Impact of comorbidities on immediate post-operative complications in oral cavity free flap patients.

PURPOSE: To examine the relationship between comorbidities and the development of immediate post-operative complications in patients undergoing oral cavity composite resection (OCCR) with free flap (FF) reconstruction. MATERIALS AND METHODS: Retrospective analysis was completed on all consecutive OCCRs with FF reconstruction performed at a single quaternary care facility between 1999 and 2020. Comorbidities, immediate post-operative complications, patient demographics, and tumor characteristics were collected. Odds ratios (OR) with 95 % confidence intervals were calculated for associations between comorbidities and immediate post-operative complications. RESULTS: 320 patients who underwent OCCR with FF reconstruction were included. One hundred twenty-one (37.8 %) patients developed a post-operative complication during their initial hospital admission. The most common complications were non-pneumonia cardiopulmonary events (14.1 %), pneumonia (9.4 %), and wound infection (8.4 %). Other complications included flap compromise, bleeding, and fistula. On multivariate analysis, patients without comorbid conditions were less likely to develop a post-operative complication (OR 0.64; 0.41-0.98). Atrial fibrillation (OR 2.94; 1.17-7.39) and cerebrovascular disease (OR 2.28; 1.08-4.84) were associated with increased odds of developing any complications. Furthermore, cerebrovascular disease (OR: 2.33; 1.04-5.39) and peripheral vascular disease (OR: 2.7; 1.2-6.08) were independently associated with pneumonia. CONCLUSION: In this retrospective review of patients undergoing OCCR with FF reconstruction for oral cavity SCC, lack of identifiable comorbidities appeared to be protective for post-operative complications while atrial fibrillation and cerebrovascular disease were associated with increased odds of any complication. Pre-existing vascular disease was also associated with an increased risk of pneumonia.

Tumor collagens predict genetic features and patient outcomes.

The extracellular matrix (ECM) is a critical determinant of tumor fate that reflects the output from myriad cell types in the tumor. Collagens constitute the principal components of the tumor ECM. The changing collagen composition in tumors along with their impact on patient outcomes and possible biomarkers remains largely unknown. The RNA expression of the 43 collagen genes from solid tumors in The Cancer Genome Atlas (TCGA) was clustered to classify tumors. PanCancer analysis revealed how collagens by themselves can identify the tissue of origin. Clustering by collagens in each cancer type demonstrated strong associations with survival, specific immunoenvironments, somatic gene mutations, copy number variations, and aneuploidy. We developed a machine learning classifier that predicts aneuploidy, and chromosome arm copy number alteration (CNA) status based on collagen expression alone with high accuracy in many cancer types with somatic mutations, suggesting a strong relationship between the collagen ECM context and specific molecular alterations. These findings have broad implications in defining the relationship between cancer-related genetic defects and the tumor microenvironment to improve prognosis and therapeutic targeting for patient care, opening new avenues of investigation to define tumor ecosystems.

Somatic mutations in collagens are associated with a distinct tumor environment and overall survival in gastric cancer.

BACKGROUND: Gastric cancer is a heterogeneous disease with poorly understood genetic and microenvironmental factors. Mutations in collagen genes are associated with genetic diseases that compromise tissue integrity, but their role in tumor progression has not been extensively reported. Aberrant collagen expression has been long associated with malignant tumor growth, invasion, chemoresistance, and patient outcomes. We hypothesized that somatic mutations in collagens could functionally alter the tumor extracellular matrix. METHODS: We used publicly available datasets including The Tumor Cancer Genome Atlas (TCGA) to interrogate somatic mutations in collagens in stomach adenocarcinomas. To demonstrate that collagens were significantly mutated above background mutation rates, we used a moderated Kolmogorov-Smirnov test along with combination analysis with a bootstrap approach to define the background accounting for mutation rates. Association between mutations and clinicopathological features was evaluated by Fisher or chi-squared tests. Association with overall survival was assessed by Kaplan-Meier and the Cox-Proportional Hazards Model. Gene Set Enrichment Analysis was used to interrogate pathways. Immunohistochemistry and in situ hybridization tested expression of COL7A1 in stomach tumors. RESULTS: In stomach adenocarcinomas, we identified individual collagen genes and sets of collagen genes harboring somatic mutations at a high frequency compared to background in both microsatellite stable, and microsatellite instable tumors in TCGA. Many of the missense mutations resemble the same types of loss of function mutations in collagenopathies that disrupt tissue formation and destabilize cells providing guidance to interpret the somatic mutations. We identified combinations of somatic mutations in collagens associated with overall survival, with a distinctive tumor microenvironment marked by lower matrisome expression and immune cell signatures. Truncation mutations were strongly associated with improved outcomes suggesting that loss of expression of secreted collagens impact tumor progression and treatment response. Germline collagenopathy variants guided interpretation of impactful somatic mutations on tumors. CONCLUSIONS: These observations highlight that many collagens, expressed in non-physiologically relevant conditions in tumors, harbor impactful somatic mutations in tumors, suggesting new approaches for classification and therapy development in stomach cancer. In sum, these findings demonstrate how classification of tumors by collagen mutations identified strong links between specific genotypes and the tumor environment.