The prevalence of obesity, defined as the body mass index (BMI) ≥ 30 kg/m², has reached epidemic levels. Obesity is associated with an increased risk of various cancers, including gastrointestinal ones. Recent evidence has suggested that obesity disproportionately impacts males and females with cancer, resulting in varied transcriptional and metabolic dysregulation. This study aimed to elucidate the differences in the metabolic milieu of adenocarcinomas of the gastrointestinal (GI) tract both related and unrelated to sex in obesity. To demonstrate these obesity and sex-related effects, we utilized three primary data sources: serum metabolomics from obese and non-obese patients assessed via the Biocrates MxP Quant 500 mass spectrometry-based kit, the ORIEN tumor RNA-sequencing data for all adenocarcinoma cases to assess the impacts of obesity, and publicly available TCGA transcriptional analysis to assess GI cancers and sex-related differences in GI cancers specifically. We applied and integrated our unique transcriptional metabolic pipeline in combination with our metabolomics data to reveal how obesity and sex can dictate differential metabolism in patients. Differentially expressed genes (DEG) analysis of ORIEN obese adenocarcinoma as compared to normal-weight adenocarcinoma patients resulted in large-scale transcriptional reprogramming (4029 DEGs, adj. p < 0.05 and |logFC| > 0.58). Gene Set Enrichment and metabolic pipeline analysis showed genes enriched for pathways relating to immunity (inflammation, and CD40 signaling, among others) and metabolism. Specifically, we found alterations to steroid metabolism and tryptophan/kynurenine metabolism in obese patients, both of which are highly associated with disease severity and immune cell dysfunction. These findings were further confirmed using the TCGA colorectal adenocarcinoma (CRC) and esophageal adenocarcinoma (ESCA) data, which showed similar patterns of increased tryptophan catabolism for kynurenine production in obese patients. These patients further showed disparate alterations between males and females when comparing obese to non-obese patient populations. Alterations to immune and metabolic pathways were validated in six patients (two obese and four normal weight) via CD8+/CD4+ peripheral blood mononuclear cell RNA-sequencing and paired serum metabolomics, which showed differential kynurenine and lipid metabolism, which corresponded with altered T-cell transcriptome in obese populations. Overall, obesity is associated with differential transcriptional and metabolic programs in various disease sites. Further, these alterations, such as kynurenine and tryptophan metabolism, which impact both metabolism and immune phenotype, vary with sex and obesity together. This study warrants further in-depth investigation into obesity and sex-related alterations in cancers that may better define biomarkers of response to immunotherapy.

Background: We aimed to determine the prognostic value of an immunoscore reflecting CD3+ and CD8+ T cell density estimated from real-world transcriptomic data of a patient cohort with advanced malignancies treated with immune checkpoint inhibitors (ICIs) in an effort to validate a reference for future machine learning-based biomarker development. Methods: Transcriptomic data was collected under the Total Cancer Care Protocol (NCT03977402) Avatar^® project. The real-world immunoscore for each patient was calculated based on the estimated densities of tumor CD3+ and CD8+ T cells utilizing CIBERSORTx and the LM22 gene signature matrix. Then, the immunoscore association with overall survival (OS) was estimated using Cox regression and analyzed using Kaplan–Meier curves. The OS predictions were assessed using Harrell’s concordance index (C-index). The Youden index was used to identify the optimal cut-off point. Statistical significance was assessed using the log-rank test. Results: Our study encompassed 522 patients with four cancer types. The median duration to death was 10.5 months for the 275 participants who encountered an event. For the entire cohort, the results demonstrated that transcriptomics-based immunoscore could significantly predict patients at risk of death (p-value < 0.001). Notably, patients with an intermediate–high immunoscore achieved better OS than those with a low immunoscore. In subgroup analysis, the prediction of OS was significant for melanoma and head and neck cancer patients but did not reach significance in the non-small cell lung cancer or renal cell carcinoma cohorts. Conclusions: Calculating CD3+ and CD8+ T cell immunoscore using real-world transcriptomic data represents a promising signature for estimating OS with ICIs and can be used as a reference for future machine learning-based biomarker development.

Androgen-indifferent prostate cancer (AIPC) is increasingly common and particularly lethal. Data describing these tumors are sparse, and AIPC remains a poorly understood malignancy. Utilizing the Oncology Research Information Exchange Network (ORIEN) database, we enriched for tumors with features of AIPC using previously described characteristics. Our AIPC cohort included three subgroups: aggressive variant prostate cancer (AVPC), neuroendocrine PC (NEPC), and double-negative PC (DNPC). Of 1496 total PC patients available for analysis, we identified 323 (22%) as MCRPC. Of those, 39 (12%) met AIPC criteria (17 AVPC, 13 NEPC, 9 DNPC) and 284 (88%) were non-AIPC. Forty-three percent of AIPC patients had de novo metastatic disease vs. 15% for non-AIPC (p = 0.003). Homologous recombination deficiency (HRD) and tumor mutational burden (TMB) did not differ between cohorts, but microsatellite instability scores (MSI) were significantly higher in AIPC (p = 0.019). Using Gene Set Enrichment Analysis (GSEA), we found that genes defining response to androgens and genes involved in oxidative phosphorylation were the most downregulated, whereas genes involved in epithelial–mesenchymal transition (EMT) and immune signaling were significantly upregulated in AIPC vs. non-AIPC. Our study demonstrates the potential for predefined criteria that aim to enrich for AIPC and suggests opportunities for therapeutic investigation.

Background: Solid tumors vary by the immunogenic potential of the tumor microenvironment (TME) and the likelihood of response to immunotherapy. The emerging literature has identified key immune cell populations that significantly impact immune activation or suppression within the TME. This study investigated candidate T-cell populations and their differential infiltration within different tumor types as estimated from mRNA co-expression levels of the corresponding cellular markers. Methods: We analyzed the mRNA co-expression levels of cellular biomarkers that define stem-like tumor-infiltrating lymphocytes (TILs), tissue-resident memory T-cells (TRM), early dysfunctional T-cells, late dysfunctional T-cells, activated-potentially anti-tumor (APA) T-cells and Butyrophilin 3A (BTN3A) isoforms, utilizing clinical and transcriptomic data from 1892 patients diagnosed with melanoma, bladder, ovarian, or pancreatic carcinomas. Real-world data were collected under the Total Cancer Care Protocol and the Avatar^® project (NCT03977402) across 18 cancer centers. Furthermore, we compared the survival outcomes following immune checkpoint inhibitors (ICIs) based on immune cell gene expression. Results: In melanoma and bladder cancer, the estimated infiltration of APA T-cells differed significantly (p = 4.67 × 10⁻¹² and p = 5.80 × 10⁻¹², respectively) compared to ovarian and pancreatic cancers. Ovarian cancer had lower TRM T-cell infiltration than melanoma, bladder, and pancreatic (p = 2.23 × 10⁻⁸, 3.86 × 10⁻²⁸, and 7.85 × 10⁻⁹, respectively). Similar trends were noted with stem-like, early, and late dysfunctional T-cells. Melanoma and ovarian expressed BTN3A isoforms more than other malignancies. Higher densities of stem-like TILs; TRM, early and late dysfunctional T-cells; APA T-cells; and BTN3A isoforms were associated with increased survival in melanoma (p = 0.0075, 0.00059, 0.013, 0.005, 0.0016, and 0.041, respectively). The TRM gene signature was a moderate predictor of survival in the melanoma cohort (AUROC = 0.65), with similar findings in testing independent public datasets of ICI-treated patients with melanoma (AUROC 0.61–0.64). Conclusions: Key cellular elements related to immune activation are more heavily infiltrated within ICI-responsive versus non-responsive malignancies, supporting a central role in anti-tumor immunity. In melanoma patients treated with ICIs, higher densities of stem-like TILs, TRM T-cells, early dysfunctional T-cells, late dysfunctional T-cells, APA T-cells, and BTN3A isoforms were associated with improved survival.

Thyroid diseases are common and highly heritable. Under the Global Biobank Meta-analysis Initiative, we performed a meta-analysis of genome-wide association studies from 19 biobanks for five thyroid diseases: thyroid cancer, benign nodular goiter, Graves’ disease, lymphocytic thyroiditis, and primary hypothyroidism. We analyzed genetic association data from ∼2.9 million genomes and identified 235 known and 501 novel independent variants significantly linked to thyroid diseases. We discovered genetic correlations between thyroid cancer, benign nodular goiter, and autoimmune thyroid diseases ( r ² =0.21-0.97). Telomere maintenance genes contribute to benign and malignant thyroid nodular disease risk, whereas cell cycle, DNA repair, and DNA damage response genes are predominantly associated with thyroid cancer. We proposed a paradigm explaining genetic predisposition to benign and malignant thyroid nodules. We evaluated thyroid cancer polygenic risk scores (PRS) for clinical applications in thyroid cancer diagnosis. We found PRS associations with thyroid cancer risk features: multifocality, lymph node metastases, and extranodal extension.

Background: Prostate cancer is a heterogeneous disease with variable clinical outcomes. If localized, the patient may be cured. However, prostate cancer is lethal if recurrence/progression to metastatic castrate resistant disease occurs. Thus, there is an unmet need to further understand the molecular underpinnings of this progression. Epidemiologic studies show that increased risk of developing and dying from prostate cancer has been associated with elevated serum IGF-1 levels, hyperinsulinemia and metabolic syndrome. Alterations in insulin pathway genes, such as PTEN, FOXO, and PIK3CA, are mutated in up to 32%, 15%, and 11% of localized prostate tumors, respectively. We aimed to further characterize expression of insulin pathway genes in localized prostate cancers in an effort to (1) provide insights into potential mechanisms of progression to metastatic disease and (2) try to further enrich for those prostate tumors that portend worse survival outcomes. Methods: Using the multi-institutional Oncology Research Information Exchange Network (ORIEN) database, gene expression data was analyzed from localized prostate cancer tumors. The raw counts were first normalized, and 176 genes related to the insulin receptor and its downstream pathways were then subset and used for clustering using the non-negative matrix factorization (NMF). The NMF cluster analysis was performed in an attempt to separate gene expression into two groups. Gene Set Enrichment Analysis (GSEA) was then performed between the two groups that had been separated by cluster analysis to determine homology between other GSEA sets. Kaplan–Meier curves were used to assess median overall survival. Cox analysis was performed to generate the adjusted KM curve. Mediation analysis was conducted to determine the relationship between cluster status, TN stage, and survival. Results: Cluster analysis revealed two distinct groups of insulin gene expression, cluster 1 (n = 96) and cluster 2 (n = 337). Compared with cluster 2, cluster 1 consisted of decreased expression of PTEN (p < 0.001) and PIK3R1 (p < 0.001), along with increases in the expression of AKT1 (p < 0.001), IRS1/2 (p < 0.001), FASN (p < 0.001), IGFBP2 (p < 0.001), and MTOR (p < 0.001). GSEA analysis revealed changes in lipid metabolism and WNT secretion pathways in cluster 1. Cluster 2 GSEA showed pathway changes related to DNA damage repair and testosterone. Patient characteristics between clusters differed significantly in the T and N stages of tumor but not in other ways. In unadjusted analysis, median overall survival was estimated at 117 months and 232 months for cluster 1 and cluster 2, respectively (p < 0.05). The proportion of patients who went on to develop metastases (p < 0.05) or need chemotherapy (p < 0.05) was increased in cluster 1 compared to cluster 2. Repeat survival analysis adjusted for confounders (T stage, N stage, age at diagnosis, pathologic grade) showed no difference in survival between clusters. Mediation analysis showed that the contribution of cluster status to survival was independent of T or N stage. Conclusions: A subset of localized prostate cancer patients demonstrated linked insulin pathway changes that are consistent with prior studies describing a pattern of insulin dysregulation. Though the group characterized by insulin dysregulation initially showed worse survival outcomes, this difference disappeared when controlling for confounders. Though baseline differences in tumor stage seemed to most readily explain the difference in survival between clusters, mediation analysis showed that the effect of cluster status on survival was independent of tumor stage. This suggests that other confounders, such as pathologic grade or baseline age, may explain the survival difference.