Daily Endocrinology Research Analysis
Three notable endocrinology-related advances stand out today: (1) ACLY inhibition reprograms the tumor microenvironment to enhance anti-tumor immunity and suppress MASH-driven hepatocellular carcinoma; (2) trapping gut microbiota–derived D-lactate with a non-absorbed polymer improves glycemia and MASH in obese mice; and (3) mRNA expression–based classifiers preoperatively rule out invasion and lymph node metastasis in thyroid cancer with very high NPVs, enabling surgical de-escalation.
Summary
Three notable endocrinology-related advances stand out today: (1) ACLY inhibition reprograms the tumor microenvironment to enhance anti-tumor immunity and suppress MASH-driven hepatocellular carcinoma; (2) trapping gut microbiota–derived D-lactate with a non-absorbed polymer improves glycemia and MASH in obese mice; and (3) mRNA expression–based classifiers preoperatively rule out invasion and lymph node metastasis in thyroid cancer with very high NPVs, enabling surgical de-escalation.
Research Themes
- Immunometabolism as a therapeutic axis in liver cancer
- Microbiome-derived metabolites and metabolic disease intervention
- Molecular diagnostics to personalize thyroid cancer surgery
Selected Articles
1. ACLY inhibition promotes tumour immunity and suppresses liver cancer.
Preclinical work demonstrates that inhibiting ATP citrate lyase (ACLY) enhances anti-tumor immunity and suppresses liver cancer in the MASH-HCC context. The study positions ACLY as an immunometabolic target capable of reprogramming an immunosuppressive tumor microenvironment.
Impact: Identifies an immunometabolic node (ACLY) with therapeutic potential to convert an immunosuppressive milieu and inhibit MASH-HCC, a clinically challenging cancer. The work may inform combination strategies with immunotherapy.
Clinical Implications: Suggests ACLY inhibition as a candidate strategy to enhance responsiveness to immunotherapy and suppress tumor growth in MASH-HCC. If translated, it could expand options for metabolic liver cancer therapy.
Key Findings
- ACLY inhibition enhanced anti-tumor immunity within an immunosuppressive microenvironment characteristic of MASH-HCC.
- Preclinical ACLY targeting suppressed liver cancer growth.
- The study establishes ACLY as a therapeutically actionable immunometabolic node.
Methodological Strengths
- Rigorous mechanistic preclinical approach in relevant metabolic liver cancer context
- Clear therapeutic hypothesis linking lipid metabolism to anti-tumor immunity
Limitations
- Preclinical data; human efficacy and safety remain untested
- Details of models and breadth of validation are not provided in the abstract snippet
Future Directions: Conduct translational and early-phase clinical trials testing ACLY inhibitors in MASH-HCC, potentially in combination with checkpoint blockade; dissect immune cell subsets and metabolic rewiring mediating benefit.
Immunosuppressive tumour microenvironments are common in cancers such as metabolic dysfunction-associated steatohepatitis (MASH)-driven hepatocellular carcinoma (HCC) (MASH-HCC)
2. Gut substrate trap of D-lactate from microbiota improves blood glucose and fatty liver disease in obese mice.
Obesity elevates circulating D-lactate, a microbiota-derived metabolite that drives hepatic glycogen and triglyceride accumulation and hyperglycemia. A non-absorbed, biocompatible polymer that traps gut D-lactate reduced blood glucose, insulin resistance, and MASH histopathology in obese mice.
Impact: Reveals D-lactate as a microbiome-derived driver of dysglycemia and liver injury, and demonstrates a tractable gut-targeted trapping intervention with translational potential.
Clinical Implications: Supports development of oral, non-absorbed polymers that sequester harmful microbial metabolites to improve glycemia and MASH; motivates human proof-of-concept trials and biomarker strategies (e.g., circulating D-lactate) for patient selection.
Key Findings
- Circulating D-lactate is elevated in humans and mice with obesity.
- D-lactate increases hepatic glycogen, triglycerides, and blood glucose more than equimolar L-lactate.
- Stable isotope tracing shows D-lactate is metabolized to pyruvate, TCA intermediates, lipids, and glucose.
- A gut D-lactate–trapping polymer lowers blood glucose, insulin resistance, and hepatic inflammation/fibrosis in obese/MASH mice.
Methodological Strengths
- Multiple complementary systems: human observations, mouse models, hepatocytes, and isotope tracing
- Causal manipulation via colonization with D-lactate–producing bacteria and gut-targeted polymer intervention
Limitations
- Preclinical findings; human efficacy/safety of the polymer approach are unknown
- Long-term durability and potential microbiome shifts with chronic trapping not assessed
Future Directions: Early human trials to assess safety, tolerability, and glycemic/liver endpoints of D-lactate trapping; define pharmacodynamics, optimal polymer length/dose, and patient selection by D-lactate.
L-lactate participates in metabolism, including the Cori cycle, but less is known about D-lactate. We found that circulating D-lactate was higher in humans and mice with obesity. D-lactate increased hepatic glycogen, triglycerides, and blood glucose more than equimolar L-lactate in mice. Stable isotope analyses showed that D-lactate is metabolized in mice and in hepatocytes to pyruvate, TCA intermediates, lipids, and glucose. The gut microbiota is the main source of blood D-lactate. Colonization of mice with a bacterial strain that produced D-lactate elevated blood glucose more than an L-lactate producer. Oral delivery of a biocompatible polymer that traps gut D-lactate, forcing fecal excretion, lowered blood glucose and insulin resistance in obese mice in a polymer length- and dose-dependent manner. This D-lactate trap lowered hepatic inflammation and fibrosis in mice with metabolic dysfunction-associated fatty liver disease (MAFLD)/metabolic dysfunction-associated steatohepatitis (MASH). Therefore, microbial-derived D-lactate contributes to host glucose and lipid metabolism and can be trapped to improve metabolic disease during obesity.
3. Development and validation of mRNA expression-based classifiers to predict low-risk thyroid tumors.
Retrospective development and validation of mRNA-based classifiers showed very high NPVs (99–100%) to preoperatively rule out invasion and lymph node metastasis in thyroid cancer. About half of nodules could be safely ruled out for high-risk features, enabling de-escalation of surgery.
Impact: Offers a practical molecular tool to avoid unnecessary extensive thyroid surgery and associated complications by reliably ruling out invasive features preoperatively.
Clinical Implications: May reduce total thyroidectomy and prophylactic nodal dissection rates, surgical complications, and postoperative hypothyroidism by supporting hemithyroidectomy or surveillance when classifiers indicate low risk.
Key Findings
- Development cohort (n=697): low-risk invasion NPV 97.6%; low-risk LNM NPV 98.6%.
- Validation cohort (n=259): 51% ruled out for invasion with 99% NPV; 53% ruled out for LNM with 100% NPV.
- Approximately half of nodules can be preoperatively ruled out for high-risk features, enabling personalized surgery.
Methodological Strengths
- Independent retrospective validation with blinded histopathologic scoring
- Machine learning leveraging literature-derived signatures and differentially expressed genes
Limitations
- Retrospective design; prospective PRCT validation is lacking
- Generalizability beyond Afirma-tested cohorts requires assessment
Future Directions: Prospective, multicenter validation to assess impact on surgical decision-making, outcomes, costs, and patient-reported measures; evaluation across platforms and diverse populations.
BACKGROUND: Molecular variants and fusions in thyroid nodules can provide prognostic information at a population level. However, thyroid cancers harboring the same molecular alterations may exhibit diverse clinical behavior. Leveraging exome-enriched gene expression analysis may overcome the limitations seen in models based on a small number of point mutations or fusions. Here, we developed and validated mRNA-based classifiers with high negative predictive values to preoperatively rule out thyroid tumor invasion and lymph node metastases. MATERIALS AND METHODS: In this retrospective cohort study, histopathology reports from the Afirma Genomic Sequencing Classifier (GSC) algorithm training and consecutive thyroid cancer patients with Bethesda III-VI thyroid nodules in clinical practice (total 697 and ~50%, respectively) were scored for invasion and metastases. mRNA expression-based classifiers were developed utilizing literature-derived signatures as well as differentially expressed genes between samples with or without clinically significant invasion/metastases as the basic building blocks. Machine learning algorithms were employed to develop the final candidate classifiers. The final locked classifiers were validated on a retrospective cohort of 259 patients with Afirma testing who had thyroid surgery and had invasion and metastasis scores assigned based on histopathology while blinded to the classifier results. RESULTS: A total of 697 (88% female) patient Afirma samples and scored histology reports were used for classifier development. In development, patients had a median age of 51 years. Ten percent of samples were assigned a high risk for invasion label, and 11.3% were assigned a high risk for lymph node metastasis (LNM) label. A low-risk invasion classifier result was assigned to 41.3% of the cohort with a negative predictive value (NPV) of 97.6%, and a low-risk LNM classifier result was assigned to 49.8% of the cohort with an NPV of 98.6%. In the validation cohort, made up of 75% women with a median age of 53 years, 51% of the samples were ruled out for high risk for invasion label with a 99% [95-100] NPV, and 53% were ruled out for high risk for LNM label with 100% [97-100] NPV. DISCUSSION: Gene expression-based classifiers that confidently, preoperatively rule out thyroid tumor invasion and lymph node metastasis may help personalize the surgical approach for individuals, reducing overtreatment, surgical complications, and postoperative hypothyroidism.