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PubMed2026

Enhancing Self Care Among Oral Cancer Survivors Using a Digital Approach: The Empowered Survivor Trial.

BACKGROUND: Oral and oropharyngeal cancer survivors experience debilitating physical and psychosocial challenges. Little knowledge exists on the efficacy of interventions to enhance self-efficacy in managing these challenges, increase survivorship preparedness, and improve health-related quality of life (HRQoL). METHODS: Individuals (n = 643) diagnosed with oral or oropharyngeal cancer diagnosed within past 3 years were randomized to a digital intervention, Empowered Survivor (ES) or a Generic Online Intervention (GO). Primary (self-efficacy, preparedness, HRQoL) and secondary outcomes (self-care activities) were measured at Baseline, 2-months, and 6-months. RESULTS: Participants assigned to ES reported greater self-efficacy and increased self-care activities of oral self-exams, swallowing, and mobility exercises than those assigned to GO (self-efficacy: 2 months, p = 0.003, 6-months, p < 0.001; self-care activities). CONCLUSIONS: The ES enhanced self-efficacy and increased self-care activities. Further examinations of survivorship preparedness and HRQoL in oral and oropharyngeal cancer are warranted. TRIAL REGISTRATION: Registered on clinicaltrials. gov as NCT04713449.

Humans↗

PubMed2026

Mining Stored-Specimen Studies for Information about Cancer Natural History.

The advent of new multicancer early detection tests and publication of early diagnostic results have generated expectations of clinical benefit from multicancer screening. The clinical benefit of a cancer screening test depends critically on disease natural history, which is typically learned from prospective screening studies. Retrospective studies of stored blood specimens are important in learning about a test's preclinical diagnostic performance but have rarely been used to infer natural history. The extent to which these studies might be harnessed to also learn natural history is discussed in the context of an article in this issue that infers the combined natural history of a range of cancers targeted by a multicancer early detection test using a case-control subsample of specimens from a large cohort study. The critical question concerns the identifiability of key transition rates in multistate models of natural history alongside state-specific sensitivities. The article suggests that these parameters are estimable within a Bayesian framework that leverages prior information about test sensitivity from diagnostic studies. We offer a heuristic discussion of identifiability in this setting and encourage formal study to determine the extent to which models with varying degrees of complexity may be learned from stored-specimen studies. See related article by Dai et al., p. 1535.

Humans↗

PubMed2026

Sarcomas: Research on Ultrarare Subtypes Gains Ground.

Rare cancers account for almost one fourth of all cancers. Sarcomas belong to the group of cancerous diseases with an incidence of less than 6 cases per 100,000 inhabitants. Over the past decade, activities were launched worldwide to elucidate the peculiarities of many of the more than 100 sarcoma subtypes described in the World Health Organization handbook. The major contributor to exact diagnosis is molecular pathology. The subgroup of ultrarare sarcomas (URS) poses a significant problem as each URS type has its own morphology, biology, natural history, and prognosis. In 2020, 35 international sarcoma centers agreed to standards of evaluating URS. The threshold was set to an incidence of less than 1 case per 1,000,000 inhabitants, and 77 URS subtypes were defined. Also quality criteria for centers to be selected for retrieving data to registries were consented. This issue of Cancer Epidemiology, Biomarkers & Prevention contains the first article to validate these principles of URS using the data from a nationwide cancer database. The authors from Taiwan also pointed out limitations of the approach. Combination with the national death database allowed to calculate overall survival (OS) and identified age as a significant factor for OS per URS type. These new data might foster future research on diagnosis and treatment of URS. See related article by Lee et al., p. 1654.

Humans↗

PubMed2026

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer↗

PubMed2026

Time-varying hazard rates reveal patterns of progression in HR+/HER2- metastatic breast cancer: Towards risk-adapted monitoring.

BACKGROUND: optimal imaging intervals for patients with hormone receptor-positive/HER2-negative metastatic breast cancer (MBC) remains undefined. Aim of this study was to analyze the temporal patterns of disease progression to identify high risk subgroups that may benefit from intensified monitoring. METHODS: we analyzed 149 hormone receptor-positive/HER2-negative MBC patients prospectively enrolled in the MAGNETIC.1 trial (NCT05814224) and treated with first line endocrine therapy. Hazard rates (HR) for disease progression were determined according to clinico-pathological and liquid biopsy features. RESULTS: in the overall population, two distinct progression-risk peaks emerged at 2-3 months (32.9/1000 person-months) and at 24 months (28.0/1000). Higher risk of progression was observed in lobular carcinoma (61.1) [HR 61.12 per 1000 person month (pm)], progesterone receptor-negative status (HR 39.07), fulvestrant-based treatment (HR 46.88), liver metastases (HR 59.00), and presence of ≥ 3 metastatic sites (HR 40.10). CONCLUSIONS: Hazard distribution in hormone receptor-positive/HER2-negative MBC is biphasic and modulated by readily available clinical variables. High-risk subgroups may benefit from intensified radiologic and liquid-biopsy surveillance during the first three months and around two years after treatment start.

Breast cancer↗

PubMed2026

Identifying biomarkers of accelerated ageing in cancer patients from routine clinical data.

INTRODUCTION: Cancer and ageing have a bidirectional relationship: age is the strongest risk factor for cancer, and cancer and treatments can accelerate ageing. Therefore, biological age can differ from chronological age; biomarkers are needed to stratify interventions to minimise accelerated ageing. METHODS: PhenoAge was calculated from routine blood test results of patients attending a Geriatric Oncology clinic. PhenoAgeAccel was the residual from a regression of PhenoAge against age. RESULTS: Data were available for 173 patients (62% male). Mean PhenoAge was higher than age (84.3 (12.6) vs 76.2 (7.24), p < 0.001), though the two were correlated (r = 0.579, p < 0.001). Unlike age, PhenoAge and PhenoAgeAccel were associated with one-year mortality (PhenoAge OR=1.083, 95% CI: 1.038-1.136; PhenoAgeAccel OR=1.096, 95% CI: 1.047-1.155). PhenoAge correlated with Clinical Frailty Score and Timed Up and Go (CFS: Rs=0.31, p < 0.001; TUG: Rs=0.25, p < 0.005); there were no correlations with age. PhenoAgeAccel correlated with the number of CGA interventions made (Rs=0.17, p < 0.05), unlike age and PhenoAge. Patients with diabetes mellitus had a higher PhenoAgeAccel compared to those without (3.40 vs -1.71, p = 0.002). In patients receiving systemic anti-cancer treatment, patients with PhenoAgeAccel calculated pre-treatment had less age acceleration than those with PhenoAgeAccel calculated post-treatment, both overall (2.18 vs -2.87; p = 0.048) and in matched samples (n = 21, 7.76 vs -2.87, p < 0.001). CONCLUSIONS: PhenoAgeAccel is a greater predictor of risk than chronological age in older people with cancer. This makes it a promising biomarker to stratify patients for holistic geriatric assessment, dose reductions, or future geroprotective measures which could be integrated within electronic healthcare record systems.

Humans↗

PubMed2026

Unveiling the power of TIIC: A prognostic tool for esophageal adenocarcinoma.

BACKGROUND: Esophageal adenocarcinoma (EAC) remains a lethal malignancy with limited prognostic tools for guiding immunotherapy. Tumor-infiltrating immune cells (TIICs) play a critical role in EAC prognosis and treatment response. METHODS: We integrated single-cell RNA sequencing and bulk transcriptome data from TCGA and GEO databases. TIIC-specific RNAs were identified via tissue specificity index calculation combined with machine learning feature selection. Twenty machine learning algorithms were benchmarked to construct an optimal TIIC signature score (TIIC-Score) based on the comprehensive C-index. Immunotherapy response, genomic mutation, and copy number variation were analyzed. Summary-data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) were performed to explore genetic associations. Core prognostic TIIC-related genes were functionally validated in esophageal cancer cell lines through loss-of-function assays. RESULTS: The TIIC-Score demonstrated robust prognostic value for 1-, 2-, and 3-year overall survival across multiple cohorts, outperforming 22 published models. High TIIC-Score was associated with poor survival and increased chromosomal instability. Mutation profiling revealed high frequencies of TP53 (78.2%), TTN (48.7%), and SYNE1 (30.8%). MR analysis identified a significant association between gastro-oesophageal reflux and EAC risk at SNP rs8130507. Functionally, CCNI was upregulated in esophageal cancer cells, and its knockdown suppressed malignant phenotypes while promoting apoptosis, supporting its pro-tumorigenic role. CONCLUSION: The TIIC-Score provides a novel prognostic framework for EAC that effectively stratifies patient risk and may help identify individuals most likely to benefit from immunotherapy.

Esophageal adenocarcinoma↗

PubMed2026

Exercise prehabilitation in head and neck cancer patients proposed for definitive chemoradiotherapy: The FIT4TREAT randomized controlled trial.

BACKGROUND: Patients with head and neck cancer (HNC) initially scheduled for definitive chemoradiotherapy (CRT) often experience early functional decline and deterioration in health-related quality of life (HRQoL) even before treatment initiation. Evidence for prehabilitation in this non-surgical setting remains limited. This study evaluated whether exercise prehabilitation (EP) initiated before CRT improves functional capacity compared with usual care (UC). METHODS: FIT4TREAT (ClinicalTrials.gov: NCT05418842) was a prospective, single-center, randomized clinical trial. Adults with HNC proposed for definitive CRT were randomly assigned (1:1) to EP or UC. EP consisted of supervised combined aerobic and resistance exercise performed three times per week from baseline until radiotherapy initiation. The primary outcome was the six-minute walk distance (6MWD) at the end of the pre-treatment period. Secondary outcomes included muscle strength, lower-limb functionality, body composition, and HRQoL assessed using the EORTC QLQ-C30 and QLQ-HN43. RESULTS: Between May 2021 and February 2025, 47 patients were enrolled; 40 were included in the primary analysis. After adjustment for baseline 6MWD and the randomization stratification variables, EP resulted in a significantly greater pre-treatment 6MWD than UC (adjusted between-group difference, 28.6 m; 95 % CI, 4.1-53.1; P = 0.023). EP also improved lower-limb functionality (P < 0.001) and was associated with better preservation in the QLQ-C30 summary score (P = 0.008), social functioning (P = 0.038) and body image (P = 0.011). CONCLUSION: EP before definitive CRT improves functional capacity and may help preserve HRQoL in patients with HNC, supporting its potential integration into routine oncology care.

Humans↗

PubMed2026

Characterization of ZIC5 expression in esophageal squamous cell carcinoma and its association with patient survival.

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignancy known for its aggressive nature and poor prognosis. The present study aimed to investigate the expression levels and clinical importance of the Zic family member 5 (ZIC5) gene in ESCC. Gene expression data and survival information obtained from The Cancer Genome Atlas and Gene Expression Omnibus were utilized. In 176 patients with surgically resected ESCC, immunohistochemical analysis was conducted to validate the expression of ZIC5 protein in cancerous and adjacent tissues. The findings of the present study revealed a significant upregulation of ZIC5 in ESCC compared with normal tissues (P<0.05), which was further corroborated by immunohistochemistry exhibiting a notable association between ZIC5 expression and clinical parameters such as tumor size, invasion depth, lymph node metastasis and TNM staging (P<0.05). Survival analysis further indicated that high ZIC5 expression was an independent prognostic factor for poor outcomes in patients with ESCC (hazard ratio=1.519; 95% CI: 1.017-2.269; P<0.05). In addition, bioinformatic analyses predicted that hsa-microRNA-212-5p may regulate ZIC5 mRNA and gene enrichment analysis suggested that ZIC5 may facilitate ESCC progression through involvement in the cell cycle and DNA repair pathways. In conclusion, ZIC5 is highly expressed in ESCC and associated with a poor prognosis, indicating its potential as a therapeutic target and biomarker for ESCC management. Further studies are warranted to elucidate the precise mechanisms underlying the role of ZIC5 in ESCC progression.

ESCC↗

PubMed2026

In vitro evaluation of sacituzumab govitecan in non-small cell lung cancer with actionable genomic alterations.

PURPOSE: The TROP2-directed antibody-drug conjugate sacituzumab govitecan (SG) has shown substantial therapeutic benefit in several malignancies; however, preclinical evidence supporting its activity in non-small cell lung cancer (NSCLC) is rare. MATERIALS AND METHODS: We evaluated 16 NSCLC cell lines harboring actionable genomic alterations for TROP2 expression and treated them with SG or its unconjugated payload, SN-38, for 3 days to determine cytotoxic effects. Apoptosis and DNA damage signaling were assessed using flow cytometry and western blot. SG internalization and lysosomal trafficking were visualized by confocal microscopy. RESULTS: SG had greater cytotoxic potency than SN-38, across all NSCLC cell lines, independent of genomic subtype or TROP2 expression level. Cell lines that were sensitive to SN-38 showed enhanced vulnerability to SG (P < 0.0001). Higher SLFN11 expression, a recognized determinant of SN-38 responsiveness, correlated with lower SG IC50 values. Both SG and SN-38 triggered apoptotic and DNA damage responses within 6-48 h, with SG inducing stronger activation of these pathways than SN-38. SG was efficiently taken up in CUTO17 and SNU-3173 adenocarcinoma cells, with more than 60% of the conjugate internalized within 3 h and subsequently localized to lysosomes. CONCLUSION: Our study provides in vitro evidence supporting the potential activity of SG in NSCLC with actionable genomic alterations. The efficacy of SG closely paralleled intrinsic sensitivity to the SN-38 payload, suggesting that DNA-damage responses, rather than oncogenic drivers, predominantly contribute to SG activity.

Actionable genomic alterations↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.

PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization. MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines (PROSPERO: CRD42024539475) across five databases. Meta-analyses used random-effects models with logit-transformed Area Under the Curve (AUCs) and cluster-robust standard errors. AI models were classified as Machine Learning Models (MLM) or Hybrid Nomograms (HN) based on their construction methodology. RESULTS: Of 3,742 articles identified, 53 were included. MLMs demonstrated higher point estimates than radiologists in differential diagnosis (AUC: 0.87 vs. 0.83), though this difference was not statistically significant and carried substantial uncertainty. HNs achieved stronger performance in risk stratification (AUC: 0.87). AI-derived nomograms (AUC: 0.9) and gene signatures (AUC: 0.8) outperformed conventional prognostic markers descriptively. Chemotherapy response prediction remained below clinical utility thresholds across all model types. Only 33.9% of models reported calibration and 24.5% underwent external validation. CONCLUSIONS: AI demonstrates proof-of-concept across multiple NB clinical domains. However, clinical adoption remains premature given persistent gaps in external validation, calibration, dataset size, and pediatric-specific model development. Future studies should test these models prospectively in multicenter pediatric cohorts, ideally through COG or SIOPEN, using shared definitions for diagnosis, risk group, treatment response, and survival outcomes.

Humans↗

PubMed2026

Older adults with resectable gastric cancer undergoing perioperative chemotherapy or preoperative chemoradiotherapy plus perioperative chemotherapy: A secondary analysis of the AGITG TOPGEAR phase III trial.

PURPOSE: To evaluate treatment adherence, adverse events, and survival in older (≥70 years) adults undergoing perioperative treatment for gastric cancer. METHODS: Patients with resectable gastric/gastro-esophageal junction adenocarcinoma (ECOG 0-1) enrolled in the phase III TOPGEAR trial were randomized to perioperative chemotherapy (ECF/ECX or FLOT) alone or perioperative chemotherapy plus preoperative chemoradiotherapy (45 Gy in 25 fractions with concurrent fluoropyrimidine). In this exploratory analysis, treatment completion, grade ≥ 3 adverse events (CTCAE v3.0), surgical outcomes, overall survival (OS) and progression-free survival (PFS) were compared between older and younger adults. RESULTS: Of the 574 patients enrolled, 135 (24%) were ≥ 70 years. Older adults more frequently required preoperative chemotherapy dose reductions, omissions, or delays (chemoradiotherapy: 55% vs 35%, p = 0.004; chemotherapy: 60% vs 48%, p = 0.087). Rates of grade ≥ 3 adverse events were comparable between older and younger patients (chemoradiotherapy: 66% vs 67%, p = 0.874; chemotherapy: 68% vs 59%, p = 0.220), but older adults more often had hematologic toxicity and grade ≥ 3 diarrhea in the chemotherapy group (56% vs 37%, p = 0.006; 21% vs 6%, p < 0.001). Resection rates, grade 3/4 surgical complications, number of removed lymph nodes, and 30-/90-day mortality were similar by age. OS and PFS were comparable across age groups, with numerically favorable outcomes for older adults (OS: HR 0.86, 95% CI 0.58-1.26 [chemoradiotherapy]; HR 0.75, 95% CI 0.51-1.11 [chemotherapy]; PFS: HR 0.78, 95% CI 0.53-1.15 [chemoradiotherapy]; HR 0.70, 95% CI 0.47-1.03 [chemotherapy]). CONCLUSIONS: Older adults with gastric cancer achieved comparable oncologic outcomes to younger patients, despite more frequent treatment modifications and higher hematologic toxicity.

Humans↗

PubMed2026

The role of particle therapy in the treatment of locally recurrent rectal cancer: a systematic review.

BACKGROUND: Colorectal cancer is a common malignancy. Advancements in multimodality treatment have improved outcomes. About 2-10% of patients will have a local recurrence even after optimal treatment. Salvage surgical treatment is the treatment of choice, however, in posterior and lateral recurrences, surgery is linked to a high rate of treatment-related morbidity. Some recurrences remain unresectable even after neoadjuvant treatment. MATERIALS AND METHODS: A systematic literature review was performed to search for studies on curative-intent radiation therapy (RT) with photons, stereotactic body radiation therapy (SBRT) and particle beam therapy. The aim of the literature search was to define the role of particle therapy in the treatment of patients with unresectable or inoperable local recurrences of rectal cancer where neoadjuvant treatment is unlikely to result in downstaging, leaving patients with RT as the only curative treatment option. RESULTS: 32 studies which fulfil the criteria were identified. In general, SBRT and particle beam therapy permitted the application of significantly higher doses to the target without a concomitant increase in treatment-related toxicities. CONCLUSIONS: For unresectable and inoperable locally recurrent rectal cancer ablative radiotherapy techniques such as SBRT and particle beam therapy offer a curative treatment approach as an alternative to surgery. SBRT can be offered for small local and nodal recurrences, while particle beam therapy can be offered for larger recurrences and complex shapes spanning several anatomical compartments as well. Further research is needed to stratify patients according to their need and eligibility for the different possible modalities of curative-intent RT.

Humans↗

PubMed2026

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy↗

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 74·1 months (IQR 68·3-75·4). 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 0·84 [95% CI 0·79-0·88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11·6%) 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] 0·41-0·93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0·36-0·48), 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 (≥70·0%; mean absolute improvement 12·1 percentage points [SD 2·8]). 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<0·010). 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

A machine learning-derived and functionally validated circadian rhythm signature predicts clinical outcomes and in silico drug sensitivity in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) displays considerable heterogeneity in clinical outcomes, highlighting the need for reliable prognostic biomarkers. While the aberrant expression of circadian rhythm-related genes has been implicated in cancer pathogenesis, its comprehensive role in CRC progression and predicted therapeutic vulnerabilities remains inadequately characterized. METHODS: Bulk and single-cell RNA-sequencing data were integrated from multiple CRC cohorts. A circadian rhythm signature (CRS) was developed through machine learning algorithms and validated for prognostic value. Comprehensive analyses of tumor microenvironment, genomic alterations, and drug sensitivity were performed. Furthermore, the biological function of the core gene, BHLHE40, was validated in CRC cell lines through CCK-8, EdU, and wound healing assays. RESULTS: Single-cell analysis demonstrated an elevated expression signature of circadian rhythm-related genes in dendritic cells. The optimized CRS, comprising 14 circadian rhythm-related genes, successfully categorized patients into high- and low-risk groups. Patients with a high CRS showed markedly poorer overall survival and computationally inferred immunosuppressive features, including reduced CD8+ T cell infiltration and increased M2 macrophage polarization. Genomic analysis revealed enhanced mutation burden in TP53 and alterations in RTK-RAS/WNT pathways. Notably, in vitro assays confirmed that BHLHE40 is significantly overexpressed in CRC cells. Knockdown of BHLHE40 markedly inhibited tumor cell proliferation and migration. Drug sensitivity profiling identified bexarotene and SMER-3 as potential therapeutic options for high-CRS patients. A nomogram integrating CRS with clinical parameters demonstrated superior predictive accuracy for 1-, 3-, and 5-year survival. CONCLUSIONS: The CRS represents a promising prognostic biomarker that reflects tumor immune status and genomic features, providing valuable insights for personalized treatment strategies in CRC.

Circadian rhythm↗

PubMed2026

Lactylation-related immune-metabolic dysregulation defines prognostic and therapeutic stratification in lung adenocarcinoma.

BACKGROUND: Lactylation links lactate metabolism with inflammatory signaling and immune regulation in tumors. However, its cellular distribution and translational value in lung adenocarcinoma (LUAD) remain unclear. METHODS: Single-cell RNA-sequencing datasets GSE189357 and GSE171145 were integrated to characterize lactylation-related activity, intercellular communication, and malignant epithelial cell states in LUAD. Single-cell-derived lactylation-related differentially expressed genes were mapped to TCGA-LUAD and multiple GEO cohorts. Univariate Cox regression and machine learning algorithms were used to construct a lactylation-related prognostic signature (LRPS). The associations of LRPS with prognosis, immunotherapy response, drug sensitivity, genomic alterations, immune infiltration, and inflammation- and metabolism-related pathways were evaluated. KRT7 was further validated using virtual knockout analysis, spatial transcriptomics, and in vitro and in vivo experiments. RESULTS: lactylation-related transcriptional activity showed heterogeneous distribution across LUAD cell populations and was associated with altered cell-cell communication. In malignant epithelial cells, LRTS-high and LRTS-low states exhibited distinct metabolic, inflammatory, and tumor-related pathway activities. LRPS showed stable prognostic performance in TCGA-LUAD and multiple GEO cohorts and remained an independent prognostic factor. Low LRPS was associated with greater potential benefit from immunotherapy, whereas different LRPS groups displayed distinct drug sensitivity, genomic alteration, and immune microenvironment patterns. KRT7 was highly expressed in LUAD and associated with poor prognosis. KRT7 knockdown suppressed LUAD cell proliferation, migration, invasion, colony formation, and tumor growth in vivo. CONCLUSIONS: This study identifies lactylation-related immune-metabolic dysregulation as a clinically relevant feature of LUAD and develops a single-cell-guided LRPS for prognosis and therapeutic stratification. KRT7 emerged as an LRPS-related functional candidate with experimentally supported roles in malignant LUAD phenotypes.

Immunotherapy↗