PubMed Health⌕ Search

Biomedical subjects

Carsten Denkert

Publications and source records attributed to Carsten Denkert.

7 recordsLinked to original sources
PubMed2026

Divergent c-MYC Expression Patterns in NET and NEC: Insights from a Multicentre Cohort of 1380 Neuroendocrine Neoplasms.

Neuroendocrine neoplasms (NEN) comprise well-differentiated neuroendocrine tumours (NET) and neuroendocrine carcinomas (NEC), whose distinction is clinically critical. Although c-MYC alterations have been implicated in NEC pathogenesis, c-MYC expression across NEC subtypes and anatomical sites, as well as in NET, remains incompletely defined. We analysed c-MYC immunohistochemically in 1380 resected NEN using the Immunoreactive Score (IRS: negative 0-1, weak 2-3, moderate 4-8, strong 9-12). Overall, c-MYC positivity (IRS ≥ 2) was observed in 13.3% of NEN. Expression was detected in 43% of NEC (164/381), including strong staining in 19.4%, whereas it was rare in NET and pulmonary carcinoids (20/999; 2%; p ≤ 0.001). Within NEC, c-MYC expression was enriched in LCNEC and MiNEN compared with SCNEC and Merkel cell carcinoma (p ≤ 0.001) and occurred more often in gastroenteropancreatic than in pulmonary NEC (57.6% vs. 37.3%; p ≤ 0.001). Among NET, G3 tumours showed the highest positivity rate (6/35; 17.1%), although this was significantly lower than in NEC (p ≤ 0.001), with strong expression observed in only one NET G3 (2.9%). No association between c-MYC expression and survival was identified in either NEC or NET. Our study confirms c-MYC expression as a common event in NEC and highlights differences across histological subtypes and anatomical sites, while demonstrating its absence in most low-proliferative NET. A subset of NET G3 tumours exhibits weak to moderate c-MYC expression at levels far below those seen in NEC, suggesting that strong c-MYC positivity may support a NEC classification in borderline cases but does not represent a definitive discriminatory marker.

Humans↗
PubMed2026

A pro-inflammatory metastasis-associated macrophage subset induces tumor-promoting mesothelial cell conversion in ovarian cancer via IL-1α secretion.

Tumor-associated macrophages (TAMs) are key regulators of the tumor microenvironment, yet the functional specialization of TAM subsets in metastatic progression remains incompletely defined. Here, we characterized distinct TAM populations contributing to tumor-promoting mesothelial cell conversion in high-grade ovarian carcinoma using single-cell RNA sequencing of patient-derived macrophages from ascites (ascTAMs) and omental metastases (omTAMs). TAMs from these anatomical sites were clearly distinguishable by polarization states, with omTAMs exhibiting a mixed M1⁺/M2⁺ phenotype, in contrast to the M1low/M2⁺ profile observed in ascTAMs. Transcriptomic analysis further revealed functional divergence of these subsets. Notably, omTAMs displayed gene signatures associated with mesothelial-to-mesenchymal transition (MMT), a critical process enabling tumor invasion across the peritoneal lining. Functionally, conditioned media from omTAMs, similar to that from classically activated M1 macrophages, induced MMT in primary mesothelial cells via TGFβ and ERK/p38 MAPK signaling pathways. This phenotypic transition enhanced transmesothelial tumor cell invasion. Proteomic analysis identified IL-1α as a key MMT-inducing factor secreted by pro-inflammatory macrophages. Mechanistically, IL-1α cooperates with TGFβ by activating an autocrine TGFβ/TGFBR1 feedback loop in mesothelial cells, thereby amplifying MMT. Consistent with these findings, IL1A expression was enriched in omTAM clusters across independent patient samples and was confirmed by immunohistochemical analysis of clinical samples. From a therapeutic perspective, our study identifies new avenues to counteract the mesothelial reprogramming driven by IL-1α⁺ TAMs, potentially impeding metastatic progression. Created in BioRender. Heidemann, S. (2026) https://BioRender.com/aeu6yd0 .

Female↗
PubMed2026

Ascites reprograms innate lymphoid immune cells in ovarian cancer by promoting ILC2 enrichment and dysfunctional NK-cell states.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is commonly accompanied by malignant ascites, a clinically relevant tumor niche that promotes immune evasion, metastasis, and treatment resistance. Although natural killer (NK)-cell dysfunction has been described in ovarian cancer, the broader innate lymphoid landscape of ascites and the mechanisms linking ascites-derived signals to innate immune suppression remain insufficiently resolved. METHODS: We performed single-cell RNA sequencing of NK/innate lymphoid cells from ovarian cancer ascites to define cellular heterogeneity and differentiation states. Functional assays assessed NK-cell cytotoxicity, degranulation, and receptor expression following exposure to patient-derived ascites, with or without transforming growth factor-β (TGF-β) receptor inhibition. Proteomic profiling was used to characterize the soluble ascites milieu, and clinical associations were examined for innate lymphoid subsets. RESULTS: Single-cell analysis identified eight transcriptionally distinct NK/innate lymphoid states, including cytotoxic, precursor, early-like, tolerant/immunoregulatory, regulatory, proinflammatory, and innate lymphoid populations. Ovarian cancer ascites was characterized by depletion of cytotoxic and precursor NK-cell states together with enrichment of early-like, tolerant, regulatory, pro-inflammatory, and innate lymphoid cell (ILC) populations. Trajectory analysis indicated impaired maturation toward terminally differentiated cytotoxic NK cells. Notably, ascites contained an expanded population of programmed cell death protein 1 (PD-1)+ ILC2s, which were more abundant in patients with shorter progression-free survival. In functional assays, short-term exposure of healthy donor NK cells to ascites suppressed degranulation and tumor-cell killing, reduced expression of activating receptors including NKp30 and DNAM-1, increased inhibitory receptor expression, and shifted NK cells toward a CD56highCD16low phenotype. Proteomic profiling supported a soluble milieu consistent with type 2 immune skewing and NK-cell suppression. Importantly, TGF-β receptor inhibition partially restored NK-cell activation and function in the presence of ascites. CONCLUSIONS: HGSOC ascites establishes a type 2-skewed immunoregulatory niche that coordinately drives NK cell dysfunction and PD-1+ ILC2 accumulation. The findings identify TGF-β-linked suppression and ascites-associated immune regulators as candidate immunotherapeutic vulnerabilities for restoring antitumor immunity in ovarian cancer.

Humans↗
PubMed2026

Pembrolizumab plus chemotherapy followed by pembrolizumab in participants in Asia with early triple-negative breast cancer: An updated subgroup analysis of the KEYNOTE-522 randomized clinical trial.

BACKGROUND: In KEYNOTE-522 (NCT03036488), addition of perioperative pembrolizumab to neoadjuvant chemotherapy significantly improved pathological complete response (pCR), event-free survival (EFS), and overall survival (OS) in early-stage triple-negative breast cancer (TNBC). pCR and EFS results in participants enrolled in Asia were consistent with those in the overall population. We report OS, updated EFS, and safety outcomes in participants enrolled in Asia. METHODS: Participants with newly diagnosed, high-risk, early-stage TNBC (T1c [N1‒N2] or T2‒T4 [N0‒N2] per AJCC 7th edition) were randomized 2:1 to 8 cycles of neoadjuvant pembrolizumab 200 mg Q3W or placebo plus chemotherapy. After definitive surgery, participants received adjuvant pembrolizumab 200 mg Q3W or placebo for ≤9 cycles. Primary endpoints were pCR (ypT0/Tis ypN0) and EFS. OS was a secondary endpoint. RESULTS: Of 1174 randomized participants, 216 were enrolled in Asia. At data cutoff (March 22, 2024), EFS events occurred in 18/136 participants (13.2%) in the pembrolizumab + chemotherapy group versus 22/80 (27.5%) in the placebo + chemotherapy group (HR, 0.43 [95% CI, 0.23‒0.81]); 60-month EFS rates (95% CIs) were 87.4% (80.6%‒92.0%) and 72.1% (60.7%‒80.6%), respectively. In the respective groups, 12/136 (8.8%) and 16/80 participants (20.0%) died (HR, 0.41 [95% CI, 0.19‒0.86]); 60-month OS rates (95% CIs) were 91.9% (85.8%‒95.4%) and 81.1% (70.5%‒88.1%). Treatment-related AEs led to treatment discontinuation in 19/136 participants (14.0%) with pembrolizumab + chemotherapy and 7/79 (8.9%) with placebo + chemotherapy. CONCLUSIONS: OS and updated EFS outcomes in KEYNOTE-522 participants enrolled in Asia were consistent with those in the overall population and support use of perioperative pembrolizumab + neoadjuvant chemotherapy as a standard-of-care treatment in this setting.

Adjuvant↗
PubMed2026

Clinical and Molecular Evaluation of HER2-Low and HER2-Ultralow Breast Cancer in the Penelope-B Clinical Trial Cohort.

The DestinyBreast (DB)04 and DB06 trials have shown clinical activity of trastuzumab-deruxtecan (T-DXd) in HER2-low and HER2-ultralow metastatic breast cancer. The identification of HER2-low and HER2-ultralow breast cancer is therefore essential for personalized therapy with T-DXd. We evaluated 723 residual tumors from the Penelope-B trial (NCT01864746) and correlated different levels of HER2 protein expression with prognosis and messenger RNA (mRNA) profiles, including HER2 transcripts. In Penelope-B, 57.68% (n = 417) of 723 residual tumors were HER2 low. The HER2-ultralow category was assigned to 109 (15.08%) tumors, and 197 (27.25%) tumors were completely HER2 negative (HER2 0). In Kaplan-Meier analysis, there were no survival differences among these 3 subgroups. There was no significant difference in HER2 mRNA expression between HER2-0 and HER2-ultralow tumors (P = .08). In contrast, there was a highly significant difference in HER2 mRNA expression between HER2-ultralow and HER2-low tumors (P < .0001) and between HER2-low and HER2-positive tumors (P < .0001). The extracellular protease cathepsin L, which has been suggested as a biomarker for extracellular cleavage of T-DXd, was detectable in all HER2-related subgroups and was a negative prognostic factor for invasive disease-free survival and overall survival (P = .0001) in preneoadjuvant core biopsies. In our study, we were able to characterize HER2 low as a clinically relevant and molecular defined tumor group with significantly increased HER2 expression. In contrast, for HER2 ultralow, we did not observe a defined molecular phenotype, despite the clinically relevant regulatory approval of T-DXd also in the ultralow subgroup. Additional investigations are needed to identify biomarkers beyond HER2 for T-DXd response as a basis for refined criteria for treatment eligibility.

Adult↗
PubMed2026

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74&#xb7;1 months (IQR 68&#xb7;3-75&#xb7;4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0&#xb7;84 [95% CI 0&#xb7;79-0&#xb7;88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11&#xb7;6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0&#xb7;41-0&#xb7;93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0&#xb7;36-0&#xb7;48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (&#x2265;70&#xb7;0%; mean absolute improvement 12&#xb7;1 percentage points [SD 2&#xb7;8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0&#xb7;010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

Humans↗
PubMed2026

Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study.

BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are a robust prognostic marker in patients with triple-negative breast cancer. Artificial intelligence (AI)-derived computational tools assessing TILs could improve efficiency, but require independent validation against clinical outcomes. We aimed to compare the prognostic performance of AI-derived TIL scores with pathologist-scored TILs in a large, prospectively collected dataset pooled from randomised controlled trials. METHODS: CATALINA was an independent, external validation study using prospectively collected long-term clinical outcome data pooled from seven randomised clinical trials conducted at multiple sites. We independently evaluated two previously validated AI pipelines that generate five computationally assessed tumour-infiltrating lymphocyte (cTIL) scores by masked, independent deployment of locked models. cTIL scores were correlated with the mean of the pathologist-scored stromal TILs (sTILs) in 220 digitised haematoxylin and eosin whole slide images in a cohort of patients with early-stage triple-negative or HER-2 positive breast cancer, previously scored by trained pathologists in a TIL-reproducibility study. Prognostic performance was assessed in a separate cohort of patients with early triple-negative breast cancer pooled from seven prospective, randomised adjuvant trials. Multivariable Cox regression models adjusted for clinicopathological factors and study heterogeneity assessed associations of cTIL score and sTIL score with invasive disease-free survival, distant disease-free survival, and overall survival. 5-year discrimination was estimated using time-dependent area under the receiver operating characteristic curve (AUC). FINDINGS: Individual data were collated from 1759 patients, of whom 1356 had complete clinicopathological data, pathologist sTIL scores, and cTIL scores available. Modest correlation (r 0&#xb7;375-0&#xb7;473) was observed between cTIL scores and the mean pathologist sTIL score. Both sTIL and cTIL were independently associated with 5-year invasive disease-free survival, distant disease-free survival, and overall survival after adjustment for clinicopathological factors (hazard ratio for invasive disease-free survival was 0&#xb7;73 [95% CI 0&#xb7;66-0&#xb7;82]; q<0&#xb7;0001, distant disease-free survival was 0&#xb7;70 [0&#xb7;61-0&#xb7;79]; q<0&#xb7;0001, and overall survival was 0&#xb7;72 [0&#xb7;63-0&#xb7;82]; q<0&#xb7;0001 for sTIL scores and 0&#xb7;80 [0&#xb7;73-0&#xb7;89]; q<0&#xb7;0001, 0&#xb7;77 [0&#xb7;69-0&#xb7;86]; q<0&#xb7;0001, and 0&#xb7;79 [0&#xb7;70-0&#xb7;88]; q=0&#xb7;0002, respectively, for percentage_lymphocyte scores). In models adjusted for clinicopathological variables and sTIL score, cTIL score did not maintain a statistically significant prognostic association. Both sTIL and cTIL scores improved the 5-year AUC over clinicopathological variables alone, while cTIL score did not significantly further improve AUC when combined with clinicopathological variables and sTIL score. INTERPRETATION: Two cTIL models deployed entirely without retraining or modification provided statistically significant prognostic information and improved risk discrimination compared with clinicopathological variables alone in this large, platform-based, independent validation study. Although cTIL score did not incrementally improve prognostication compared with models combining clinicopathological variables with sTIL score, these findings support the application of cTILs as a reproducible prognostic biomarker, particularly in settings where routine or widespread pathologist assessment is unavailable. FUNDING: Breast Cancer Research Foundation (USA).

Humans↗