyses. Methods CCND1 amplification was assessed using SNP arrays from two cohorts of 1965 and 340 patients with matching gene expression array and clinical follow-up data of over 15 years. Kaplan-Meier and multivariable Cox regression analyses were used to determine survival differences between CCND1 amplified vs. non-amplified tumours in clinically relevant patient sets, within PAM50 subtypes and within treatment-specific subgroups. Boxplots and differential gene expression analyses were performed to assess differences between amplified vs. non-amplified tumours within PAM50 subtypes. Results When combining both cohorts, worse survival was found for patients with CCND1-amplified tumours in luminal A (HR = 1.68; 95% CI, 1.15–2.46), luminal B (1.37; 1.01–1.86) and ER+/LN−/HER2− (1.66; 1.14–2.41) subgroups. In gene expression analysis, CCND1-amplified luminal A tumours showed increased proliferation (P < 0.001) and decreased progesterone (P = 0.002) levels along with a large overlap in differentially expressed genes when comparing luminal A and B-amplified vs. non-amplified tumours. Conclusions Our results indicate that CCND1 amplification is associated with worse 15-year survival in ER+/LN−/HER2−, luminal A and luminal B patients. Moreover, luminal A CCND1-amplified tumours display gene expression changes consistent with a more aggressive phenotype. These novel findings highlight the potential of CCND1 to identify patients that could benefit from long-term treatment strategies