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NTRK gene fusions are rare somatic mutations found across cancer types with promising targeted therapies emerging. Healthcare systems face significant challenges in integrating these treatments, with uncertainty in prevalence and optimal testing methods to identify eligible patients. We performed a systematic review of NTRK fusion prevalence to inform efficient diagnostic screening and scale of therapeutic uptake. We searched Medline, Embase and Cochrane databases on 31/03/2021. Inclusion criteria were studies reporting fusion rates in solid tumours, English language, post-2010 publication and minimum sample size. Critical appraisal was performed using a custom 11-item checklist. Rates were collated by cancer type and pooled if additional synthesis criteria were met. 160 studies were included, with estimates for 15 pan-cancer and 429 specific cancer types (63 paediatric). Adult pan-cancer estimates ranged 0.03–0.70%, with higher rates found in RNA-based assays. In common cancers, rates were consistently below 0.5%. Rare morphological subtypes, colorectal microsatellite instability, and driver mutation exclusion cancers had higher rates. Only 35.6% of extracted estimates used appropriate methods and sample size to identify NTRK fusions. NTRK fusion-positive cancers are rare and widely distributed across solid tumours. Small-scale, heterogeneous data confound prevalence prediction. Further large-scale, standardised genomic data are needed to characterise NTRK fusion epidemiology.

Additional file 6. Selection of colon and rectal cancer cases from the 45 and Up Study cohort for inclusion in this study.

Additional file 3. Colon and rectal cancer cases assigned to each treatment category based on treatment received in the 0-1, 0-2, and 0-5 years after diagnosis, by spread of disease.

Additional file 9. Cancer-specific 1- and 2-year survival after a diagnosis of colon or rectal cancer, by spread of disease, based on NSWCR data to 31 December 2013.

Additional file 5. Detailed information on the subdistribution, separate Cox’s cause-specific and joint Cox hazard model and application of each method using the SAS procedure PHREG.

Additional file 13. Multivariable adjusted hazard ratios for associations between characteristics of rectal cancer cases and treatment received within 2 years from the cancer diagnosis. SHRs from the competing risks Fine-Gray model, and HRs from the cause-specific Cox hazard and joint Cox model were adjusted for all characteristics in the table. P-values with two asterisks (**) are significant after Bonferroni adjustment for 16 tests (i.e., p

Additional file 12. Multivariable adjusted hazard ratios for associations between characteristics of colon cancer cases and cancer treatment received within 2 years after cancer diagnosis. Subdistribution hazard ratios (SHRs) from the competing risks Fine-Gray model, and hazard ratios (HRs) from the cause-specific Cox hazard and joint Cox model were adjusted for all characteristics shown in the table. P-values with two asterisks (**) are significant after Bonferroni adjustment for 16 tests (i.e., p

Additional file 8. Overall 1-, 2-, 3- and 5-year survival after a diagnosis of colon or rectal cancer, by spread of disease, based on RBDM data to June 2017.

Additional file 1. Diagnosis codes used to identify conditions in the Admitted Patient Data Collection and derive Charlson’s comorbidity index score. The total index score was calculated as the total sum of updated weights for conditions captured in the 5 years prior to diagnosis.

Additional file 4. Characteristics of colon cancer and rectal cancer cases by type of cancer treatment received in the 0-2 years after diagnosis.

Additional file 10. Time from diagnosis to first cancer treatment received in the 0-2 years after diagnosis, by treatment category. The cumulative percentage was obtained using the cumulative incidence function (CIF).

Additional file 7. Age and spread of disease at diagnosis of colon and rectal cancer cases in the 45 and Up Study, and of all cases in NSW and Australia.

Additional file 2. Codes used to identify cancer treatment procedures in the different health datasets.

Additional file 1: Supplementary Notes.

Additional file 2. Figure showing comparison of age-standardised incidence rates for cancers of the lung, colorectum, prostate and breast including death certificate only and people with multiple cancers for New South Wales and Australia, using data from Cancer Data in Australia, 1982-2016. Age-standardised using the Australian population in 2001.

Additional file 4: Cumulative percentage of female 45 and Up Study participants with self-reported age at menopause (years) below each age threshold. This figure illustrates the approach used to determine the age threshold for the reference approach (here, age ��� 55 years at baseline). The cumulative percentage of female participants with self-reported age at menopause below each age threshold is based on women aged 55 + years at baseline who had experienced natural menopause and reported their age at menopause, never used MHT, have not had an oophorectomy nor a hysterectomy, and were not using oral contraceptives at baseline (n = 30,591).

Additional file 7: Correspondence between directly self-reported, detailed derived and consolidated derived menopausal status in the 45 and Up Study (based on the reference approach, here, age ��� 55 years at baseline). The diagram illustrates the classification of female 45 and Up Study participants by directly self-reported menopausal status (left vertical bar), detailed derived menopausal status (middle vertical bar) and consolidated derived menopausal status (right vertical bar). The horizontal bands represent the re-classification of participants between the different status assignments, coloured according to the directly self-reported menopausal status. For example, ~ 19,000 participants had directly self-reported ���not sure��� status (light blue horizontal bands), of whom ~ 8,000 were assigned the ���no periods due to hysterectomy��� detailed derived menopausal status. Of these ~ 5,500 were then assigned ���post-menopause��� consolidated derived status in the final step, while ~ 2,500 were assigned ���unknown��� consolidated derived status.

Additional file 1. Table showing harmonisation of categories for characteristics across the 45 and Up Study and survey questionnaires. A. Harmonisation of categories for 45 and Up Study and ABS Census. B. Harmonisation of categories for 45 and Up Study, NDSHS and ANHS.

Additional file 3: Supplementary Methods.

Additional file 5: Diagnostic genetic testing among patients with complete, high-risk tumour test results who had a referral to genetic services.

Additional file 4. Calculation of standardised incidence ratios.

Additional file 2: Conceptual map of a step-wise tumour testing approach for LS.

Additional file 2: Systematic categorisation of the combinations of interventions that could affect menopausal status and frequency of each category in the 45 and Up Study (n = 142,973). Final categories are shown in dark red.

Additional file 7. Figure of unweighted and weighted Standardised Incidence Ratios (SIRs) for cancers of the lung, colorectum, breast and prostate for the 45 and Up Study cohort compared to the NSW and Australian population, using NSW Cancer Registry data (2009-2013).

Additional file 5: Frequency of self-reported menopausal status of female 45 and Up Study participants by single year age at baseline. This table illustrates the approach used to determine the age threshold for the conservative approach (here, ��� age 57 years at baseline). The frequency is based on female participants who had never used MHT, have not had an oophorectomy nor a hysterectomy, and did not use oral contraceptives at baseline (n = 63,742).

Additional file 6: Examples of different terminology for LS tumour test results used in pathology reports.

Additional file 8: Australian Classification of Health Interventions (ACHI) procedure codes mapped to consensus list of MBS items as an alternative to identify colorectal resections (in conjunction with ICD codes for CRC diagnosis).

Additional file 7: Consensus list of Medicare Benefit Schedule (MBS) procedure codes used to identify colorectal resections (in conjunction with ICD codes for CRC diagnosis).

Additional file 6: Cumulative percentage of female 45 and Up Study participants who had experienced natural menopause by age at baseline. This figure illustrates the approach used to determine the age threshold for the least-conservative approach (here, age ��� 54 years at baseline). The percentage is based on all female 45 and Up Study participants who had never used MHT, have not had an oophorectomy nor a hysterectomy, and were not using oral contraceptives at baseline (n = 41,891).

Additional file 8: Age at menopause, prevalence of hysterectomy, bilateral oophorectomy and current MHT use in the 45 and Up Study compared to other Australian studies. 1 Estimates from InterLACE Study Team. Variations in reproductive events across life: a pooled analysis of data from 505 147 women across 10 countries. Hum Reprod. 2019;34(5):881���93. 2 Estimates from Wilson LF, Pandeya N, Byles J, Mishra GD. Hysterectomy status and all-cause mortality in a 21-year Australian population-based cohort study. Am J Obstet Gynecol. 2019;220(1):83 e1���e11. 3 Estimates from Velentzis LS, Banks E, Sitas F, Salagame U, Tan EH, Canfell K. Use of Menopausal Hormone Therapy and Bioidentical Hormone Therapy in Australian Women 50 to 69 Years of Age: Results from a National, Cross-Sectional Study. PloS one. 2016;11(3):e0146494-e.

Additional file 3: Assignment of the detailed derived menopausal status based on self-reported menopausal status, oophorectomy, hysterectomy, MHT use, and the timing of these interventions for women in the 45 and Up Study. Fewer than 5 women, actual number suppressed to preserve confidentiality.^ Missing either one or more responses to ever had a hysterectomy, oophorectomy, ever used MHT or self-reported menopause.

Additional file 4: P-values for pairwise differences for missing test results and referrals to genetics services between hospitals.

Additional file 3. Development of raking weights.

Study personnel roles and responsibilities; data variables; focus group schedules; overview of Implementation Lead training. (DOCX 44 kb)

Master consent forms. (PDF 398 kb)

SPIRIT checklist. (DOC 127 kb)

Study personnel roles and responsibilities; data variables; focus group schedules; overview of Implementation Lead training. (DOCX 44 kb)

Master consent forms. (PDF 398 kb)

Item does not contain fulltext The XXI World Congress of Psychiatric Genetics (WCPG), sponsored by the International Society of Psychiatric Genetics (ISPG), took place in Boston, Massachusetts, on 17-21 October 2013. Approximately 900 participants gathered to discuss the latest findings in this rapidly advancing field. The following report was written by student travel awardees. Each was assigned one or more sessions as a rapporteur. This manuscript represents topics covered in most, but not all of the oral presentations during the conference, and contains some of the major notable new findings reported.

The Schwinger-boson theory of the frustrated square lattice antiferromagnet yields a stable, gapped $\mathbb{Z}_2$ spin liquid ground state with time-reversal symmetry, incommensurate spin correlations and long-range Ising-nematic order. We obtain an equivalent description of this state using fermionic spinons (the fermionic spinons can be considered to be bound states of the bosonic spinons and the visons). Upon doping, the $\mathbb{Z}_2$ spin liquid can lead to a fractionalized Fermi liquid (FL*) with small Fermi pockets of electron-like quasiparticles, while preserving the $\mathbb{Z}_2$ topological and Ising-nematic orders. We describe a Higgs transition out of this deconfined metallic state into a confining superconducting state which is usually of the Fulde-Ferrell-Larkin-Ovchinnikov type, with spatial modulation of the superconducting order., Comment: 26+20 pages, 5 figures, 3 tables; With minor edits and additional references

BackgroundUnintended pregnancy is common and disproportionately occurs among low-income and African-American (AA) women. Male partners may influence women's risk of unintended pregnancy through reproductive coercion, although studies have not assessed whether racial differences in reproductive coercion impact AA women's disparate risk for unintended pregnancy. We sought to describe women's experiences with pregnancy-promoting behaviors by male partners and explore differences in such experiences by race.MethodsSemistructured interviews were conducted with low-income, AA and White women aged 18 to 45 years recruited from reproductive health clinics in Western Pennsylvania to explore contextual factors that shape women's contraceptive behaviors. Narratives were analyzed using content analysis and the constant comparison method.FindingsAmong the 66 participants (36 AA and 30 White), 25 (38%) described experiences with male partner reproductive coercion. Narratives provided accounts of contraceptive sabotage, verbal pressure to promote pregnancy and specific pregnancy outcomes, and potential motives behind these behaviors. AA women in the sample reported experiences of reproductive coercion more often than White women (53% and 20%, respectively). AA women were also more likely than White women to attribute a current or prior pregnancy to reproductive coercion. AA women identified relationship transiency and impending incarceration as potential motivations for men to secure a connection with a female partner via pregnancy.ConclusionsOur findings suggest that reproductive coercion may be a factor contributing to disparities in unintended pregnancy. More research, including population-level studies, is needed to determine the impact of reproductive coercion on unintended pregnancy and to understand the social and structural factors associated with pregnancy-promoting behaviors.

ContextYoung Latinos in the United States are at high risk for STDs and are less likely than other youth to use condoms. To our knowledge, no studies have examined the relationship between sexual values and condom negotiation strategies among young Latinos.MethodsCross-sectional data collected in 2003-2006 from 571 Latino women and men aged 16-22 in the San Francisco Bay Area were used to examine associations between sexual values (e.g., considering sexual talk disrespectful or female virginity important) and use of strategies to engender or avoid condom use. Linear regression analyses were used to identify such associations while adjusting for potential covariates and gender interactions.ResultsAmong women, sexual comfort and comfort with sexual communication were positively associated with frequency of direct communication to foster condom use; the importance of female premarital virginity and levels of sexual self-acceptance were positively associated with expressing dislike of condoms to avoid using them; and levels of sexual self-acceptance were negatively associated with expressing dislike of condoms to avoid using them. Moreover, the degrees to which women considered sexual talk disrespectful and female virginity important were positively associated with the frequency with which they shared risk information as a condom use strategy. Among both sexes, the importance that respondents placed on premarital female virginity was negatively associated with use of direct communication strategies.ConclusionResearchers designing interventions to influence Latino youths' sexual decision making and behaviors should consider including program components that address sexual values.

Osteoarthritis causes debilitating pain and disability, resulting in a considerable socioeconomic burden, yet no drugs are available that prevent disease onset or progression. Here, we develop, validate and use rapid-throughput imaging techniques to identify abnormal joint phenotypes in randomly selected mutant mice generated by the International Knockout Mouse Consortium. We identify 14 genes with functional involvement in osteoarthritis pathogenesis, including the homeobox gene Pitx1, and functionally characterize 6 candidate human osteoarthritis genes in mouse models. We demonstrate sensitivity of the methods by identifying age-related degenerative joint damage in wild-type mice. Finally, we phenotype previously generated mutant mice with an osteoarthritis-associated polymorphism in the Dio2 gene by CRISPR/Cas9 genome editing and demonstrate a protective role in disease onset with public health implications. We hope this expanding resource of mutant mice will accelerate functional gene discovery in osteoarthritis and offer drug discovery opportunities for this common, incapacitating chronic disease.

Osteoarthritis (OA) is a common disease characterized by cartilage degeneration and joint remodeling. The underlying molecular changes underpinning disease progression are incompletely understood. We investigated genes and pathways that mark OA progression in isolated primary chondrocytes taken from paired intact versus degraded articular cartilage samples across 38 patients undergoing joint replacement surgery (discovery cohort: 12 knee OA, replication cohorts: 17 knee OA, 9 hip OA patients). We combined genome-wide DNA methylation, RNA sequencing, and quantitative proteomics data. We identified 49 genes differentially regulated between intact and degraded cartilage in at least two -omics levels, 16 of which have not previously been implicated in OA progression. Integrated pathway analysis implicated the involvement of extracellular matrix degradation, collagen catabolism and angiogenesis in disease progression. Using independent replication datasets, we showed that the direction of change is consistent for over 90% of differentially expressed genes and differentially methylated CpG probes. AQP1, COL1A1 and CLEC3B were significantly differentially regulated across all three -omics levels, confirming their differential expression in human disease. Through integration of genome-wide methylation, gene and protein expression data in human primary chondrocytes, we identified consistent molecular players in OA progression that replicated across independent datasets and that have translational potential.

Funder: NIHR Cambridge Biomedical Research Centre, Objectives: To determine how gene expression profiles in osteoarthritis joint tissues relate to patient phenotypes and whether molecular subtypes can be reproducibly captured by a molecular classification algorithm. Methods: We analysed RNA sequencing data from cartilage and synovium in 113 osteoarthritis patients, applying unsupervised clustering and Multi-Omics Factor Analysis to characterise transcriptional profiles. We tested the association of the molecularly defined patient subgroups with clinical characteristics from electronic health records. Results: We detected two patient subgroups in low-grade cartilage (showing no/minimal degeneration, cartilage normal/softening only), with differences associated with inflammation, extracellular matrix-related and cell adhesion pathways. The high-inflammation subgroup was associated with female sex (OR 4.12, p=0.0024) and prescription of proton pump inhibitors (OR 4.21, p=0.0040). We identified two independent patient subgroupings in osteoarthritis synovium: one related to inflammation and the other to extracellular matrix and cell adhesion processes. A seven-gene classifier including MMP13, APOD, MMP2, MMP1, CYTL1, IL6 and C15orf48 recapitulated the main axis of molecular heterogeneity in low-grade knee osteoarthritis cartilage (correlation ρ=−0.88, p

OBJECTIVES: To identify molecular differences between chondrocytes from osteophytic and articular cartilage tissue from OA patients. METHODS: We investigated genes and pathways by combining genome-wide DNA methylation, RNA sequencing and quantitative proteomics in isolated primary chondrocytes from the cartilaginous layer of osteophytes and matched areas of low- and high-grade articular cartilage across nine patients with OA undergoing hip replacement surgery. RESULTS: Chondrocytes from osteophytic cartilage showed widespread differences to low-grade articular cartilage chondrocytes. These differences were similar to, but more pronounced than, differences between chondrocytes from osteophytic and high-grade articular cartilage, and more pronounced than differences between high- and low-grade articular cartilage. We identified 56 genes with significant differences between osteophytic chondrocytes and low-grade articular cartilage chondrocytes on all three omics levels. Several of these genes have known roles in OA, including ALDH1A2 and cartilage oligomeric matrix protein, which have functional genetic variants associated with OA from genome-wide association studies. An integrative gene ontology enrichment analysis showed that differences between osteophytic and low-grade articular cartilage chondrocytes are associated with extracellular matrix organization, skeletal system development, platelet aggregation and regulation of ERK1 and ERK2 cascade. CONCLUSION: We present a first comprehensive view of the molecular landscape of chondrocytes from osteophytic cartilage as compared with articular cartilage chondrocytes from the same joints in OA. We found robust changes at genes relevant to chondrocyte function, providing insight into biological processes involved in osteophyte development and thus OA progression.

Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis.

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985), Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156), Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis.

OBJECTIVES: To determine how gene expression profiles in osteoarthritis joint tissues relate to patient phenotypes and whether molecular subtypes can be reproducibly captured by a molecular classification algorithm. METHODS: We analysed RNA sequencing data from cartilage and synovium in 113 osteoarthritis patients, applying unsupervised clustering and Multi-Omics Factor Analysis to characterise transcriptional profiles. We tested the association of the molecularly defined patient subgroups with clinical characteristics from electronic health records. RESULTS: We detected two patient subgroups in low-grade cartilage (showing no/minimal degeneration, cartilage normal/softening only), with differences associated with inflammation, extracellular matrix-related and cell adhesion pathways. The high-inflammation subgroup was associated with female sex (OR 4.12, p=0.0024) and prescription of proton pump inhibitors (OR 4.21, p=0.0040). We identified two independent patient subgroupings in osteoarthritis synovium: one related to inflammation and the other to extracellular matrix and cell adhesion processes. A seven-gene classifier including MMP13, APOD, MMP2, MMP1, CYTL1, IL6 and C15orf48 recapitulated the main axis of molecular heterogeneity in low-grade knee osteoarthritis cartilage (correlation ρ=-0.88, p

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985), Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156), Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis.