Fanconi anemia (FA) is a rare inherited, generally autosomal recessive syndrome, but it displays X-linked or dominant negative inheritance for certain genes. FA is characterized by a deficiency in DNA damage repair that results in bone marrow failure, and in an increased risk for various epithelial tumors, most commonly squamous cell carcinomas of the head and neck (HNSCC) and of the esophagus, anogenital tract and skin. Individuals with FA exhibit increased human papilloma virus (HPV) prevalence. Furthermore, a subset of anogenital squamous cell carcinomas (SCCs) in FA harbor HPV sequences and FA-deficient laboratory models reveal molecular crosstalk between HPV and FA proteins. However, a definitive role for HPV in HNSCC development in the FA patient population is unproven. Cellular metabolism plays an integral role in tissue homeostasis, and metabolic deregulation is a known hallmark of cancer progression that supports uncontrolled proliferation, tumor development and metastatic dissemination. The metabolic consequences of FA deficiency in keratinocytes and associated impact on the development of SCC in the FA population is poorly understood. Herein, we review the current literature on the metabolic consequences of FA deficiency and potential effects of resulting metabolic reprogramming on FA cancer phenotypes.

Persistent infection with HPV causes nearly 5% of all cancers worldwide, including cervical and oropharyngeal cancers. Compared to HPV-negative (HPV−) head and neck squamous cell carcinomas (HNSCCs), HPV-positive (HPV+) HNSCCs exhibit a significantly improved treatment response; however, established treatment regimens were largely developed for HPV− disease. Effectively de-escalating therapy and optimizing treatment protocols to minimize toxicity for both HPV+ and HPV− tumors has been variably successful, in part due to the heterogeneity of cellular subpopulations. Single-cell RNA sequencing (scRNAseq) has primarily been used to define immune cell populations rather than the cell type of origin, epithelial cells. To address this, we analyzed published scRNAseq data of HPV+ and HPV− HNSCCs to distinguish epithelial tumor cell populations as a function of HPV status. We identified the transcriptome signatures, ontologies, and candidate biomarkers of newly identified epithelial subpopulations with attention to those that are shared or enriched in HPV+ or HPV− HNSCCs. We hypothesize that distinct epithelial cell populations and reprogramming in HPV− versus HPV+ HNSCC represent important components of the pro-tumor environment. These are described here as a foundation for the identification of new epithelial-cell-specific biomarkers, effectors, and candidate targets for optimizing the treatment of HNSCC.

Background: Pancreatic cancer is the most lethal of all human cancers. The disease has no obvious symptoms in its early stages and in the majority of cases, the cancer goes undetected until it has advanced to the point that surgery is no longer a viable option or until it has metastasized to other organs. The absence of reliable and sensitive biomarkers for the early detection of pancreatic cancer contributes to the poor ability to detect the disease before it progresses to an untreatable stage. Objectives: Here, an orthotopic xenograft mouse model of pancreatic cancer was investigated to determine if urinary metabolic biomarkers could be identified and used to detect the early formation of pancreatic tumors. Methods: The orthotopic xenograft mouse model of pancreatic cancer was established by injecting human MiaPaCa-2 cells, derived from a male patient aged 65 years with pancreatic adenocarcinoma, into the pancreata of severe combined immunodeficient mice. Orthotopic pancreatic tumors, allowed to grow for eight weeks, were successfully established in the pancreata in 15 out of 20 mice. At the time of sacrifice, tumors were excised and histologically analyzed and the masses and volumes recorded. Urine samples were collected prior to injection, at one-week post injection, and every two weeks afterwards for eight weeks. Results: NMR-based metabolic profiling of the urine samples indicated that 31 metabolites changed significantly over the course of tumor initiation and growth. Longitudinal metabolic profiling analysis indicated an initial increase in activity of the metabolic pathways involved in energy production and/or cell synthesis by cancer cells as required to support tumor growth that was followed by a diminished difference between control and orthotopic mice associated with tumor senescence as the tumors reached 7–8 weeks post injection. Conclusions: The results indicate that NMR-based urinary metabolic profiling may be able to detect the earliest stages of pancreatic tumor initiation and growth, highlighting the potential for translation to human clinical studies.