Aug 2026· Diseases of the esophagus· Vol 39· 0 citations
TL;DR
The first validated morpho-molecular classification of Esophageal adenocarcinoma is reported, with the transitional and signet ring signatures associated with worse prognosis compared to tumors with a glandular signature.
Abstract
Esophageal Cancer: Molecular Biology/Pathology
Esophageal adenocarcinoma (EAC) is histologically graded as well, moderately, or poorly differentiated. Poorly differentiated tumours are associated with worse prognosis compared to well and moderately differentiated tumours. However, the molecular mechanisms driving these differences are poorly understood and their delineation may lead to improved biologically-informed patient stratification and therapeutic development.
We primarily analyzed two cohorts of laser-capture microdissected (LCM) EAC samples: a discovery cohort consisting of 73 untreated primary biopsies and a validation cohort of 34 metastatic and/or post-treated samples. Additional validation cohorts included an independent cohort from The Cancer Genome Atlas (TCGA; n=80), a spatial transcriptomics (Visium) cohort (n=6), and a patient-derived EAC organoids cohort (n=24). Consensus non-negative matrix factorization (NMF) was performed on the discovery cohort (K=9 components, 3 glandular, 2 transitional, 1 signet ring associated, and 3 others) and independently on TCGA (K=9, 3 glandular, 1, transitional, and 5 other). The discovery NMF was projected onto the validation cohort. Morphology scores were calculated by summing sample component weights within their predefined component groups and correlated with histologic quantification by a board-certified gastrointestinal pathologist.
The discovery NMF model was validated in TCGA, where all three glandular signatures and one transitional signature were reproducible. The second transitional signature was confounded by squamous contamination in TCGA samples. The signet ring-associated component was not detected in TCGA and was not observed in corresponding slide images. NMF-derived morphology scores accurately predicted tumour histology (Figures 1,2), with mean absolute errors (percentage points) of 16.05%/14.89% (glandular), 13.59%/15.36% (transitional), and 8.18%/9.41% (signet ring) in discovery/validation cohorts, respectively; these errors seem reasonable given potential LCM bias and the inherent limitations of pathologist quantification. Signatures were further validated by spatial transcriptomics with pathologist annotations, multi-area within-slide LCM RNA-seq, and patient-derived EAC organoids. Importantly, the transitional and signet ring signatures were associated with worse prognosis compared to tumors with a glandular signature.
We report the first validated morpho-molecular classification of EAC. Our findings highlight the limitations of bulk RNA-seq, particularly the overinflation of poorly differentiated signatures due to the presence of squamous contamination and demonstrate the value of profiling following LCM. Ongoing studies are integrating whole-genome sequencing and clinical correlates to further define the biological and therapeutic implications of these morpho-molecular subtypes.
Colon cancer is a major global malignancy with significant mortality. Right-sided (RCC) and left-sided colon cancers (LCC) exhibit distinct clinicopathological characteristics. Tumor microenvironment score (TMS) combines Klintrup-Mäkinen grade, tumor stroma percentage, and tumor budding, classifying cases into 4 groups (TMS 0-3). Evaluation of TMS is an integrative method for prognostic classification; however, further validation is needed, and differences between RCC and LCC remain unclear. A discovery cohort (n=940) and a validation cohort (n=613) were retrospectively included. TMS was evaluated from hematoxylin-eosin-stained slides. Five-year disease-specific survival (DSS) was analyzed using life-table methods and Cox regression. Associations with clinicopathological variables were assessed. In both the discovery and validation cohorts, higher TMS was associated with worse 5-year DSS in univariable analyses for both RCC and LCC. In multivariable analysis, high TMS (TMS3 vs. TMS0) remained independently associated with survival in the discovery cohort (RCC-HR: 2.47, 95% CI: 1.36-4.46, P=0.003; LCC-HR: 3.08, 95% CI: 1.46-6.45, P=0.003). In the validation cohort, the prognostic impact of TMS was more pronounced in RCC (HR: 4.35, 95% CI: 2.32-8.14, P<0.001) than in LCC (HR: 2.21, 95% CI: 0.81-6.03, P=0.12). TMS also appeared to provide improved prognostic stratification compared with the Glasgow microenvironment score (combination of Klintrup-Mäkinen grade and tumor stroma percentage). In conclusion, TMS serves as an integrative histopathological marker with potential to improve prognostic stratification in colon cancer, particularly in right-sided tumors.
Mari J. Jawad, Vilja V Tapiainen, Ville K. Äijälä et al.· American Journal of Surgical...· 0 citations
Esophageal Cancer: Molecular Biology/Pathology
The tumor microenvironment (TME) holds an important role in the biological behaviour of the esophageal cancer, influenced by neoadjuvant treatment (NAT). However, its correlation to patient outcomes remains poorly defined. The aim of this study was to assess the prognostic value of TME in terms of long-term recurrence and survival.
All eligible patients with esophageal adenocarcinoma (EAC) and squamous cell carcinoma (SCC), treated with curative intent including surgery between 01.2009 and 12.2021, were retrospectively analyzed. Immunohistochemical analysis of pre-treatment biopsies and surgical specimens, was performed for biomarkers CD3, CD8, CD68, CD163, Treg/FoxP3 and PD-L1 (combined positive score, CPS). Histologic slides were scanned at high resolution (x400), and the above biomarkers were eye-counted as mean number/high power field. Pathological response to NAT was assessed with the Mandard tumor regression grade (TRG). The chi2 and Fisher tests were used to compare categorical, and the student’s t test continuous variables. Overall survival (OS) and disease-free survival (DFS) were analyzed using Cox simple and multiple regression.
Overall, 64 patients were included (51 EAC, 13 SCC) in the present study; 81% of patients were male, with a median age of 64 years (IQR 57-69), and a median follow-up of 48 months. Although baseline TME composition was comparable in all patients, poor pathological responders (TRG 3-5) showed higher macrophage infiltration after NAT compared to good responders (TRG 1-2) (Mean total macrophages [CD68+] 63.6 poor vs 44.3 good responders, p = 0.002, mean M2-like [CD163+] 50.3 poor vs 38.3 good responders, p = 0.038). In multivariable analysis, Treg/FoxP3 expression (HR 0.95, 95% CI 0.90–1.00, p = 0.041) and pathological nodal status (HR 2.37, 95% CI 1.58–3.54, p < 0.001) remained independent predictors of DFS, but not OS. Within the EAC subgroup, FOXP3 expression was associated with more favourable OS (adjHR 0.93, 95% CI0.88–0.98, p = 0.008) and DFS (adjHR 0.95, 95% CI 0.90–1.00, p = 0.049).
The present study indicates increased macrophage concentration (total and M2-like phenotype) to be related to poor response to NAT. In addition, increased numbers of Treg/FOXP3 lymphocytes were associated with a more favourable overall and disease-free patient survival especially within the adenocarcinoma histology. Targeted agents with inhibitory action towards macrophages and expansive action for Treg/FOXP3 lymphocytes might have therapeutic potential for esophageal cancer patients.
H. T. Farinha, François Fasquelle, Raphaël Marangon et al.· Diseases of the esophagus· 0 citations
BACKGROUND AND AIMS
Peritoneal metastases (PMs) represent the most frequent, clinically challenging dissemination pattern in advanced gastric cancer, especially poorly cohesive (PCGC) subtype, and are associated with poor prognosis. We aimed to characterize the transcriptomic landscape of primary gastric tumors (PGTs) and matched PMs to identify differential molecular programs, tumor-microenvironment (TME) features, and potential biomarkers.
METHODS
We analyzed 55 FFPE samples from 23 treatment-naïve patients with synchronous peritoneal-only stage IV PCGC and 10 non-neoplastic gastric controls (NNC). RNA sequencing was analyzed using DESeq2 and GSEA, with cell proportions estimated through immune deconvolution (TIMER/xCell).
RESULTS
A total of 4279 differentially expressed genes were identified across all groups. CLDN18 expression progressively decreased from NNCs to PGTs and PMs. Direct PGT-PM comparison revealed that PGTs were characterized by cytoskeletal and extracellular-matrix remodeling genes upregulation, mitotic/cell-cycle, NOTCH and apical-junction pathways enrichment, and memory T-cell predominance. Compared with PGTs, PMs showed increased IGF1, IGFN1, NTRK2 and adipogenesis-related transcripts, adipogenesis and MAPK7/11-NTRK2 signaling enrichment, and macrophage-dominant and dendritic-cell-dominant microenvironments. epithelial-mesenchymal transition (EMT), inflammatory pathways, and cancer-associated fibroblasts were shared by both tumor lesions. PMs did not match established TCGA or PCGC subtypes, suggesting a distinct molecular identity.
CONCLUSIONS
PMs are characterized by TME remodeling and transcriptional reprogramming. Shared EMT and inflammatory pathways act as bridge linking PGT to PM, consistent with adaptive exploitation of physiological peritoneal programs. Collectively, our findings suggest a transcriptomic framework in which PM can be characterized as a distinct niche-conditioned biological entity and support microenvironment-informed diagnostic and therapeutic strategies.
M. Bencivenga, M. Simbolo, Stefano Gobbo et al.· Annals of Surgery· 0 citations
High-grade serous ovarian carcinoma (HGSOC) displays pronounced histological and microenvironmental heterogeneity that contributes to therapeutic resistance and poor survival. Artificial Intelligence (AI)-derived cellular morphometric biomarkers (CMBs) from routine hematoxylin and eosin (H&E) whole-slide images (WSIs) provide an unbiased means to quantify tissue heterogeneity and infer tumor microenvironment (TME) states; however, their associations with immune contexture and survival across diverse populations remain unknown. We applied a machine-learning cellular morphometric biomarker (CMB) pipeline to H&E images from 106 patients in The Cancer Genome Atlas ovarian cohort (TCGA-OV) and an independent cohort of 22 patients with HGSOC collected at Loma Linda University (LLU-OV). Differential CMBs were identified, corroborated across cohorts, and evaluated for associations with overall survival (OS). Immune deconvolution and checkpoint gene expression analyses were performed using TCGA data, while CD3, CD8, and PDCD1 immunohistochemistry (IHC) assessed immune infiltration in LLU samples. Three reproducible CMBs (CMB73, CMB80, CMB215) demonstrated consistent patterns across cohorts. Higher abundances of CMB73 and CMB80 were associated with worse OS and reduced immune infiltration, whereas CMB215 correlated with improved OS and immune-enriched TMEs, including increased PDCD1, PDCD1LG2, and CD8A expression. IHC findings showed significant association of OS with T cells and age. Overall, AI-derived CMBs capture clinically meaningful heterogeneity and provide a scalable New Approach Methodology (NAM) framework for immune-informed risk stratification in HGSOC.
Jane M Muinde, Joseph Cruz, Dan K. Celestin et al.· AI in Precision Oncology· 0 citations
Cutaneous squamous cell carcinoma (cSCC) is the second most common form of cancer worldwide. While most cSCCs are not life-threatening, 2-5% of patients develop metastases. To better understand what causes some cSCCs to progress to metastatic disease, we assembled a nationwide cohort of 19,120 patients with clinico-pathologically annotated tumors linked to metastatic outcome. RNA-sequencing was performed on 378 tumors, and whole-exome sequencing on 147, with balanced numbers of tumors that progressed to metastatic disease (cases) and did not (controls). UV radiation was the dominant mutational signature with additional contributions from aging, APOBEC activity, and, in immunosuppressed patients, azathioprine exposure. We identified 38 genes under selection across a core set of signaling pathways. Gene expression clusters were primarily associated with the differentiation state of tumor cells and secondarily with the composition of the tumor microenvironment. Several mutational and transcriptional programs were associated with metastasis, including a dedifferentiated gene expression signature, activating mutations in the RAS signaling pathway, loss-of-function alterations in the SWI/SNF chromatin remodeling complex, and specific arm-level copy number alterations. A 23-gene expression signature was built to predict metastasis from primary cSCC tissue. The signature was validated in two independent cohorts (N=102 and 52), where it predicted metastasis independently of staging systems. Together, these findings provide the most detailed molecular portrait of cSCC to date and establish an assay for risk stratification suitable for clinical implementation.
B. Rentroia-Pacheco, Harsh Sharma, L. Pozza et al.· medRxiv· 0 citations
Background and Objectives: Non-small cell lung cancer (NSCLC) comprises biologically distinct histologic subtypes, including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). We evaluated whether the prognostic association of cyclin-dependent kinase-like 2 (CDKL2) differs by histology. Materials and Methods: TCGA CDKL2 expression was linked to harmonized clinical data. The primary analysis used a pooled multivariable Cox model with continuous standardized CDKL2 expression, histology, and a CDKL2 × histology interaction, adjusted for age, sex, pathologic stage, and smoking. Additional analyses assessed model assumptions, tumor purity, tumor-versus-normal expression, KEGG pathways, the tumor microenvironment, and single-cell RNA sequencing. External evaluation used GSE30219. Results: The primary TCGA cohort included 943 patients (471 LUAD, 472 LUSC; 375 deaths). Higher CDKL2 expression was associated with lower mortality in LUAD (HR per 1 pooled SD = 0.721, 95% CI 0.603–0.862, p < 0.001) but higher mortality in LUSC (HR = 1.237, 95% CI 1.011–1.515, p = 0.039), with a significant interaction (HR = 1.717, p < 0.001) persisting after tumor-purity adjustment. CDKL2-low tumors were enriched for cell-cycle, DNA-replication, proteasome, and DNA-repair programs. Single-cell analyses showed predominant epithelial detection and greater malignant-cell CDKL2 detection in LUAD. In GSE30219, the favorable LUAD association was supported in a median-split-adjusted analysis of 207073_at (HR = 0.473, 95% CI 0.250–0.897, p = 0.022), whereas the corresponding continuous estimate was directionally favorable but nonsignificant; 236331_at was nonsignificant in both models; neither probe supported the adverse LUSC association or histology interaction. Conclusions: Higher CDKL2 expression showed a favorable prognostic association in LUAD, with consistent TCGA sensitivity analyses and limited but suggestive independent-cohort support. The adverse LUSC association remains preliminary, and CDKL2 should be regarded as a candidate prognostically associated marker rather than an established clinical biomarker.
Min-Ji Song, Yun-Han Lee, Junchae Lee et al.· Medicina· 0 citations
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