Validating risk prediction models for multiple primaries and competing cancer outcomes in families with Li-Fraumeni syndrome using clinically ascertained data at a single institute.

Purpose: There exists a barrier between developing and disseminating risk prediction models in clinical settings. We hypothesize this barrier may be lifted by demonstrating the utility of these models using incomplete data that are collected in real clinical sessions, as compared to the commonly used research cohorts that are meticulously collected. Patients and methods: Genetic counselors (GCs) collect family history when patients (i.e., probands) come to MD Anderson Cancer Center for risk assessment of Li-Fraumeni syndrome, a genetic disorder characterized by deleterious germline mutations in the TP53 gene. Our clinical counseling-based (CCB) cohort consists of 3,297 individuals across 124 families (522 cases of single primary cancer and 125 cases of multiple primary cancers). We applied our software suite LFSPRO to make risk predictions and assessed performance in discrimination using area under the curve (AUC), and in calibration using observed/expected (O/E) ratio. Results: For prediction of deleterious TP53 mutations, we achieved an AUC of 0.81 (95% CI, 0.70 - 0.91) and an O/E ratio of 0.96 (95% CI, 0.70 - 1.21). Using the LFSPRO.MPC model to predict the onset of the second cancer, we obtained an AUC of 0.70 (95% CI, 0.58 - 0.82). Using the LFSPRO.CS model to predict the onset of different cancer types as the first primary, we achieved AUCs between 0.70 and 0.83 for sarcoma, breast cancer, or other cancers combined. Conclusion: We describe a study that fills in the critical gap in knowledge for the utility of risk prediction models. Using a CCB cohort, our previously validated models have demonstrated good performance and outperformed the standard clinical criteria. Our study suggests better risk counseling may be achieved by GCs using these already-developed mathematical models.

Male and female rats exhibit comparable gaping behavior but activate brain regions differently during expression of conditioned nausea.

Twenty-five to fifty percent of patients undergoing chemotherapy will develop anticipatory nausea and vomiting (ANV), in which symptoms occur in anticipation of treatment. ANV is triggered by environmental cues and shows little response to traditional antiemetic therapy, suggesting that unique neural pathways mediate this response. Understanding the underlying neural mechanisms of this disorder is critical to the development of novel therapeutic interventions. The purpose of the present study was to identify brain areas activated during ANV and characterize sex differences in both the behavior and the brain areas activated during ANV. We used a rat model of ANV by pairing a novel context with the emetic drug lithium chloride (LiCl) to produce conditioned nausea behaviors in the LiCl-paired environment. We quantitated gaping, an analog of human vomiting, after acute or repeated LiCl in a unique environment. To identify brain regions associated with gaping, we measured c-fos activation by immunochemical staining after these same treatments. We found that acute LiCl activated multiple brain regions including the supraoptic nucleus of the hypothalamus, central nucleus of the amygdala, nucleus of the solitary tract and area postrema, none of which were activated during ANV. ANV activated c-fos expression in the frontal cortex, insula and paraventricular nucleus of the hypothalamus of males but not females. These data suggest that therapies such as ondansetron which target the area postrema are not effective in ANV because it is not activated during the ANV response. Further studies aimed at characterizing the neural circuits and cell types that are activated in the conditioned nausea response will help identify novel therapeutic targets for the treatment of this condition, improving both quality of life and outcomes for patients undergoing chemotherapy.

Behavior and Fos activation reveal that male and female rats differentially assess affective valence during CTA learning and expression.

Females are more affected by psychiatric illnesses including eating disorders, depression, and post-traumatic stress disorder than males. However, the neural mechanisms mediating these sex differences are poorly understood. Animal models can be useful in exploring such neural mechanisms. Conditioned taste aversion (CTA) is a behavioral task that assesses how animals process the competition between associated reinforcing and aversive stimuli in subsequent task performance, a process critical to healthy behavior in many domains. The purpose of the present study was to identify sex differences in this behavior and associated neural responses. We hypothesized that females would value the rewarding stimulus (Boost®) relative to the aversive stimulus (LiCl) more than males in performing CTA. We evaluated behavior (Boost® intake, LiCl-induced behaviors, ultrasonic vocalizations (USVs), CTA performance) and Fos activation in relevant brain regions after the acute stimuli [acute Boost® (AB), acute LiCl (AL)] and the context-only task control (COT), Boost® only task (BOT) and Boost®-LiCl task (BLT). Acutely, females drank more Boost® than males but showed similar aversive behaviors after LiCl. Females and males performed CTA similarly. Both sexes produced 55 kHz USVs anticipating BOT and inhibited these calls in the BLT. However, more females emitted both 22 kHz and 55 kHz USVs in the BLT than males: the latter correlated with less CTA. Estrous cycle stage also influenced 55 kHz USVs. Fos responses were similar in males and females after AB or AL. Females engaged the gustatory cortex and ventral tegmental area (VTA) more than males during the BOT and males engaged the amygdala more than females in both the BOT and BLT. Network analysis of correlated Fos responses across brain regions identified two unique networks characterizing the BOT and BLT, in both of which the VTA played a central role. In situ hybridization with RNAscope identified a population of D1-receptor expressing cells in the CeA that responded to Boost® and D2 receptor-expressing cells that responded to LiCl. The present study suggests that males and females differentially process the affective valence of a stimulus to produce the same goal-directed behavior.

Precision medicine integrating whole-genome sequencing, comprehensive metabolomics, and advanced imaging.

Genome sequencing has established clinical utility for rare disease diagnosis. While increasing numbers of individuals have undergone elective genome sequencing, a comprehensive study surveying genome-wide disease-associated genes in adults with deep phenotyping has not been reported. Here we report the results of a 3-y precision medicine study with a goal to integrate whole-genome sequencing with deep phenotyping. A cohort of 1,190 adult participants (402 female [33.8%]; mean age, 54 y [range 20 to 89+]; 70.6% European) had whole-genome sequencing, and were deeply phenotyped using metabolomics, advanced imaging, and clinical laboratory tests in addition to family/medical history. Of 1,190 adults, 206 (17.3%) had at least 1 genetic variant with pathogenic (P) or likely pathogenic (LP) assessment that suggests a predisposition of genetic risk. A multidisciplinary clinical team reviewed all reportable findings for the assessment of genotype and phenotype associations, and 137 (11.5%) had genotype and phenotype associations. A high percentage of genotype and phenotype associations (>75%) was observed for dyslipidemia (n = 24), cardiomyopathy, arrhythmia, and other cardiac diseases (n = 42), and diabetes and endocrine diseases (n = 17). A lack of genotype and phenotype associations, a potential burden for patient care, was observed in 69 (5.8%) individuals with P/LP variants. Genomics and metabolomics associations identified 61 (5.1%) heterozygotes with phenotype manifestations affecting serum metabolite levels in amino acid, lipid and cofactor, and vitamin pathways. Our descriptive analysis provides results on the integration of whole-genome sequencing and deep phenotyping for clinical assessments in adults.