From flocking birds to swarming insects, interactions of organisms large and small lead to the emergence of collective dynamics. Here, we report striking collective swimming of bovine sperm in dynamic clusters, enabled by the viscoelasticity of the fluid. Sperm oriented in the same direction within each cluster, and cluster size and cell-cell alignment strength increased with viscoelasticity of the fluid. In contrast, sperm swam randomly and individually in Newtonian (nonelastic) fluids of low and high viscosity. Analysis of the fluid motion surrounding individual swimming sperm indicated that sperm-fluid interaction was facilitated by the elastic component of the fluid. In humans, as well as cattle, sperm are naturally deposited at the entrance to the cervix and must swim through viscoelastic cervical mucus and other mucoid secretions to reach the site of fertilization. Collective swimming induced by elasticity may thus facilitate sperm migration and contribute to successful fertilization. We note that almost all biological fluids (e.g. mucus and blood) are viscoelastic in nature, and this finding highlights the importance of fluid elasticity in biological function.
5582 Background: Primary mucinous ovarian cancers (MOC) are histopathologically challenging to differentiate from ovarian metastases of non-gynecologic origin, with this distinction being critical for appropriate management and prognosis. We compared the somatic gene variant landscape of MOC to that of non-gynecologic mucinous tumors. Methods: Data were extracted from the American Association for Cancer Research’s (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) database version 13.0 via cBioPortal. This publicly available, multi-institutional database provides next generation sequencing (NGS) genomic profiles of tumors. We queried this database for samples of MOC, mucinous colorectal cancer (MCRC), mucinous appendiceal cancer (MAC), mucinous breast cancer (MBC) and gastric type mucinous cancer (GMC). Frequencies of somatic gene variants including mutations, copy number alterations and structural variants were compared using Chi-squared or Fischer’s exact tests, using the Benjamini-Hochberg method to control for multiple hypothesis testing with q-values reported. Results: A total of 883 tumors were included for analysis: 358 MCRC, 268 MAC, 157 MOC, 59 MBC and 41 GMC samples. Compared to MAC, MOC samples had higher variant frequencies of CDKN2A (33.3% vs 0.4%, q<0.001), CDKN2B (24.0% vs 0.0%, q<0.001), TP53 (64.3% vs 23.5%, q<0.001), ERBB2 (14.3% vs 1.1%, q<0.001) and CDK12 (13.2% vs 0.0%, q<0.001), whereas GNAS variants were more common in MAC (45.5% vs 5.7%, q<0.001). Compared to MCRC, MOC samples had higher variant frequencies of CDKN2A (33.3% vs 2.3%, q<0.001), CDKN2B (24.0% vs 3.7%, q<0.001), TP53 (64.3% vs 42.9%, q<0.001), KRAS (69.4% vs 51.1%, q<0.001) and ERBB2 (14.3% vs 5.3%, q<0.001), whereas MCRC had higher variant frequencies of 57 genes, with the largest differentials among APC (48.8% vs 2.6%, q<0.001), SMAD4 (25.2% vs 5.8%, q<0.001) and TCF7L2 (19.0% vs 0.0%, q<0.001). Samples of MOC had significantly higher rates of KRAS variants compared to GMC (69.4% vs 31.7%, q<0.001) and lower rates of STK11 variants (1.9% vs 22.0%, q<0.001). Compared to MBC, MOC samples had higher variant rates of CDKN2A (33.3% vs 3.4%, q<0.001), TP53 (64.3% vs 10.2%, q<0.001) and KRAS (69.4% vs 0.0%, q<0.001), whereas MBC samples had higher variant frequencies of 11 genes, with the largest differentials among GATA3 (32.1% vs 0.8%, q<0.001), FGF3 (30.4% vs 2.4%, q<0.05) and CCND1 (28.1% vs 1.6%, q<0.001). Conclusions: NGS demonstrates that MOCs carry a distinct genetic signature compared to mucinous tumors of non-gynecologic origin, most commonly with significantly higher variant frequencies of CDKN2A, CDKN2B and lower variant frequencies of GNAS, APC, STK11 and GATA3. This provides rationale for prospective studies evaluating genetic signatures as an adjunct to histopathology in the diagnosis of primary MOC.
10594 Background: Germline pathogenic gene variants (PGV) in homologous recombination deficiency (HRD) genes are traditionally associated with breast, ovarian, pancreatic, prostate and melanoma skin cancer. Recent evidence suggests other cancers may also be associated with these genes. We analyzed the prevalence of somatic HRD mutations in common, traditionally non-hereditary breast and ovarian cancer (HBOC) associated incident cancers in the US. Methods: Data were collected from the American Association for Cancer Research’s (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) database version 13.0 via cBioPortal (http://genie.cbioportal.org). This is a publicly available, multi-institutional database of next-generation sequencing (NGS) genomic profiles of tumor samples. The database was queried for all cancers with at least 20,000 incident cases in 2022, as reported by the American Cancer Society, excluding well established HBOC associated cancers – breast, ovarian, prostate, pancreatic, melanoma. Frequencies of somatic PGVs were reported for nine HRD genes currently included in National Comprehensive Cancer Network (NCCN) management guidelines for HBOC: ATM , BARD1, BRCA1, BRCA2, BRIP1, CHEK2, PALB2, RAD51C and RAD51D. Results: A total of 78,285 tumor samples across 12 cancer types were included. At least 1 somatic HRD was found in 6.8% of all included tumors. At least 1 HRD PGV was most common in: Uterine Cancer (694/5,760, 12.1%), Non-Melanoma Skin Cancer (127/1,209, 10.5%), Bladder Cancer (462/4,605, 10.0%), Colorectal Cancer (1306/14,625, 8.9%) Non-Hodgkin’s Lymphoma (5/58, 8.6%), Esophagogastric Cancer (356/4,649, 7.7%), Hepatobiliary Cancer (219/3,325, 6.6%), Lung Cancer (1,480/23,621, 6.3%), Kidney Cancer (113/2,564, 4.4%), Brain Cancer (420/10,206, 4.1%), Thyroid Cancer (89/2,246, 4.0%) and Leukemia (80/5,417, 1.5%). The most common PGVs across all cancer types were BRCA1/2 and ATM (Table). Conclusions: A pan-cancer analysis using NGS data demonstrates a substantial rate of somatic HRD PGVs in common, traditionally non-HBOC associated cancers in the US. These data raise the possibility that germline pathogenic variants in HRD genes could be associated with several more cancers than currently known, underscoring the need for studies evaluating risks of the aforementioned cancers in germline PGV carriers. Additionally, these findings present opportunities for trials evaluating the efficacy of HRD-targeting therapies in these cancers. [Table: see text]
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