pACC and pAMPK Immunohistochemical Quantification in Recurrent Glioblastoma treated with regorafenib or with fotemustine/lomustine — Digital Pathology Dataset

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Dataset Overview This dataset contains quantitative immunohistochemical (IHC) data obtained from tumor sections of patients with recurrent glioblastoma (GBM), generated as part of a retrospective, multicenter real-world study. All samples were analyzed using standardized digital pathology workflows with the ImageScope software (v.12.4.2.5010, Leica Biosystems). No whole-slide images are included; only the numerical outputs of the automated IHC quantification are provided. The dataset supports investigation of the expression patterns and predictive value of two markers of the LKB1/AMP-activated protein kinase (AMPK) metabolic pathway: · pACC (phospho-Acetyl-CoA Carboxylase, Ser79) — a canonical downstream target of AMPK, whose phosphorylation reflects AMPK-mediated inhibition of fatty acid synthesis and metabolic adaptation to energy stress. · pAMPK (phospho-AMP-activated protein kinase, Thr172) — a marker of AMPK activation along the LKB1/AMPK signaling axis. Scientific Context Regorafenib is a small-molecule multikinase inhibitor targeting VEGFR-1–3, TIE2, PDGFR-β, FGFR, and oncogenic kinases such as KIT, RET, RAF1, and BRAF. Based on its broad kinase-inhibitory profile and encouraging preclinical activity in GBM models, regorafenib has been evaluated in the recurrent GBM setting. The randomized, multicenter phase II REGOMA trial first demonstrated that regorafenib significantly improves overall survival compared with lomustine in patients with relapsed IDH-wild-type GBM, establishing this drug as a viable second-line option. The large, multicenter REGOMA-OSS observational study subsequently confirmed that regorafenib yields a median overall survival and toxicity profile comparable to those observed in the original REGOMA trial, supporting its activity in routine clinical practice. The REGOMA translational program identified several in situ biomarkers related to tumor metabolism and the LKB1/AMPK pathway that might modulate response to antiangiogenic therapy. Prior analysis of tumor sections from the REGOMA cohort showed that pACC expression was associated with a clinically meaningful benefit in terms of overall survival among patients treated with regorafenib, whereas no significant association was observed in the lomustine-treated arm, suggesting that basal activation of the AMPK/pACC axis may identify a subset of GBM patients more likely to respond to this antiangiogenic-metabolic targeting strategy. Despite these encouraging findings, the pattern of expression of AMPK markers in GBM has been characterized only in small cohorts of patients and the prognostic value is not firmly established. The present dataset was generated to chart patterns of expression of AMPK markers in a broader, real-world cohort and to further investigate the predictive value of pACC expression in recurrent GBM treated with regorafenib, by integrating refined IHC assessment with standardized digital pathology. File Structure The dataset is organized in a single Excel workbook containing four sheets, stratified by treatment arm and marker: Sheet 1: pACC, Regorafenib (second-line) Sheet 2: pACC, Fotemustine / Lomustine (second-line) Sheet 3: pAMPK, Regorafenib (second-line) Sheet 4: pAMPK, Fotemustine / Lomustine (second-line) Variables Each row corresponds to one tumor sample. The following variables are reported for each sample in each sheet: Sample ID: Anonymized patient identifier (progressive code), Categorical Treatment group: Second-line therapy: Regorafenib or Fotemustine/Lomustine, Categorical % 0+: Percentage of cells classified as negative by ImageScope, Continuous (%) % 1+: Percentage of cells classified as weakly positive, Continuous (%) % 2+: Percentage of cells classified as moderately positive, Continuous (%) % 3+: Percentage of cells classified as strongly positive, Continuous (%) Sum % 2+ 3+: Sum of moderately and strongly positive cells (% 2+ + % 3+), Continuous (%) H-score: Composite IHC score (see formula below), Continuous (0–300) H-score Calculation The H-score is calculated as: H-score = (1 x %1+) + (2 x %2+) + (3 x %3+) with a theoretical range of 0 to 300. This score integrates both the proportion and the staining intensity of positive cells into a single composite index. Positivity Threshold The Sum % 2+ 3+ variable represents the fraction of tumor cells exhibiting moderate or strong IHC positivity. Digital Pathology Workflow IHC staining was performed on formalin-fixed paraffin-embedded (FFPE) tumor sections. Automated IHC quantification was performed using ImageScope software (v.12.4.2.5010, Leica Biosystems) with a validated algorithm for 4-tier chromogenic scoring (0+/1+/2+/3+). The same protocol and algorithm parameters were applied uniformly across all samples and both treatment arms. Data Privacy and Anonymization All samples have been fully anonymized prior to deposition. Patient identifiers have been replaced by a progressive numeric code. No date of birth, hospital record number, or direct identifiers are present. The dataset complies with applicable data protection regulations (GDPR). Funding This work was supported by European Union – NextGenerationEU PNRR-POC-2022-12375884 "Rafforzamento e potenziamento della ricerca biomedica del SSN", CUP J93C22002270006.

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