Search

Nonsyndromic orofacial clefts (NSOFCs) represent a large proportion (70%-80%) of all OFCs. They can be broadly categorized into nonsyndromic cleft lip with or without cleft palate (NSCL/P) and nonsyndromic cleft palate only (NSCPO). Although NSCL/P and NSCPO are considered etiologically distinct, recent evidence suggests the presence of shared genetic risks. Thus, we investigated the genetic overlap between NSCL/P and NSCPO using African genome-wide association study (GWAS) data on NSOFCs. These data consist of 814 NSCL/P, 205 NSCPO cases, and 2159 unrelated controls. We generated common single-nucleotide variants (SNVs) association summary statistics separately for each phenotype (NSCL/P and NSCPO) under an additive genetic model. Subsequently, we employed the pleiotropic analysis under the composite null (PLACO) method to test for genetic overlap. Our analysis identified two loci with genome-wide significance (rs181737795 [p = 2.58E-08] and rs2221169 [p = 4.5E-08]) and one locus with marginal significance (rs187523265 [p = 5.22E-08]). Using mouse transcriptomics data and information from genetic phenotype databases, we identified MDN1, MAP3k7, KMT2A, ARCN1, and VADC2 as top candidate genes for the associated SNVs. These findings enhance our understanding of genetic variants associated with NSOFCs and identify potential candidate genes for further exploration., (© 2024 The Authors. Genetic Epidemiology published by Wiley Periodicals LLC.)

Non-syndromic orofacial clefts (NSOFCs) are common birth defects with a complex etiology. While over 60 common risk loci have been identified, they explain only a small proportion of the heritability for NSOFCs. Rare variants have been implicated in the missing heritability. Thus, our study aimed to identify genes enriched with nonsynonymous rare coding variants associated with NSOFCs. Our sample included 814 non-syndromic cleft lip with or without palate (NSCL/P), 205 non-syndromic cleft palate only (NSCPO), and 2150 unrelated control children from Nigeria, Ghana, and Ethiopia. We conducted a gene-based analysis separately for each phenotype using three rare-variants collapsing models: (1) protein-altering (PA), (2) missense variants only (MO); and (3) loss of function variants only (LOFO). Subsequently, we utilized relevant transcriptomics data to evaluate associated gene expression and examined their mutation constraint using the gnomeAD database. In total, 13 genes showed suggestive associations (p = E-04). Among them, eight genes (ABCB1, ALKBH8, CENPF, CSAD, EXPH5, PDZD8, SLC16A9, and TTC28) were consistently expressed in relevant mouse and human craniofacial tissues during the formation of the face, and three genes (ABCB1, TTC28, and PDZD8) showed statistically significant mutation constraint. These findings underscore the role of rare variants in identifying candidate genes for NSOFCs., (© 2024. The Author(s).)

In April 2023, the National Cancer Institute offered a roadmap for cancer research to achieve Cancer Moonshot goals. To reach these goals requires making progress for all cancers, not just those that are most common. Achieving progress against rare cancers, as well as common cancers, requires involvement of large clinical research networks. In 2020, the Patient-Centered Outcomes Research Institute (PCORI) launched an initiative on Conducting Rare Disease Research using PCORnet, the National Patient-Centered Clinical Research Network. The purpose of this commentary is to introduce the broader community of cancer researchers to the PCORnet NET-PRO study (comparing the effects of different treatment approaches for neuroendocrine tumors on patient-reported outcomes) thereby demonstrating how researchers can use the PCORnet infrastructure to conduct large-scale patient-centered studies of rare cancers., (© 2024 The Authors. Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society.)

Background: Older patients with cancer often have lower surgery rates and survival than younger patients, but this may reflect surgical contraindications of advanced disease, comorbidities, and frailty - and not necessarily under-treatment., Objectives: This review aims to describe variations in surgery rates and observed or net survival among younger (<75) and older (≥75) patients with breast, lung and colorectal cancer, while taking account of pre-existing health factors, in order to understand how under-treatment is defined and estimated in the literature., Method: MEDLINE, EMBASE, Web of Science and PubMed databases were searched for studies reporting surgery rates and observed or net survival among younger and older patients with breast, lung, and colorectal cancer. Study quality was assessed using the Newcastle Ottawa Scale, and random effects meta-analyses were used to combine study results. The I-squared statistic and subgroup analyses were used to assess heterogeneity., Results: Thirty relatively high-quality studies of patients with breast (230,200; 71.9%), lung (77,573; 24.2%), and colorectal (12,407; 3.9%) cancers were identified. Compared to younger patients, older patients were less likely to receive surgical treatment for 1) breast cancer after adjusting for comorbidity, performance status (PS), functional status and patient choice, 2) lung cancer after accounting for stage, comorbidity, PS, and 3) colorectal cancer after adjusting for stage, comorbidity, and gender. The pooled unadjusted analyses showed lower surgery receipt in older patients with breast (odds ratio [OR] 0.31, 95% confidence interval [CI] 0.13-0.78), lung (OR 0.54, 95% CI 0.39-0.75), and colorectal (OR 0.59, 95% CI 0.51-0.68) cancer. In separate analyses, older patients with breast, lung and colorectal cancer had lower observed and net survival, compared to younger patients., Conclusions: Lower surgery rates in older patients may contribute to their poorer survival compared to younger patients. Future research quantifying under-treatment should include necessary clinical factors, patient choice, patient's quality of life and a statistically-robust approach, which will demonstrate how much of the survival deficit in older patients is due to their receiving lower surgery rates., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objective: We aim to evaluate the impact gynecologic oncologists have on ovarian cancer adjuvant chemotherapy care from their role as surgeons recommending adjuvant chemotherapy care and their role as adjuvant chemotherapy providers while considering rural-urban differences., Methods: Multivariable adjusted logistic regressions and Cox proportional hazards models were developed using a population-based, retrospective cohort of stage II-IV and unknown stage ovarian cancer patients diagnosed in Iowa, Kansas, and Missouri in 2010-2012 whose medical records were abstracted in 2017-2018., Results: Gynecologic oncologist surgeons (versus other type of surgeon) were associated with increased odds of adjuvant chemotherapy initiation (adjusted odds ratio (OR) 2.18; 95% confidence interval (CI) 1.10-4.33) and having a gynecologic oncologist adjuvant chemotherapy provider (OR 10.0; 95% CI 4.58-21.8). Independent of type of surgeon, rural patients were less likely to have a gynecologic oncologist chemotherapy provider (OR 0.52; 95% CI 0.30-0.91). Gynecologic oncologist adjuvant chemotherapy providers (versus other providers) were associated with decreased surgery-to-chemotherapy time (rural: 6 days; urban: 8 days) and increased distance to chemotherapy (rural: 22 miles; urban: 11 miles). Rural women (versus urban) traveled 38 miles farther when their chemotherapy provider was a gynecologic oncologist and 27 miles farther when it was not., Conclusion: Gynecologic oncologist surgeons may impact adjuvant chemotherapy initiation. Gynecologic oncologists serving as adjuvant chemotherapy providers were associated with some care benefits, such as reduced time from surgery-to-chemotherapy, and some care barriers, such as travel distance. The barriers and benefits of having a gynecologic oncologist involved in adjuvant chemotherapy care, including rural-urban differences, warrant further research in other populations., Competing Interests: Declaration of Competing Interest The authors do not have conflicts of interest., (Copyright © 2021 Elsevier Inc. All rights reserved.)