tbuckley/cabot-search huggingface dataset:
Whole genome sequencing and the genetics of extramedullary disease in multiple myeloma
Authors: Nicholas Bingham, Jaynish Shah, Daniel Wong, Sueh-li Lim, Krystal Bergin, Anna Kalff, Antonia Reale, Tiffany Khong, Sridurga Mithraprabhu, Andrew Spencer
Journal: Blood Cancer Journal (2025)

Dear Editor,Extramedullary disease (EMD) in multiple myeloma (MM) affects up to 20% of patients throughout the disease course [1].It is associated with poor outcomes due to aggressive disease kinetics and therapy resistance, but the biology remains relatively unknown [2,3].EMD is variably defined, but two major subtypes exist: extraosseous EMD arising from bone and extending into surrounding tissue, and true EMD arising by haematogenous spread, which is associated with the worst outcomes [2, 3].To describe the genetic landscape of haematogenous-spread EMD, we performed whole genome sequencing of extramedullary tumours from 15 patients; three patients had multiple biopsies.Patient samples were collected after written consent was obtained.Tumour DNA was obtained from two cohorts: fresh biopsies (n = 8; QIAGEN DNeasy Blood & Tissue Kit) and formalin-fixed, paraffin-embedded (FFPE) historical samples (n = 8; Roche High Pure FFPET DNA isolation Kit).Germline DNA was obtained from buccal swabs or stored autologous stem cells.Library preparation was optimised for DNA from FFPE samples using IDT® xGen PRISM DNA library preparation kit.Sequencing was performed on an Illumina NovaSeq® by the Australian Genome Research Facility.Briefly, bioinformatics utilised BWA-MEM, the GATK Mutect2, CNVpytor, Manta, Accucopy, SigProfilerMatrixGenerator, mmSig and FFPEsig.Liquid biopsy of circulating tumour DNA (ctDNA) utilised QX200 droplet digital PCR system (Bio-Rad®).See supplementary material for detailed methods.Patient data is shown in Table 1.The median age at MM diagnosis was 52 years.Two cases of primary EMD were included.There was no unifying genetic event in EMD.The median number of small nucleotide variants (SNV) was 18,819 mutations per sample across the whole genome, with no difference between fresh and FFPE samples, although this is impacted by two highly mutated fresh samples (Fig. 1A).The median number of SNV was increased compared to published data for MGUS, newly diagnosed MM (NDMM) and relapsed/ refractory MM (RRMM) (3406, 5483 and 10,938, respectively [4, 5]; Fig. 1B).Three samples were hypermutated, defined as total SNV above the upper limit of the interquartile range.Of 137 published driver genes [6][7][8][9] in MM, a median of 3 were mutated per EMD tumour (Fig. 1C).This is compared to 2 in NDMM [7], but clear data for comparison is lacking in RRMM.Twenty-three genes were mutated in 3 or more patients, with oncogenicity assessment using intOGen [10] noting driver genes as NRAS, KRAS, BRAF and TP53 (Fig. 1D).We identified MAPKactivating mutations in NRAS, KRAS and BRAF in 80% of patients, and importantly all were present at clonal cancer fractions of >0.9.The RAS mutations almost exclusively impacted codon 61.
Unsupervised deep learning of electrocardiograms enables scalable human disease profiling
Authors: Sam F. Friedman, Shaan Khurshid, Rachael A. Venn, Xin Wang, Nate Diamant, Paolo Di Achille, Lu-Chen Weng, Seung Hoan Choi, Christopher Reeder, James P. Pirruccello, Pulkit Singh, Emily S. Lau, Anthony Philippakis, Christopher D. Anderson, Mahnaz Maddah, Puneet Batra, Patrick T. Ellinor, Jennifer E. Ho, Steven A. Lubitz
Journal: npj Digital Medicine (2025)

The 12-lead electrocardiogram (ECG) is inexpensive and widely available. Whether conditions across the human disease landscape can be detected using the ECG is unclear. We developed a deep learning denoising autoencoder and systematically evaluated associations between ECG encodings and ~1,600 Phecode-based diseases in three datasets separate from model development, and meta-analyzed the results. The latent space ECG model identified associations with 645 prevalent and 606 incident Phecodes. Associations were most enriched in the circulatory (n = 140, 82% of category-specific Phecodes), respiratory (n = 53, 62%) and endocrine/metabolic (n = 73, 45%) categories, with additional associations across the phenome. The strongest ECG association was with hypertension (p < 2.2×10-308). The ECG latent space model demonstrated more associations than models using standard ECG intervals, and offered favorable discrimination of prevalent disease compared to models comprising age, sex, and race. We further demonstrate how latent space models can be used to generate disease-specific ECG waveforms and facilitate individual disease profiling.
Early assessment of IL8 and PD1+ Treg predicts response and guides treatment monitoring in cemiplimab-treated cutaneous squamous cell carcinoma
Authors: Daniela Esposito, Fabiana Napolitano, Daniela Claudia Maresca, Marcella Scala, Annarita Amato, Stefania Belli, Claudia Maria Ascione, Angela Vallefuoco, Giovanna Attanasio, Fabio Somma, Angela Ianaro, Daniela Russo, Silvia Varricchio, Massimo Mascolo, Claudia Costa, Alessia Villani, Massimiliano Scalvenzi, Gianfranco Orlandino, Teresa Troiani, Alberto Servetto, Roberto Bianco, Giuseppe Ercolano, Luigi Formisano
Journal: Journal for ImmunoTherapy of Cancer (2025)

Anti-programmed cell death 1 (PD1) is the first-choice treatment in patients with advanced cutaneous squamous cell carcinoma (cSCC), when curative options are unavailable. However, reliable biomarkers for patient selection are still lacking. In this translational study, clinical annotations, tissue and liquid biopsies were acquired to investigate the association between sustained objective responses and transcriptional profiles, immune cell dynamics in tumor tissue and peripheral blood samples, as well as circulating cytokine levels. First, we investigated the baseline characteristics of the immune landscape of cSCC biopsies. Gene Set Enrichment Analysis showed upregulation of interleukin (IL)2/STAT5 pathways and downregulation of Interferon signatures in non-responder patients compared with responders. Next, we studied the early changes induced by cemiplimab in tissue biopsies. Notably, after only three weeks, cemiplimab treatment induced an increase in B cells and CD8+ T cells in responders, whereas their abundance decreased in non-responder patients. Moreover, analyzing differentially expressed genes modulated early during treatment, compared with baseline biopsies, we found that IL1β and IL8 exhibited early downregulation in responder patients' tumor specimens. We assessed whether changes in the local tumor microenvironment were mirrored in peripheral blood. Similar to tissue findings, no changes were observed in the whole T regulatory (Treg) population, although PD1+ Tregs, which were downregulated in responder patients (vs T0), showed a rebound enrichment in non-responders after three cycles of cemiplimab. Finally, IL8 mirrored the tissue results, unlike IL1β, with early (T1) and then sustained (T3) downregulation of its levels in responder patients, while increased in non-responders. Taken together, these findings shed light on the significance of early transcriptomic and immune cell modulation in predicting responses to cemiplimab therapy. Additionally, our data suggest that IL8 levels in peripheral blood offer promising avenues for personalized treatment selection and response assessment in patients with cSCC receiving cemiplimab, while PD1+Tregs can be followed longitudinally to monitor response to therapy.
HDAC and MEK inhibition synergistically suppresses HOXC6 and enhances PD-1 blockade efficacy in BRAF<sup>V600E</sup>-mutant microsatellite stable colorectal cancer
Authors: Zhuang Sun, Mengyuan Shi, Jinhong Xia, Xin Li, Nan Chen, Hanyang Wang, Zhaoya Gao, Jinying Jia, Peng Yang, Dengbo Ji, Jin Gu
Journal: Journal for ImmunoTherapy of Cancer (2025)

B-Raf proto-oncogene, serine/threonine kinase (BRAF)V600E-mutant microsatellite stable (MSS) colorectal cancer (CRC) constitutes a distinct CRC subgroup, traditionally perceived as minimally responsive to standard therapies. Recent clinical attempts, such as BRAF inhibitors (BRAFi) monotherapy and combining BRAFi with other inhibitors, have yielded unsatisfactory efficacy. This study aims to identify a novel therapeutic strategy for this challenging subgroup. We first performed a large-scale drug screening using patient-derived organoid models and cell lines to pinpoint potential therapies. Subsequently, we investigated the synergistic effects of identified effective inhibitors and probed their cooperative mechanisms. Concurrently, we explored the immune characteristics of BRAFV600E MSS CRC using RNA sequencing and multiplex immunohistochemistry. Finally, we established a CT26 BRAFV637E mouse cell line and validated the efficacy of combining these inhibitors and programmed death 1 (PD-1) blockades in immunocompetent mice. Drug screening identified histone deacetylase (HDAC) inhibitor and mitogen-activated protein kinase kinase (MEK) inhibitor as significantly effective against BRAFV600E MSS CRC. Further research revealed that these two inhibitors have superior synergistic effects by comprehensively inhibiting the activation of the epidermal growth factor receptor, mitogen-activated protein kinase, and phosphoinositide 3-kinase-protein kinase B pathways and suppressing the key target homeobox C6 (HOXC6). HOXC6, overexpressed in BRAFV600E MSS CRC, regulates the MYC gene and contributes to treatment resistance, tumor growth, and metastasis. Moreover, the combination therapy demonstrated the ability to enhance antitumor immunity by synergistically upregulating the expression of immune activation-related genes, activating the cyclic guanosine monophosphate-adenosine monophosphate synthase/stimulator of interferon genes (cGAS/STING) pathway, and diminishing the tumor cells' DNA mismatch repair capacity. Notably, BRAFV600E MSS CRC was identified to exhibit a distinct immune microenvironment with increased PD-1+ cell infiltration and potential responsiveness to immunotherapy. Echoing the above findings, in vivo, HDAC and MEK inhibitors significantly improved PD-1 blockade efficacy, accompanied by increased CD8+ T-cell infiltration. Our findings indicate that combining HDAC inhibitor, MEK inhibitor, and PD-1 blockade is a potential strategy for treating BRAFV600E-mutant MSS CRC, warranting further investigation in clinical settings.
Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics
Authors: Johnathan Arnon, Gal Dinstag, Omer Tirosh, Leon Gugel, Yaron Kinar, Tzivia Gottlieb, Anna Elia, Yakir Rottenberg, Hovav Nechushtan, Michael Tabi, Philip Blumenfeld, Eli Pikarsky, Tuvik Beker, Ranit Aharonov, Aron Popovtzer
Journal: Journal for ImmunoTherapy of Cancer (2025)

Introduction Immune checkpoint inhibitors (ICI) have improved outcomes in non-small cell lung cancer (NSCLC). Nevertheless, the clinical benefit of ICI as monotherapy or in combination with chemotherapy remains widely varied and existing biomarkers have limited predictive value. We present an analysis of ENLIGHT-DP, a novel transcriptome-based biomarker directly from histopathology slides, in patients with lung adenocarcinoma (LUAD) treated with ICI and platinum-based chemotherapy. Methods We retrospectively scanned high-resolution H&amp;E slides from pretreatment tumor-tissue samples of 50 patients with metastatic LUAD treated with first-line ICI with (46) or without (4) platinum-based chemotherapy and applied our ENLIGHT-DP pipeline to generate, in a blinded manner, an individual prediction score. ENLIGHT-DP predicts response to ICI and targeted therapies given H&amp;E slide scans in two steps: (1) predict individual messenger RNA expression directly from high-resolution H&amp;E scanned slides using DeepPT, a digital-pathology-based algorithm. (2) Use these values as input to ENLIGHT, a transcriptome-based platform that predicts response to ICI and targeted therapies derived from drug-specific networks of gene expressions. We then unblinded the clinical outcomes and evaluated the predictive value of ENLIGHT-DP in comparison to programmed death ligand (PD-L)-1 and tumor mutational burden (TMB). Results ENLIGHT-DP is predictive of response to treatment with receiver operating characteristic (ROC) area under the curve (AUC) of 0.69 (p=0.01) and outperforms both TMB and PD-L1 expression with ROC AUC of 0.52 and 0.46, respectively. Using a predetermined binary cut-off (established on independent cohorts) for patients predicted to respond to ICI, ENLIGHT-DP achieves 100% positive predictive value (PPV) and 44% sensitivity, superior to both PD-L1&gt;50% (65% PPV and 38% sensitivity) and TMB-high (82% PPV and 26% sensitivity). ENLIGHT-DP was highly predictive in PD-L1&lt;1% and TMB-low outlier groups with ROC AUC of 0.88 and 0.80, respectively (p value&lt;0.05). ENLIGHT-DP is the only biomarker in this cohort significantly correlated with progression-free survival (HR: 0.45, 95% CI: 0.2 to 0.99, p=0.048). Conclusion We demonstrate the application of ENLIGHT-DP, a transcriptome-based biomarker for accurate prediction of treatment of LUAD with ICI and platinum-based chemotherapy, outperforming PD-L1 and TMB, and relying solely on accessible H&amp;E scanned slides. Further studies on different tumor types, ICI monotherapy and bigger NSCLC cohorts are warranted.
Utilization of primary tumor samples for cancer neoantigen discovery
Authors: Vid Leko, Eric Groh, Shoshana T Levi, Amy R Copeland, Bradley Sinclair White, Billel Gasmi, Yong Li, Victoria Hill, Devikala Gurusamy, Noam Levin, Sanghyun Peter Kim, Sivasish Sindiri, Jared J Gartner, Todd D Prickett, Maria Parkhust, Frank J Lowery, Stephanie L Goff, Steven A Rosenberg, Paul Robbins
Journal: Journal for ImmunoTherapy of Cancer (2025)

Background The use of tumor-infiltrating T lymphocytes (TIL) that recognize cancer neoantigens has led to lasting remissions in metastatic melanoma and certain cases of metastatic epithelial cancer. For the treatment of the latter, selecting cells for therapy typically involves laborious screening of TIL for recognition of autologous tumor-specific mutations, detected through next-generation sequencing of freshly resected metastatic tumors. Our study explored the feasibility of using archived formalin-fixed, paraffin-embedded (FFPE) primary tumor samples for cancer neoantigen discovery, to potentially expedite this process and reduce the need for resections normally required for tumor sequencing. Method Whole-exome sequencing was conducted on matched primary and metastatic colorectal cancer samples from 22 patients. The distribution of metastatic tumor mutations that were confirmed as neoantigens through cognate TIL screening was evaluated in the corresponding primary tumors. Mutations unique to primary tumors were screened for recognition by metastasis-derived TIL and circulating T lymphocytes. Results We found that 25 (65.8%) of the 38 validated neoantigens identified in metastatic tumors from 18 patients with colorectal cancer were also present in matched primary tumor samples. This included all 12 neoantigens encoded by putative cancer driver genes, which are generally regarded as superior targets for adoptive cell therapy. The detection rate for other neoantigens, representing mutations without an established role in cancer biology, was 50% (13/26). Gene products encoding neoantigens detected in the primary tumors were not more likely to be clonal or broadly distributed among the analyzed metastatic lesions compared with those undetected in the primary tumors. Additionally, we found that mutations detected only in primary tumor samples did not elicit recognition by metastatic tumor-derived TIL but could elicit specific recognition by the autologous circulating memory T cells. Conclusions Our findings indicate that primary FFPE tumor-derived screening libraries could be used to discover most neoantigens present in metastatic tumors requiring treatment. Furthermore, this approach can reveal additional neoantigens not present in resected metastatic tumors, prompting further research to understand their clinical relevance as potential therapeutic targets.
Cognitive Behavioral Therapy for Insomnia across the Spectrum of Alcohol Use Disorder: A Systematic Review and Meta-Analysis
Authors: Cagdas Türkmen, Carlotta L Schneider, Wolfgang Viechtbauer, Ingeborg Bolstad, Subhajit Chakravorty, Mary Beth Miller, Håvard Kallestad, Guro W Angenete, Anna F Johann, Bernd Feige, Kai Spiegelhalder, Dieter Riemann, Øystein Vedaa, Ståle Pallesen, Elisabeth Hertenstein
Journal: Sleep Medicine Reviews (2025)
Radiomics signature for dynamic monitoring of tumor inflamed microenvironment and immunotherapy response prediction
Authors: Kinga Bernatowicz, Ramon Amat, Olivia Prior, Joan Frigola, Marta Ligero, Francesco Grussu, Christina Zatse, Garazi Serna, Paolo Nuciforo, Rodrigo Toledo, Manel Escobar, Elena Garralda, Enriqueta Felip, Raquel Perez-Lopez
Journal: Journal for ImmunoTherapy of Cancer (2025)

The efficacy of immune checkpoint inhibitors (ICIs) depends on the tumor immune microenvironment (TIME), with a preference for a T cell-inflamed TIME. However, challenges in tissue-based assessments via biopsies have triggered the exploration of non-invasive alternatives, such as radiomics, to comprehensively evaluate TIME across diverse cancers. To address these challenges, we develop an ICI response signature by integrating radiomics with T cell-inflamed gene-expression profiles. We conducted a pan-cancer investigation into the utility of radiomics for TIME assessment, including 1360 tumors from 428 patients. Leveraging contrast-enhanced CT images, we characterized TIME through RNA gene expression analysis, using the T cell-inflamed gene expression signature. Subsequently, a pan-cancer CT-radiomic signature predicting inflamed TIME (CT-TIME) was developed and externally validated. Machine learning was employed to select robust radiomic features and predict inflamed TIME. The study also integrated independent cohorts with longitudinal CT images, baseline biopsies, and comprehensive immunohistochemistry panel evaluation to assess the pan-cancer biological associations, spatiotemporal landscape and clinical utility of the CT-TIME. The CT-TIME signature, comprising four radiomic features linked to a T-cell inflamed microenvironment, demonstrated robust performance with AUCs (95% CI) of 0.85 (0.73 to 0.96) (training) and 0.78 (0.65 to 0.92) (external validation). CT-TIME scores exhibited positive correlations with CD3, CD8, and CD163 expression. Intrapatient analysis revealed considerable heterogeneity in TIME between tumors, which could not be assessed using biopsies. Evaluation of aggregated per-patient CT-TIME scores highlighted its promising clinical utility for dynamically assessing the immune microenvironment and predicting immunotherapy response across diverse scenarios in advanced cancer. Despite demonstrating progression disease at the first follow-up, patients within the inflamed status group, identified by CT-TIME, exhibited significantly prolonged progression-free survival (PFS), with some surpassing 5 months, suggesting a potential phenomenon of pseudoprogression. Cox models using aggregated CT-TIME scores from baseline images revealed a statistically significant reduction in the risk of PFS in the pan-cancer cohort (HR 0.62, 95% CI 0.44 to 0.88, p=0.007), and Kaplan-Meier analysis further confirmed substantial differences in PFS between patients with inflamed and uninflamed status (log-rank test p=0.009). The signature holds promise for impacting clinical decision-making, pan-cancer patient stratification, and treatment outcomes in immune checkpoint therapies.
MAF1 inhibits hepatocarcinogenesis by fostering an immunostimulatory tumor microenvironment
Authors: Di Cao, Yue-Ning Wang, Chao-Yue Sun, Haojiang Li, Ge Ren, Yu-Feng Zhou, Mei-Yin Zhang, Shuo-Cheng Wang, Shi-Juan Mai, Hui-Yun Wang
Journal: Journal for ImmunoTherapy of Cancer (2025)

Background The biological significance of MAF1, a tumor suppressor, in carcinogenesis and immune response of hepatocellular carcinoma (HCC) remains unreported. Understanding the underlying mechanisms by which MAF1 enhances anti-tumor immunity in HCC is crucial for developing novel immunotherapy strategies and enhancing clinical responses to treatment for patients with HCC. Methods Mice were subjected to hydrodynamic tail vein injections of transposon vectors to overexpress AKT/NRas, or c-Myc, with or without wild-type (WT) or mutant-activated (−4A) MAF1, or short-hairpin MAF1 (shMAF1). Liver tissues and tumors were harvested and analyzed using histology, immunohistochemistry, immunoblotting, quantitative reverse-transcription PCR, and flow cytometry. MAF1 was overexpressed or knocked down in HCC cells via lentiviral transfection. Cell lines were analyzed using RNA sequencing, immunoblotting, dual luciferase reporter, and chromatin precipitation assays. Results Both MAF1-WT and MAF1-4A proteins significantly inhibit hepatocarcinogenesis in mice, with the mutant form exhibiting a stronger suppressive effect. Although MAF1 knockdown alone does not induce abnormalities in the mouse liver, it accelerates c-Myc-induced carcinogenesis. Our results provide the first in vivo evidence that MAF1 plays a tumor suppressor role by activating PTEN to suppress the AKT-mammalian target of rapamycin signaling pathway during hepatocarcinogenesis in physiologically relevant tumor models. More importantly, we found that MAF1 not only enhances the intratumoral infiltration of CD8 + T cells by increasing CXCL10 secretion but also enhances their functional activity by inhibiting PDL1 transcription in mouse liver cancer, which were confirmed in human HCC or in vitro experiments. Furthermore, PDL1 overexpression accelerates mouse hepatocarcinogenesis by antagonizing the tumor-suppressive role of MAF1. Conclusions Our study uncovers a novel anti-tumor immunity of MAF1 in hepatocarcinogenesis and human HCC. These findings suggest that the stimulated MAF1 could potentially improve immunotherapy in combination with immune checkpoint inhibitors in HCC patients, especially in those with an absence of T cells in HCC tissues.