The study was designed as a single-center retrospective cohort analysis of treatment-naive patients who had undergone a standardized low-dose bromocriptine test as a marker for dopamine agonist response. Between 2008 and 2017, the test was performed routinely at the Norwegian center as part of the baseline workup for newly diagnosed acromegaly. Of 141 consecutive patients diagnosed during that decade, 71 underwent the test, and 69 were included in the final retrospective analyses after exclusions for logistical reasons, contraindications, acute surgery, hypotension or syncope during testing, prior dopamine agonist treatment, lactose intolerance, pituitary apoplexy, loss to follow-up, or lack of consent.

The bromocriptine test itself is elegantly simple. After an overnight fast, three baseline growth hormone samples are drawn 30 minutes apart and averaged. The patient then swallows a single 2.5 mg oral dose of bromocriptine, and growth hormone is measured again at 2, 4, and 6 hours. A positive response was defined as more than a 50 percent reduction in the nadir growth hormone concentration compared with the baseline mean. In the cohort, responders showed a median growth hormone decline of 74 percent, while non-responders declined only 37 percent. This acute hormonal snapshot served as the surrogate for longer-term dopamine agonist effectiveness, a concept rooted in clinical studies from the 1970s and 1980s that linked early bromocriptine-induced growth hormone suppression with later therapeutic benefit.

To probe the biology behind variable responsiveness, the researchers combined several complementary approaches. Baseline serum hormones, including growth hormone, prolactin, and insulin-like growth factor 1 (IGF1), were measured with standard immunoassays and calibrators. Magnetic resonance images were evaluated retrospectively for tumor size, volume, and invasiveness using the Knosp criteria for cavernous sinus invasion. Immunohistochemical staining of tumor tissue assessed growth hormone, prolactin, thyroid-stimulating hormone, cytokeratin 8, estrogen receptor alpha, and somatostatin receptor subtypes 1, 2, and 5, with staining intensity scored using the immunoreactive score system. Slides were evaluated by an investigator and a senior pathologist, both blinded to clinical data.

A key technical challenge emerged with the dopamine receptor D2 protein itself. Immunohistochemistry using two different commercial antibodies failed repeatedly: on postmortem central nervous system tissue, both showed distinct intracellular granular labeling, but background staining was high and could not be reduced, and on surgical pituitary specimens the staining was diffuse and nonspecific. The team therefore turned to gene expression analysis. Tumor tissue collected during surgery was snap-frozen and stored at minus 80 degrees Celsius, RNA was extracted with a column-based kit after TRIzol homogenization, and dopamine receptor D2 mRNA was quantified by real-time quantitative PCR normalized to two validated reference genes, GAPDH and PSMC4. Gene expression data were available in 54 patients.

The central result was striking. Dopamine agonist test response correlated with higher tumor dopamine receptor D2 gene expression, with a Spearman correlation coefficient of 0.53 and a p-value below 0.001. Patients with a positive test had significantly higher receptor expression than those with a negative test. Crucially, this association remained statistically significant after statistical adjustment for gender, age, tumor volume, growth hormone and prolactin concentrations, and their staining intensities, indicating that the receptor expression carried independent information about drug responsiveness. Higher receptor expression also tracked with higher serum prolactin, stronger tumor prolactin staining, and lower IGF1 levels relative to the age-adjusted upper limit of normal.

Prolactin emerged as a clinically accessible indirect marker. Stronger tumor prolactin expression correlated with better test response, and when prolactin staining was dichotomized as positive or negative, the association with test outcome was significant, with a phi coefficient of 0.39. Notably, 57 of 66 tumors showed prolactin expression by immunohistochemistry, a far higher proportion than the 20 to 30 percent hyperprolactinemia typically reported in acromegaly, reflecting that many tumors secrete prolactin histologically without elevating serum levels beyond normal. When prolactin staining was used as the marker and test response as the outcome, sensitivity was 97 percent, meaning nearly all responders stained positive, while specificity was only 30 percent, since many non-responders also stained positive. The negative predictive value of 89 percent suggests that a prolactin-negative tumor is a strong signal that dopamine agonist therapy will fail.

The statistical architecture of the analysis clarified the causal chain. When the correlation between prolactin and test response was adjusted for dopamine receptor D2 expression, it disappeared, implying that the drug effect is mediated through the receptor itself and that prolactin expression serves as an indirect proxy for receptor abundance and responsiveness. This mechanistic interpretation aligns with known pharmacology: activation of the D2 receptor reduces hormone release and can induce apoptosis in pituitary tumor cells, with the short receptor isoform appearing to exert stronger effects. Somatostatin receptor staining showed no correlation with test response, and the hypothesized link between somatostatin receptor 1 and dopamine receptor D2 expression was not borne out in this cohort.

Estrogen receptor alpha added a second layer of tumor biology. Its expression correlated with prolactin expression, and both were associated with smaller tumor volume and lower invasiveness by Knosp grade. Patients whose tumors stained negative for prolactin were older and had higher IGF1 levels relative to normal. These findings echo the 2022 World Health Organization classification, which distinguishes pure somatotroph tumors from those with combined somatotroph and lactotroph differentiation marked by growth hormone, prolactin, and estrogen receptor alpha positivity. However, the authors caution that the clinical applicability of the estrogen receptor findings remains unclear, as previous studies on estrogen receptor alpha and tumor aggressiveness in acromegaly have yielded conflicting results.

The study has limitations that temper enthusiasm. Gene expression does not necessarily reflect protein abundance, cellular localization, or receptor function, and the analysis did not distinguish between the long and short isoforms of the D2 receptor, which may differ in mechanism. The bromocriptine test is a surrogate for acute response and cannot replace studies of long-term dopamine agonist effectiveness. The 70 patients who did not undergo testing had lower prolactin concentrations and greater growth hormone excess, potentially introducing bias, although age, sex, and tumor size were comparable. Still, the large well-characterized cohort with standardized dynamic testing, supported by molecular and histological analyses, represents a methodological strength over registry-based studies. The authors conclude that readily available prolactin staining of tumor tissue may add valuable information for individualized pharmaceutical management, potentially sparing non-responders from ineffective therapy while guiding responders toward optimized treatment regimens.

Subject of Research: Acromegaly treatment markers

Article Title: Tumor expression of dopamine receptor and prolactin is associated with acute dopamine agonist response in acromegaly

Article References: Atai, S., Abusdal, M., Wessel, M. I., Casar-Borota, O., Øystese, K. A., Winther, J., Bollerslev, J., & Heck, A. (2026). Tumor expression of dopamine receptor and prolactin is associated with acute dopamine agonist response in acromegaly. Frontiers in Endocrinology, 17, Article 1930467. https://doi.org/10.3389/fendo.2026.1930467

Image Credits: AI Generated

DOI: 10.3389/fendo.2026.1930467

Keywords: acromegaly, dopamine agonist, prolactin, pituitary tumor, personalized medicine, Tumor, expression, dopamine, receptor, associated, acute, agonist

Rare diseases are defined in European legislation as life-threatening, chronic, or debilitating conditions affecting fewer than 1 in 2,000 people. Many are genetically determined and manifest in early childhood, but a growing subset of patients is now reaching older age, a shift driven by improved medical care and the development of new therapeutic options. Conditions such as chronic myeloid leukemia and cystic fibrosis have seen average life expectancy increase by more than 10 years in recent decades. This breakthrough, however, has created an unexpected challenge: a widening gap in the continuum of care for geriatric patients, whose aging bodies must cope with both the rare disease itself and the cumulative burden of multiple medications prescribed over a lifetime.

Drug-related problems are events or circumstances related to the effectiveness or safety of therapy that may negatively impact therapeutic outcomes. According to the Pharmaceutical Care Network Europe classification, version 9.1, DRPs encompass a broad range of issues, including adverse drug reactions, suboptimal therapeutic response, overdose, inappropriate prescribing, dosing problems, and medication-related safety concerns. Older adults with rare diseases are particularly vulnerable because of delayed diagnosis, limited evidence from clinical trials, multimorbidity, polypharmacy, and the need for lifelong therapy. Age-related changes such as reduced physiological reserve and altered homeostasis, combined with complications from the rare disease itself, require timely and adequate responses, as any delay in adjusting therapy can lead to rapid clinical deterioration.

The research team, led by investigators at the University Hospital for Active Treatment in Endocrinology (USHATE) Acad. Ivan Penchev in Sofia, applied a three-step methodology. First, they conducted a systematic review following the PRISMA statement, searching PubMed and Google Scholar from February 2015 to February 2025 for studies on DRPs in geriatric patients with rare diseases. Second, they performed a retrospective analysis of patients with acromegaly hospitalized at the national Expert Center for Rare Endocrine Diseases in 2021, applying the STOPP/START criteria to identify potentially inappropriate prescribing. Third, they explored the odds of experiencing a DRP according to the presence of polypharmacy and multimorbidity, using crude odds ratios with 95% confidence intervals.

The systematic review identified 188 publications in the primary search, but after applying inclusion and exclusion criteria, only six studies made the final analysis. Two were conducted in Italy, two in the United States, and one each in Greece and China. Four of the publications were case reports or case series. The majority of diagnoses belonged to oncological diseases, with additional studies covering infectious, immune, nervous, and renal system disorders. The medicines involved included orphan drugs such as bortezomib, lenalidomide, dabrafenib, trametinib, rituximab, and colchicine. Critically, none of the studies reported the use of a standardized method for DRP identification or classification, and due to heterogeneity in reporting, the total number of geriatric patients and their distribution by sex remain unknown.

The most common DRPs were associated with therapeutic failure and adverse drug reactions, which were inherently serious because they led to hospitalization or death. Safety-related problems often resulted from improper dosing. In patients with plasma cell dyscrasias, dose reduction or treatment modification was described as a key intervention to minimize the risk of neutropenia, anemia, infections, and thrombocytopenia. In Erdheim-Chester disease, drug-induced congestive heart failure required discontinuation of the MEK inhibitor trametinib and a dose reduction of the BRAF inhibitor dabrafenib, resulting in partial remission. In Philadelphia chromosome-positive chronic myeloid leukemia, older age and a history of diabetes were identified as factors associated with cardiovascular events in patients receiving tyrosine kinase inhibitors, with coronary artery disease, acute myocardial infarction, and congestive heart failure among the most common serious adverse events.

Effectiveness-related DRPs were often linked to the complexity of the patients’ clinical conditions. In a patient with chronic inflammatory demyelinating polyneuropathy, problems included non-adherence to therapy, late diagnosis of pulmonary nocardiosis secondary to immunosuppressive therapy, and non-compliance with preventive treatment. The patient subsequently died despite prescribed antibiotic therapy. In a case of Goodpasture syndrome, no restoration of renal function was achieved despite therapy with apheresis, immunomodulators, rituximab, and corticosteroids. In a 65-year-old patient with familial Mediterranean fever, the patient proved to be a colchicine non-responder, and subsequent administration of anakinra, due to issues with canakinumab availability, further worsened the condition, ultimately resulting in peritoneal mesothelioma due to lack of effective therapy.

The retrospective cohort study focused on acromegaly, a rare chronic endocrine disease caused by excessive growth hormone secretion from a pituitary tumor. Of 180 hospitalized patients with acromegaly, 42 (23.3%) met the geriatric age criterion of 65 years or older. The majority were women (71%), with an average age at diagnosis of 52 years. Somatostatin analog monotherapy was the most frequently prescribed therapy. Polypharmacy, defined as the use of five or more medications, affected 83% of the study population, while multimorbidity, defined as the presence of two or more diseases, affected 95%. Using the STOPP/START criteria, the team identified 14 DRPs in 14 patients (33%), with 10 potentially inappropriate medications and 4 cases of prescribing omissions. An additional 2 DRPs were identified through comparison with the Summary of Product Characteristics.

The potentially inappropriate medications mainly affected the endocrine, cardiovascular, and central nervous systems. These included the use of extended-acting sulfonylureas in five patients, long-term benzodiazepine use in two patients, concomitant use of drugs with anticholinergic effects, and duplicate nootropic therapy. Prescribing omissions included the lack of proton pump inhibitors in patients with severe gastropathy and deficiencies in beta-blocker prescription for coronary heart disease. The additional SmPC-based DRPs involved torasemide prescribed to a patient with gout, a stated contraindication, and the concomitant use of empagliflozin with diuretics and ACE inhibitors, which increases the risk of hypovolemia. These cases fall outside the scope of standard STOPP/START criteria but highlight the clinical relevance of individualized structured medication review.

Interestingly, the exploratory odds ratio analyses did not demonstrate statistically significant associations between polypharmacy (OR = 1.3043, p = 0.7701) or multimorbidity (OR = 3.9804, p = 0.3720) and the occurrence of DRPs. The researchers attribute this to the limited sample size, which reduced statistical power, as reflected by the extremely wide confidence intervals. The high prevalence of polypharmacy in both groups, at 83% overall, might also explain the lack of a differentiating effect. The team emphasizes that these analyses should be considered exploratory and hypothesis-generating rather than definitive. Comparison with international data suggests the prevalence of potentially inappropriate prescribing observed in the present study was lower than that reported for other chronic diseases, where PIM prevalence according to STOPP criteria has ranged between 67.8% and 87.7%. The relatively lower prevalence may reflect the regular follow-up these acromegaly patients receive at a tertiary center with proven expertise in rare endocrine disease management.

The study’s conclusions carry significant implications for clinical practice. The researchers demonstrated the potential value of tools such as the STOPP/START criteria in evaluating therapy in geriatric patients with rare diseases, showing that some DRPs can be identified and prevented through comprehensive pharmacotherapeutic analysis. They call for more in-depth research on risk factors and long-term follow-up by clinical pharmacists to optimize pharmacotherapy. Larger, prospective studies focused on geriatric patients with rare diseases are needed to allow for more detailed analysis of the role of polypharmacy, multimorbidity, and other potential risk factors. The integration of structured pharmacotherapeutic assessment tools into routine clinical practice, alongside the development of disease-specific recommendations, may contribute to reducing both the incidence and severity of DRPs over the long term, ultimately improving medication safety for a population that has long been overlooked in pharmacotherapy research.

Subject of Research: Pharmacology

Article Title: Detection of DRPs in geriatric patients with rare diseases: a systematic review and retrospective analysis

Article References: Parvanova, A., Milushewa, P., Tachkov, K., Vandeva, S., & Elenkova, A. (2026). Detection of DRPs in geriatric patients with rare diseases: a systematic review and retrospective analysis. Pharmacia, 73, Article e201120. https://doi.org/10.3897/pharmacia.73.e201120

Image Credits: AI Generated

DOI: 10.3897/pharmacia.73.e201120

Keywords: drug-related problems, rare diseases, geriatric patients, acromegaly, STOPP/START criteria, polypharmacy, medication safety, pharmacotherapy, clinical pharmacy, adverse drug reactions, Detection, DRPs

The study, published in the Journal of Translational Medicine, applied single-cell RNA sequencing to 55,648 individual cells drawn from 12 somatotroph pituitary neuroendocrine tumors, the benign but hormonally aggressive growths responsible for acromegaly. Rather than treating each tumor as a uniform mass of identical hormone-producing cells, the team dissected them cell by cell, cataloguing the transcriptional states that coexist within a single patient’s tumor. What emerged was a picture of structured heterogeneity: the tumor cells occupied a continuum of states the researchers labeled classic, intermediate, and neuronal-associated, all while retaining the molecular identity of their pituitary lineage. The tumors, in other words, are not blobs of sameness but layered ecosystems of related cell states arranged along a transcriptional gradient.

That finding alone would have been a useful contribution to the growing atlas of pituitary tumor biology. But the Yonsei team, led by neurosurgeons and endocrinologists from the Severance Hospital Pituitary Tumor Center, pushed the analysis one level higher. Using non-negative matrix factorization, a computational technique that decomposes complex expression matrices into additive components, they aggregated the single-cell data into patient-level profiles and asked whether the twelve tumors would sort themselves into meaningful groups. They did — and the dividing line was unexpected. The tumors separated cleanly into two clusters defined not by their cell-state composition, tumor size, or canonical oncogenic mutations, but by how strongly they expressed the gene encoding prolactin, a hormone classically associated with a different pituitary tumor type altogether.

The statistical robustness of this split is notable. Across 100 independent runs of the clustering algorithm, the two groups co-clustered with a mean within-group consensus of 0.925 and a between-group consensus of just 0.058, with an overall consensus silhouette width of 0.915 — figures that indicate the division is not an artifact of algorithmic noise. The team also ruled out obvious confounders: the correlation between prolactin expression and the proportion of classic tumor states was weak, and tumor size did not differ systematically between groups. One tumor showed an intermediate assignment, a reminder that biology rarely respects clean boundaries, but the core separation held firm.

Crucially, the prolactin signal was not confined to sequencing data. The researchers validated it at the protein level using immunohistochemistry on tumor sections, showing that tumors rich in PRL transcript were also rich in prolactin immunoreactivity. Even more striking, tumor prolactin expression correlated with patients’ preoperative serum prolactin levels — a routine blood test already measured in nearly every acromegaly workup. That correlation transforms an esoteric molecular observation into something clinically actionable: a biomarker that could, in principle, be read off a standard preoperative lab panel without any need for fresh tumor tissue or specialized sequencing.

To test whether the prolactin signature actually mattered for patients, the team turned to an independent clinical cohort of 188 individuals with acromegaly. Using logistic regression and stratified analyses, they asked whether prolactin-high tumor status predicted postoperative biochemical remission — the formal endpoint, determined by growth hormone and insulin-like growth factor 1 levels under oral glucose tolerance testing, that defines surgical success. It did. Patients whose tumors fell into the prolactin-high group were significantly more likely to fail to achieve remission after surgery. The association held even as the researchers accounted for other clinical variables, positioning prolactin as a candidate adjunctive risk marker alongside the anatomical and surgical predictors — tumor size, invasiveness, and extent of resection — that surgeons already weigh.

Molecularly, the prolactin-high tumors turned out to be an enigma. Gene set enrichment analysis showed that they lacked enrichment of the canonical oncogenic pathways one might expect to find in a more aggressive tumor. Instead, the differences between prolactin-high and prolactin-low tumors played out at the level of individual genes, with a notable cluster of receptor-associated candidates — including EPHA7, a receptor tyrosine kinase gene — distinguishing the two groups. The authors suggest that these receptor-level differences may shape how tumor cells respond to their hormonal and microenvironmental milieu, though the functional biology remains to be worked out. The finding is intriguing precisely because it does not fit the standard playbook: the high-risk tumors are not more oncogenic in any obvious way, just transcriptionally different in ways that matter for hormone control.

The team took several steps to guard against wishful thinking. In an external cohort of 60 somatotroph tumors from a public dataset, a discovery-derived prolactin-associated signature score — deliberately constructed with prolactin itself and pituitary lineage genes excluded to avoid circularity — tracked strongly with tumor prolactin abundance, with a Spearman correlation of 0.64. As a negative control, the same signature applied to 45 nonfunctioning pituitary tumors from the same dataset showed no such association, confirming that the signal is specific to somatotroph biology rather than a generic pituitary artifact. A sensitivity analysis excluding the one ambiguously assigned tumor left the genome-wide fold-change estimates essentially unchanged, with a concordance of 0.98.

The translational stakes are real. Acromegaly is a rare disease, but its consequences are expensive and disabling, and the current decision tree after surgery is largely reactive: patients are monitored, and second-line treatments — repeat surgery, radiation, or medical therapy with somatostatin analogs, dopamine agonists, or the growth hormone receptor antagonist pegvisomant — are deployed only after remission fails to materialize. A preoperative biomarker that flags high-risk patients could shift that calculus, prompting earlier counseling, closer biochemical surveillance, or more aggressive multimodal treatment planning from the outset. The Yonsei group is already moving in this direction: according to the paper’s competing interests statement, the university is preparing a patent application covering the use of prolactin-associated features and selected receptor-associated markers, including EPHA7, for molecular and clinical characterization of these tumors.

Caveats remain, and the authors are careful to name them. The single-cell discovery cohort comprised only twelve tumors, and while the clinical validation cohort of 188 patients is substantial, the association between prolactin-high status and remission failure was established retrospectively. The researchers themselves state that preoperative prolactin may serve as a potential adjunctive biomarker for risk stratification but that prospective external validation is required before it enters routine practice. Whether the prolactin-high state reflects a distinct developmental origin of the tumor cells, an epigenetic program, or a response to microenvironmental cues is unknown, and the functional role of EPHA7 and the other receptor-associated genes is an open question. Still, the study exemplifies a productive pattern in modern tumor biology: single-cell atlases that do not merely describe heterogeneity but convert it into clinically legible categories. For a disease in which the difference between remission and chronic illness can hinge on molecular features invisible to the surgeon’s eye, a routine blood test that whispers a warning before the first incision is a prospect worth taking seriously.

Subject of Research: Single-cell transcriptomic stratification of somatotroph pituitary tumors by prolactin expression and postoperative remission risk

Article Title: Single-cell transcriptomics reveals prolactin-associated molecular stratification and remission risk in somatotroph PitNETs

Article References: Oh, H.-C., Shim, J.-K., Oh, H., Lee, W. K., Kim, S. H., Kang, S.-G., Lee, E. J., Kim, S. H., Ku, C. R., & Kim, E. H. (2026). Single-cell transcriptomics reveals prolactin-associated molecular stratification and remission risk in somatotroph PitNETs. Journal of Translational Medicine. https://doi.org/10.1186/s12967-026-09065-2

Image Credits: AI Generated

DOI: 10.1186/s12967-026-09065-2

Keywords: acromegaly, pituitary neuroendocrine tumor, single-cell RNA sequencing, prolactin, somatotroph tumor, transcriptomics, tumor heterogeneity, EPHA7, biomarker, remission, growth hormone, non-negative matrix factorization