Conserved pan-cancer microenvironment subtypes predict response to immunotherapy

Immune infiltration landscape and potential drug-targeted implications for hepatocellular carcinoma with 'progression/hyper-progression' recurrence

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) recurrence was previously characterized into four types, and patients with progression/hyper-progression recurrence (type III-IV) have an extremely poor prognosis. However, the immune background of resectable HCC, particularly in patients who experience recurrence, remains underexplored. Therefore, this study aimed to describe the immune landscape of resectable HCC, especially postoperative type III-IV recurrent HCC, and explore potential immune-targeted anti-relapse strategies for treated populations.

METHODS

The differences in gene expression in patients with recurrent HCC (type I-II (solitary or multi-intrahepatic oligo recurrence) vs. type III-IV) were investigated using bulk sequencing. Multiple immune infiltration methods (single-sample gene set enrichment analysis (GSEA), Microenvironment Cell Populations-counter and ESTIMATE) were used, and patients were divided into four groups to identify four distinct immune subtypes: immune-enrichment/matrix-poor (IE1), immune-enrichment/matrix-rich (IE2), immune intermediate/matrix-rich (ITM) and immune desert/matrix-poor (ID). Co-expression and protein interaction analyses were used to identify characteristic genes in ITM closely associated with type III-IV recurrence, which was matched with drug targets for Huaier granules (HG) and lenvatinib. Virtual docking was used to identify potential therapeutic targets, and the results were verified using single-nuclei RNA sequencing and histological analysis.

RESULTS

ITM was closely related to type III-IV recurrence and exhibited immunotherapy potential. The potential efficacy of inhibiting CCNA2, VEGFA, CXCL8, PLK2, TIMP1, ITGB2, ALDOA, ANXA5 and CSK in ITM reversal was determined. Molecular docking demonstrated that the proteins of these genes could bind to HG or lenvatinib. The immunohistochemical findings demonstrated differential VEGFA (p < .01) and PLK2 (p < .001) expression in ITM type and ID in type III-IV recurrent HCC.

CONCLUSIONS

Three primary immunotypes of resectable HCC (IE2, ITM and ID) were identified, and HG and lenvatinib could potentially overcome immune checkpoint blockade (ICB) resistance in ITM patients with HCC, particularly those classified as type III-IV.

Mapping the rapid growth of multi-omics in tumor immunotherapy: Bibliometric evidence of technology convergence and paradigm shifts

This study aims to fill the knowledge gap in systematically mapping the evolution of omics-driven tumor immunotherapy research through a bibliometric lens. While omics technologies (genomics, transcriptomics, proteomics, metabolomics)provide multidimensional molecular profiling, their synergistic potential with immunotherapy remains underexplored in large-scale trend analyses. A comprehensive search was conducted using the Web of Science Core Collection for literature related to omics in tumor immunotherapy, up to August 2024. Bibliometric analyses, conducted using R version 4.3.3, VOSviewer 1.6.20, and Citespace 6.2, examined publication trends, country and institutional contributions, journal distributions, keyword co-occurrence, and citation bursts. This analysis of 9,494 publications demonstrates rapid growth in omics-driven tumor immunotherapy research since 2019, with China leading in output (63% of articles) yet exhibiting limited multinational collaboration (7.9% vs. the UK's 61.8%). Keyword co-occurrence and citation burst analyses reveal evolving frontiers: early emphasis on "PD-1/CTLA-4 blockade" has transitioned toward "machine learning," "multi-omics," and "lncRNA," reflecting a shift to predictive modeling and biomarker discovery. Multi-omics integration has facilitated the development of immune infiltration-based prognostic models, such as TIME subtypes, which have been validated across multiple tumor types, which inform clinical trial design (e.g. NCT06833723). Additionally, proteomic analysis of melanoma patients suggests that metabolic biomarkers, particularly oxidative phosphorylation and lipid metabolism, may stratify responders to PD-1 blockade therapy. Moreover, spatial omics has confirmed ENPP1 as a potential novel therapeutic target in Ewing sarcoma. Citation trends underscore clinical translation, particularly mutation-guided therapies. Omics technologies are transforming tumor immunotherapy by enhancing biomarker discovery and improving therapeutic predictions. Future advancements will necessitate longitudinal omics monitoring, AI-driven multi-omics integration, and international collaboration to accelerate clinical translation. This study presents a systematic framework for exploring emerging research frontiers and offers insights for optimizing precision-driven immunotherapy.

Organelle-oriented nanomedicines in tumor therapy: Targeting, escaping, or collaborating?

Precise tumor therapy is essential for improving treatment specificity, enhancing efficacy, and minimizing side effects. Targeting organelles is a key strategy for achieving this goal and is a frontier research area attracting a considerable amount of attention. The concept of organelle targeting has a significant effect on the structural design of the nanodrugs employed. Most notably, the intricate interactions among different organelles in a tumor cell essentially create a unified system. Unfortunately, this aspect might have been somewhat overlooked when existing organelle-targeting nanodrugs were designed. In this review, we underscore the synergistic relationship among the various organelles and advocate for a holistic view of organelle-targeting design. Through the integration of biology and material science, recent advancements in organelle targeting, escaping, and collaborating are consolidated to offer fresh perspectives for the development of antitumor nanomedicines.

Pan-cancer analysis identifies EIPR1 as a potential prognostic and immunological biomarker for lung adenocarcinoma and its functional validation

BACKGROUND

EARP and GARP complex-interacting protein 1 (EIPR1) may be a new oncogene in tumors, influencing the prognosis and invasion of cancer. However, a systematic analysis of the function of EIPR1 in various cancers remains vacant. Thus, we proceeded with a comprehensive analysis to ascertain the role of EIPR1 among various cancers.

METHODS

We explored EIPR1 expression in pan-cancer, and its association with clinical stage, survival, gene mutations and methylation by the TIMER 2.0, GEPIA2, cBioPortal, and UALCAN. The protein-protein interaction (PPI) network, immune infiltration, and immune checkpoint assessments of EIPR1 was performed using the STRING and SangerBox. The role of EIPR1 expression in lung adenocarcinoma (LUAD) was explored by the R software. The impact of EIPR1 expression on LUAD progression was studied through in vitro assays.

RESULTS

EIPR1 was overexpressed in most cancers and revealed as a potential prognostic biomarker in tumors, involving in tumorigenesis by affecting its methylation and gene mutations. The immune infiltration and immune checkpoints of tumors were related to the expression of EIPR1. Additionally, EIPR1 expression affected the survival, diagnosis, clinicopathological features, tumor microenvironment, and drug sensitivity of LUAD patients. Validation studies demonstrated that EIPR1 knockdown suppressed the malignant growth, invasion, and migration of LUAD cells.

CONCLUSIONS

This study delivers an extensive landscape for the oncogenesis and immunological characteristics of EIPR1, which reveals that EIPR1 may serve as a potential biological target for future prognosis and immune treatment in tumors, especially in LUAD.

Systemic inflammation in response to radiation drives the genesis of an immunosuppressed tumor microenvironment

The composition of the tumor immune microenvironment has become a major determinant of response to therapy, particularly immunotherapy. Clinically, a tumor microenvironment lacking lymphocytes, so-called "cold" tumors, are considered poor candidates for immune checkpoint inhibition. In this review, we describe the diversity of the tumor immune microenvironment in breast cancer and how radiation exposure alters carcinogenesis. We review the development and use of a radiation-genetic mammary chimera model to clarify the mechanism by which radiation acts. Using the chimera model, we demonstrate that systemic inflammation elicited by a low dose of radiation is key to the construction of an immunosuppressive tumor microenvironment, resulting in aggressive, rapidly growing tumors lacking lymphocytes. Our experimental studies inform the non-mutagenic mechanisms by which radiation affects cancer and provide insight into the genesis of cold tumors.

The clinical-grade CBP/ p300 inhibitor CCS1477 represses the global NRF2-dependent cytoprotective transcription program and re-sensitizes cancer cells to chemotherapeutic drugs

Constitutive activation of NRF2 provides a selective advantage to malignant tumour clones through the hijacking of the NRF2-dependent cytoprotective transcriptional program, which allows the cancer cells to survive and thrive in the chemically stressful tumour niche, whilst also providing resistance to anti-cancer drugs due to the upregulation of xenobiotic metabolizing enzymes and drug efflux pumps. Through a small-molecule epigenetic screen carried out in KEAP1 mutant lung cancer cells, in this study, we identified CCS1477 (Inobrodib) to be an inhibitor of the global NRF2-dependent transcription program. Mechanistically, CCS1477 is able to repress NRF2's cytoprotective response through the inhibition of its obligate transcriptional activator partner CBP/p300. Importantly, in addition to repressing NRF2-dependent anti-oxidative stress and xenobiotic metabolizing enzyme gene expression, CCS1477 treatment is also able to reverse the chemoresistance phenotype and re-sensitize NRF2-activated tumour cells to anti-cancer drugs. Furthermore, in co-culture experiments of KEAP1 mutant cancer cells with primary human T cells, CCS1477 treatment suppressed the acquisition of the T cell exhaustion transcriptional state, which should function to augment the anti-cancer immune response. Thus, CCS1477-mediated inhibition of CBP/p300 represents a novel therapeutic strategy with which to target the currently untreatable tumours with aberrant NRF2 activation.

Stimuli-responsive polymer-dasatinib prodrug to reprogram cancer-associated fibroblasts for boosted immunotherapy

The barriers from cancer-associated fibroblasts (CAFs) have diminished the clinical efficacy of immunotherapy for triple-negative breast cancer (TNBC). The obstacles from CAFs often result in poor drug penetration, constrained cytotoxic T lymphocyte infiltration, and an immunosuppressive microenvironment. Herein, chondroitin sulfate (CS) was engineered to conjugate dasatinib (DAS), a tyrosine kinase inhibitor, via the cathepsin B (CTSB)-responsive GFLG linker to produce CS-GFLG-DAS (CGD), which could be employed to reverse the CAF phenotype and regulate the biosynthesis of extracellular matrix (ECM), thus enhancing the efficacy of immune checkpoint blockade (ICB) therapy. Upon reaching the tumor site, DAS released from CGD in response to overexpressed CTSB in the tumor microenvironment could transform CAFs into a quiescent state instead of killing them to prevent CAFs from producing abundant ECM, thereby promoting deep penetration of CGD to effectively kill tumor cells. In addition, ECM remodeling facilitated tumor infiltration of cytotoxic T lymphocytes, synergistically enhancing the anti-PD-1 efficacy in the 4T1 tumor-bearing mice. In summary, this prodrug enhanced deep drug penetration and therapeutic sensitivity of anti-PD-1 by regulating CAFs, providing new insights into optimizing immunotherapy in treating fibrotic tumors via nanomedicine.

Therapeutic efficacy of TMTP1-modified EVs in overcoming bone metastasis and immune resistance in PIK3CA mutant NSCLC

Non-small cell lung cancer (NSCLC) with PIK3CA mutations demonstrates significant challenges in treatment due to enhanced bone metastasis and immune checkpoint resistance. This study investigates the efficacy of tumor-targeting peptide 1-modified cancer stem cell-derived extracellular vesicles (TMTP1-TSRP-EVs) in reshaping the tumor microenvironment and reversing immune checkpoint resistance in NSCLC. By integrating TMTP1-TSRP into EVs, we aim to specifically deliver therapeutic agents to NSCLC cells, focusing on inhibiting the PI3K/Akt/mTOR pathway, a crucial driver of oncogenic activity and immune evasion in PIK3CA-mutated cells. Our comprehensive in vitro and in vivo analyses show that TMTP1-TSRP-EVs significantly inhibit tumor growth, reduce PD-L1 expression, and enhance CD8+ T cell infiltration, effectively reversing the immune-suppressive microenvironment. Moreover, the in vivo models confirm that our approach not only suppresses bone metastases but also overcomes primary resistance to immune checkpoint inhibitors by modulating the expression of key immunological markers. These findings suggest that targeted delivery of TMTP1-TSRP-EVs could provide a novel therapeutic strategy for treating PIK3CA-mutant NSCLC, offering significant improvements over traditional therapies by directly targeting the molecular pathogenesis of tumor resistance and metastasis. Molecular Mechanisms Reshaping the TME to Halt PI3K-Mutant Bone Metastasis of NSCLC and Overcoming Primary ICI Resistance. (Created by BioRender).

GLI2 Facilitates Tumor Immune Evasion and Immunotherapeutic Resistance by Coordinating WNT and Prostaglandin Signaling

Therapeutic resistance to immune checkpoint blockade has been commonly linked to the process of mesenchymal transformation (MT) and remains a prevalent obstacle across many cancer types. An improved mechanistic understanding for MT-mediated immune evasion promises to lead to more effective combination therapeutic regimens. Herein, we identified the hedgehog transcription factor, GLI2, as a key node of tumor-mediated immune evasion and immunotherapy resistance during MT. GLI2 generated an immunotolerant tumor microenvironment through the upregulation of WNT ligand production and increased prostaglandin synthesis. This pathway drove the recruitment, viability, and function of granulocytic myeloid-derived suppressor cells while also impairing type I conventional dendritic cell, CD8+ T-cell, and NK cell functionality. Pharmacologic inhibition of EP2/EP4 prostaglandin receptor signaling or WNT ligand secretion each reversed a subset of the immunomodulatory effects of GLI2 and prevented primary and adaptive resistance to anti-PD-1 immunotherapy, respectively. A transcriptional GLI2 signature correlated with resistance to anti-PD-1 immunotherapy in patients with stage IV melanoma. Together, these findings provide a translational roadmap to direct combination immunotherapies in the clinic. Significance: WNT and prostaglandin signaling generate an immunotolerant environment in GLI2-active tumors and can be targeted as a component of immunotherapeutic combination strategies to overcome resistance in tumors exhibiting mesenchymal plasticity.

Perspectives on the role of "-Omics" in predicting response to immunotherapy

The annual Immuno-Oncology "Think Tank" held in October 2023 in Siena reviewed the rapidly evolving systems-biological approaches which are now providing a deeper understanding of tumor and tumor microenvironment heterogeneity. Based on this understanding opportunities for novel therapies may be identified to overcome resistance to immunotherapy. There is increasing evidence that malignant disease processes are not limited to purely intracellular or genetic events but constitute a dynamic interaction between the host and disease. Tumor responses are influenced by many host tissue determinants across different cellular compartments, which can now be investigated by high-throughput molecular profiling technologies, often labelled with a suffix "-omics". "Omics" together with ever increasing computational power, fast developments in machine learning, and high-resolution detection tools offer an unrivalled opportunity to connect high-dimensional data and create a holistic view of disease processes in cancer. This review describes advances in several state-of-the-art "-omics" approaches with perspectives on how these can be applied to the clinical development of new immunotherapeutic strategies and ultimately adopted in clinical practice.

Targeting JAML promotes normalization of tumour blood vessels to antagonize tumour progression via FAK/SRC and VEGF/VEGFR2 signalling pathways

BACKGROUND

Angiogenesis is a crucial process in tumour growth and metastasis. Junctional adhesion molecule-like protein (JAML) plays an important role in cancer proliferation; however, its expression and role in tumour angiogenesis remains unexplored.

METHODS

We collected colorectal cancer from Jinan Central Hospital, using immunofluorescence staining to confirm the expression of JAML in vascular endothelial cells of cancer and adjacent tissue. Then we used the endothelial-specific knockout of JAML mice and human umbilical vein endothelial cells (HUVECs) to clarify the role of JAML in vivo and in vitro.

RESULT

Our findings indicated a significant upregulation of JAML in vascular endothelial cells of colorectal cancer tissues compared to adjacent tissues. Endothelial-specific knockout of JAML effectively inhibited tumour growth through normalization of tumour blood vessels in multiple mice tumour models. The deletion of JAML in endothelial cells facilitated tumour vascular normalization, which was evident from increased pericyte coverage, vessel perfusion and T lymphocytes infiltration, decreased hypoxia, vessel density and leakage in tumour tissues. Further analysis showed that the phosphorylation of FAK/SRC/AKT/ERK pathway and VEGFR2 were suppressed in JAMLendo-/- mice with tumour.

CONCLUSION

This study concluded that JAML is specifically highly expressed in the vascular endothelial cells of tumour, promoting tumour progression by angiogenesis through the activation of the FAK/SRC/ERK/AKT pathway and VEGF/VEGFR2 pathway. JAML might be a new target for antiangiogenesis and provide valuable insights into the development of novel therapeutic approaches for cancer patients.

Tumor-infiltrated double-negative regulatory T cells predict outcome of T cell-based immunotherapy in nasopharyngeal carcinoma

Adoptive cell therapy (ACT) using tumor-infiltrating lymphocytes (TILs) has demonstrated clinical success in solid tumors. We analyze 47 TIL infusion products and 62 pretreatment tumor microenvironments (TMEs) from a randomized phase 2 clinical study of concurrent chemoradiotherapy plus TIL-ACT (NCT02421640). Using single-cell and bulk RNA sequencing along with flow cytometry, we identify 14 CD3+ T cell clusters within 26 TIL infusion products: 11 CD3+CD8+ TILs, 2 CD3+CD4+ TILs, and 1 CD3+CD8-CD4- double-negative (DN) TIL. (DN) TILs, significantly associated with poor TIL-ACT outcomes, exhibit an activated regulatory T cell-like phenotype and include two CD56+ and four CD56- subsets. Among them, CD56-KZF2+ (DN) TILs are predominantly suppressive. (DN) TILs inhibit CD8+ TIL expansion via Fas-FasL, transforming growth factor β (TGF-β), and interleukin (IL)-10 signaling. Distinct CD8+ T subsets differentially impact on TIL-ACT outcomes, while 9 baseline TME gene signatures and 14 intracellular T cell genes hold prognostic value. Our findings identify predictive TIL subsets and biomarkers for TIL-ACT outcomes.

Quantitatively defined stromal B cell aggregates are associated with response to checkpoint inhibitors in unresectable melanoma

Multiplex immunofluorescence (mIF) is a promising tool for immunotherapy biomarker discovery in melanoma and other solid tumors. mIF captures detailed phenotypic information of immune cells in the tumor microenvironment, as well as spatial data that can reveal biologically relevant interactions among cell types. Given the complexity of mIF data, the development of automated analysis pipelines is crucial for advancing biomarker discovery. In pre-treatment melanoma samples from 50 patients treated with immune checkpoint inhibitors (ICIs), a higher stromal B cell percentage is associated with the clinical benefit of ICI therapy. The automatic detection of B cell aggregates with DBSCAN, a novel application of a computer-aided machine learning algorithm, demonstrates the potential for enhanced accuracy compared to pathologist assessment of lymphoid aggregates. TCF1+ and LAG3- T cell subpopulations are enriched near stromal B cells, suggesting potential functional interactions. These analyses provide a roadmap for the further development of spatial immunotherapy biomarkers in melanoma and other diseases.

Transcriptome sequencing revealed that lymph node metastasis of papillary thyroid microcarcinoma is associated with high THBS4 expression and PDGFRA+ cancer-associated fibroblasts

Background

Cervical lymph node metastasis is a major factor influencing recurrence after surgery for papillary thyroid cancer. Molecular markers that can predict the presence of lymph node metastasis and assess the aggressiveness of papillary thyroid microcarcinoma (PTMC) remain poorly understood. The research question addressed whether specific genes, such as thrombospondin-4 (THBS4), could serve as predictive biomarkers for guiding surgical strategies, particularly in cases where current imaging modalities fail to detect LNM in the central region, and the decision for prophylactic central neck dissection remains controversial.

Methods

Transcriptome sequencing was employed to screen for differentially expressed genes and perform enrichment analysis. The study defined two groups of PTMC patients: LNM(n=50) and NLNM(n=50). 10 samples from each group were used for transcriptome sequencing. The expression of THBS4 was evaluated in both groups. Additionally, the correlation between THBS4 expression and cancer-associated fibroblasts (CAFs), specifically the PDGFRA+ inflammatory CAFs, was investigated to understand the stromal regulatory protein's role in PTMC aggressiveness.

Results

The analysis of sequencing data revealed that THBS4 expression was significantly higher in LNM PTMC compared to the NLNM group (Fold Change > 1.6 and P < 0.05). LNM PTMCs were also associated with a higher presence of PDGFRA+ inflammatory CAFs (P < 0.05), while no significant difference in the quantity of SMA+ myofibroblastic CAFs was observed between the two groups(P>0.05). Immunohistochemical analysis demonstrated increased THBS4(P < 0.01) and PDGFRA(P < 0.001) expression in LNM groups, while SMA staining showed no significant intergroup differences(P>0.05).

Conclusion

This study's findings indicate that THBS4 could be a potential biomarker for predicting the risk of lymph node metastasis in papillary thyroid microcarcinoma, thus potentially guiding more personalized surgical interventions. Further validation in larger patient cohorts and the interactions between THBS4 and CAFs are necessary.

AI-driven predictive biomarker discovery with contrastive learning to improve clinical trial outcomes

Modern clinical trials can capture tens of thousands of clinicogenomic measurements per individual. Discovering predictive biomarkers, as opposed to prognostic markers, remains challenging. To address this, we present a neural network framework based on contrastive learning-the Predictive Biomarker Modeling Framework (PBMF)-that explores potential predictive biomarkers in an automated, systematic, and unbiased manner. Applied retrospectively to real clinicogenomic datasets, particularly for immuno-oncology (IO) trials, our algorithm identifies biomarkers of IO-treated individuals who survive longer than those treated with other therapies. We demonstrate how our framework retrospectively contributes to a phase 3 clinical trial by uncovering a predictive, interpretable biomarker based solely on early study data. Patients identified with this predictive biomarker show a 15% improvement in survival risk compared to those in the original trial. The PBMF offers a general-purpose, rapid, and robust approach to inform biomarker strategy, providing actionable outcomes for clinical decision-making.

Determinants of Response to Sequential Pembrolizumab with Trastuzumab plus Platinum/5-FU in HER2-Positive Gastric Cancer: A Phase II Chemoimmunotherapy Trial

PURPOSE

Adding pembrolizumab to first-line fluoropyrimidine (5-FU)/platinum chemotherapy plus trastuzumab improves outcomes in advanced HER2+ gastroesophageal adenocarcinomas, but the benefit is largely confined to dual HER2+ and PD-L1+ patients. To assess the contributions of components, we conducted a phase II trial evaluating 5-FU/platinum/trastuzumab and added pembrolizumab in cycle 2 in patients with metastatic HER2+ disease.

PATIENTS AND METHODS

Treatment-naïve patients with advanced HER2+ gastroesophageal cancer underwent a baseline biopsy and received a single dose of 5-FU/platinum with trastuzumab followed by repeat biopsy. Pembrolizumab was added, and a third biopsy was performed after six cycles. The primary endpoint was the objective response rate. Secondary endpoints included progression-free and overall survival. Exploratory biomarker analysis and dynamic changes in HER2 and PD-L1 were prespecified.

RESULTS

Sixteen patients were enrolled. The objective response rate was 69%, and the median progression-free survival was 11.9 months. Serial whole-exome, single-cell RNA, T-cell receptor sequencing, and spatial transcriptomics from pretreatment and on-treatment samples revealed early trastuzumab-induced NK cell infiltration in HER2+ tumor beds and an increase in Fc receptor gamma III expression in macrophages, suggesting that trastuzumab directs Fc receptor-mediated antibody-dependent cytotoxicity. This favorable remodeling was enhanced by the addition of pembrolizumab, primarily in PD-L1+ samples. We observed TGF-β signaling in HER2-negative tumor regions, which was associated with nonresponder status.

CONCLUSIONS

These data highlight the biology of intratumoral heterogeneity and the impact of tumor and immune cell features on clinical outcomes and may partly explain the lesser magnitude of pembrolizumab benefit in HER2+ and PD-L1-negative subgroups.

Proteogenomic Characterization of High-Grade Lung Neuroendocrine Carcinoma Deciphers Molecular Diversity and Potential Biomarkers of Different Histological Subtypes in Chinese Population

High-grade lung neuroendocrine carcinomas (Lu-NECs) are clinically refractory malignancies with poor prognosis and limited therapeutic advances. The biological and molecular features underlying the histological heterogeneity of Lu-NECs are not fully understood. In this study, we present a multi-omics integration of whole-exome sequencing and deep proteomic profiling in 93 Chinese Lu-NECs to establish the first comprehensive proteogenomic atlas of this disease spectrum. Our analyses revealed a high degree of mutational concordance among the subtypes at the genomic level; however, distinct proteomic profiles enabled a clear differentiation of histological subtypes, unveiling subtype-specific molecular and biological features related to tumor metabolism, immunity, and proliferation. Furthermore, RB1 mutations confer divergent prognostic effects through subtype-specific cis- and trans-proteomic regulation. In addition, we identified potential protein biomarkers for histological subtype classification and risk stratification, which were validated by immunohistochemistry in an independent cohort. This study provides a valuable proteogenomic resource and insight into Lu-NEC heterogeneity.

Navigating established and emerging biomarkers for immune checkpoint inhibitor therapy

Immune checkpoint inhibitors (ICIs) have improved outcomes of patients with many different cancers. These antibodies target molecules such as programmed cell death 1 (PD-1) or cytotoxic T lymphocyte associated protein 4 (CTLA-4) which normally function to limit immune activity. Treatment with ICIs reactivates T cells to destroy tumor cells in a highly specific manner, which in some patients, results in dramatic remissions and durable disease control. Over the last decade, much effort has been directed at characterizing factors that drive efficacy and resistance to ICI therapy. Food and Drug Administration (FDA)-approved biomarkers for ICI therapy have facilitated more judicious treatment of cancer patients and transformed the field of precision oncology. Yet, adaptive immunity against cancers is complex, and newer data have revealed the potential utility of other biomarkers. In this review, we discuss the utility of currently approved biomarkers and highlight how emerging biomarkers can further improve the identification of patients who benefit from ICIs.

Assessing the prognostic and therapeutic value of cuproptosis-related genes in colon adenocarcinoma patients

Background

Colon adenocarcinoma (COAD) remains a major global health challenge with poor prognosis despite advances in treatment, underscoring the need for new biomarkers. As a novel mode of cell death, cuproptosis is thought to be potentially involved in the development of cancer. However, the particularly as the role of cuproptosis-related genes (CRGs) in COAD prognosis and therapy remains unclear.

Methods

We analyzed RNA sequencing data from The Cancer Genome Atlas for COAD, focusing on CRG expression patterns and their clinicopathological correlations. Using the Weighted Gene Co-expression Network Analysis (WGCNA) method, we identified the gene module most strongly linked to cuproptosis and conducted functional enrichment analysis to explore the roles of genes within this module in COAD tumorigenesis. A novel prognostic risk model based on four CRGs (ORC1, PTTG1, DLAT, PDHB) was developed to stratify COAD patients into high-risk and low-risk groups, assessing overall survival, tumor microenvironment, and mutational landscape differences. We also evaluated the therapeutic effects of ferredoxin 1 (FDX1) and elesclomol in promoting cuproptosis in HCT116 and LoVo cell lines through various experiments, including cell proliferation, apoptosis assessment, mitochondrial membrane potential evaluation, and DLAT lipoylation detection via Western blot.

Results

Certain CRGs showed different expressions in COAD versus normal tissues. WGCNA identified a gene module linked to cuproptosis, crucial for pathways like cell cycle regulation, citrate cycle (TCA cycle), and DNA replication. The novel risk model stratified patients into high and low-risk groups based on risk scores, revealing that high-risk COAD patients had shorter overall survival and distinct immune cell infiltration, while low-risk patients were more sensitive to immunotherapy. Experimental results indicated that FDX1 exerted an inhibitory effect on COAD, and its combination with elesclomol significantly reduced proliferation, promoted apoptosis, increased DLAT lipoylation, and lowered mitochondrial membrane potential in COAD cells.

Conclusion

The findings of this study provided a new perspective for the research on biomarkers and therapeutic strategies in COAD, evaluated the prognostic and therapeutic value of CRGs in COAD patients, and laid a theoretical foundation for the future clinical application of CRGs.

Integration of graph neural networks and transcriptomics analysis identify key pathways and gene signature for immunotherapy response and prognosis of skin melanoma

OBJECTIVE

The assessment of immunotherapy plays a pivotal role in the clinical management of skin melanoma. Graph neural networks (GNNs), alongside other deep learning algorithms and bioinformatics approaches, have demonstrated substantial promise in advancing cancer diagnosis and treatment strategies.

METHODS

GNNs models were developed to predict the response to immunotherapy and to pinpoint key pathways. Utilizing the genes from these key pathways, multi-omics bioinformatics methods were employed to refine the construction of a gene signature, termed responseScore, aimed at enhancing the precision of immunotherapy response predictions. Subsequently, responseScore was explored from the perspectives of prognosis, genetic variation, pathway enrichment, and the tumor microenvironment. Concurrently, the association among 13 genes contributing to responseScore and factors such as immunotherapy response, prognosis, and the tumor microenvironment was investigated. Among these genes, PSMB6 was subjected to an in-depth analysis of its biological effect through experimental approaches like transfection and co-culture.

RESULTS

In the finalized model utilizing GNNs, it has revealed an AUC of 0.854 within the training dataset and 0.824 within the testing set, pinpointing key pathways such as R-HSA-70,268. The indicator named as responseScore excelled in its predictive accuracy regarding immunotherapy response and patient prognosis. Investigations into genetic variation, pathway enrichment, tumor microenvironment disclosed a profound association between responseScore and the enhancement of immune cell infiltration and anti-tumor immunity. A negative correlation was observed between the expression of PSMB6 and immune genes, with elevated PSMB6 expression correlating with poor prognosis. ELISA detection after co-cultivation experiments revealed significant reductions in the levels of cytokines IL-6 and IL-1β in specimens from the PCDH-PSMB6 group.

CONCLUSION

The GNNs prediction model and the responseScore developed in this research effectively indicate the immunotherapy response and prognosis for patients with skin melanoma. Additionally, responseScore provides insights into the tumor microenvironment and the characteristics of tumor immunity of melanoma. Thirteen genes identified in this study show promise as potential tumor markers or therapeutic targets. Notably, PSMB6 emerges as a potential therapeutic target for skin melanoma, where its elevated expression exhibits an inhibitory effect on the tumor immunity.

Spatial dissection of tumour microenvironments in gastric cancers reveals the immunosuppressive crosstalk between CCL2+ fibroblasts and STAT3-activated macrophages

BACKGROUND

A spatially resolved, niche-level analysis of tumour microenvironments (TME) can provide insights into cellular interactions and their functional impacts in gastric cancers (GC).

OBJECTIVE

Our goal was to translate the spatial organisation of GC ecosystems into a functional landscape of cellular interactions involving malignant, stromal and immune cells.

DESIGN

We performed spatial transcriptomics on nine primary GC samples using the Visium platform to delineate the transcriptional landscape and dynamics of malignant, stromal and immune cells within the GC tissue architecture, highlighting cellular crosstalks and their functional consequences in the TME.

RESULTS

GC spatial transcriptomes with substantial cellular heterogeneity were delineated into six regional compartments. Specifically, the fibroblast-enriched TME upregulates epithelial-to-mesenchymal transformation and immunosuppressive response in malignant and TME cells, respectively. Cell type-specific transcriptional dynamics revealed that malignant and endothelial cells promote the cellular proliferations of TME cells, whereas the fibroblasts and immune cells are associated with procancer and anticancer immunity, respectively. Ligand-receptor analysis revealed that CCL2-expressing fibroblasts promote the tumour progression via JAK-STAT3 signalling and inflammatory response in tumour-infiltrated macrophages. CCL2+ fibroblasts and STAT3-activated macrophages are co-localised and their co-abundance was associated with unfavourable prognosis. We experimentally validated that CCL2+ fibroblasts recruit myeloid cells and stimulate STAT3 activation in recruited macrophages. The development of immunosuppressive TME by CCL2+ fibroblasts were also validated in syngeneic mouse models.

CONCLUSION

GC spatial transcriptomes revealed functional cellular crosstalk involving multiple cell types among which the interaction between CCL2+ fibroblasts and STAT3-activated macrophages plays roles in establishing immune-suppressive GC TME with potential clinical relevance.

PAQR4: From spatial regulation of cell signaling to physiological homeostasis and diseases

Progestin and adipoQ receptor family member 4 (PAQR4) gene is a recently discovered seven-transmembrane protein-coding gene that belongs to the PAQR family. An increasing amount of evidence suggests that PAQR4 is upregulated in multiple tumors and participates in tumor progression and chemotherapy resistance via different signaling pathways; PAQR4 regulates cellular ceramide homeostasis by influencing sphingolipid metabolism and glycerol metabolism, and plays a significant role in adipose tissue remodeling. Meanwhile, it is known that the differential expression of PAQR4 is associated with the occurrence of various diseases and is a potential biomarker and therapeutic target. This article conducts a systematic review of the subcellular localization of PAQR4, its topological structure characteristics, and its functions in cancer occurrence, metabolic diseases, and fertility, and provides clues for the future research and translational application of PAQR4.

Immune Clustering Reveals Molecularly Distinct Subtypes of Lung Adenocarcinoma

Background/objectives: Lung adenocarcinoma, the most prevalent type of non-small cell lung cancer, consists of two driver mutations in KRAS or EGFR. These mutations are generally mutually exclusive and biologically and clinically different. In this study, we aimed to test if lung adenocarcinoma tumors could be separated by their immune profiles using an unsupervised machine learning method. The underlying assumption was that differences in the immune response to tumors are characteristic of tumor subtypes. Methods: RNA-seq data were projected into inferred immune profiles. Unsupervised learning was used to divide the lung adenocarcinoma population based on their projected immune profiles. Results: The patient population was divided into three subgroups, one of which appeared to contain mostly EGFR patients. The tumors in the different clusters significantly differed in their expression of some of their known immune checkpoints (TIGIT, PD-1/PD-L1, and CTLA4). Discussion: We argue that EGFR mutations in each subgroup are immunologically different, which implies a distinct tumor microenvironment and might relate to the relatively high resistance of EGFR-positive tumors to immune checkpoint inhibitors. However, we cannot make the same claim about KRAS mutations.

Immunological responses and clinical outcomes in dogs with osteosarcoma receiving standard therapy and a Listeria vaccine expressing HER2

A clinical trial in dogs with spontaneous osteosarcoma was performed to assess a recombinant Listeria expressing a chimeric human HER2 (ADXS31-164c) as an adjunctive vaccine strategy to prevent metastatic disease and determine immunological correlates of clinical outcome. A total of 118 dogs with appendicular osteosarcoma were recruited into a 1-arm, multicenter, prospective trial of standard of care (SOC) therapy followed by ADXS31-164c. ADXS31-164c was well tolerated, with mostly transient, low-grade side effects. Significant differences in median disease-free interval (DFI) or median overall survival (OS) of immunized dogs compared to a historical cohort of dogs receiving SOC only were not observed. Elite survivors (DFI >490 days) showed transient increases in temperature and serum cytokines, including IL-6 and TNF-α, after the first immunization compared to short-term survivors (DFI 150-235 days). However, repeat immunizations in short-term survivors led to improved and comparable pyrexic and cytokine responses to elite survivors. PBMC transcriptomic analysis following vaccinations revealed robust cytotoxic activity in elite but not short-term survivors. Although ADXS31-164c did not significantly extend DFI or OS, immune responses to ADXS31-164c distinguished elite from short-term survivors. Improvement of immune responses over sequential ADXS31-164c administrations supports a future trial design of recurrent immunizations to improve outcomes of otherwise short-term survivors.

Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

SIGNIFICANCE

Integration of spatial transcriptomic (GeoMx Digital Spatial Profiler) and single-cell RNA sequencing data from multiple gastric cancers identifies spatially resolved expression-based intratumoral heterogeneity, associated with distinct immune microenvironments. We uncovered two separate evolutionary trajectories associated with specific molecular subtypes, clinical prognoses, stromal neighborhoods, and genetic drivers. Tumor-stroma interfaces emerged as a unique state of tumor ecology.

Health position paper and redox perspectives - Bench to bedside transition for pharmacological regulation of NRF2 in noncommunicable diseases

Nuclear factor erythroid 2-related factor 2 (NRF2) is a redox-activated transcription factor regulating cellular defense against oxidative stress, thereby playing a pivotal role in maintaining cellular homeostasis. Its dysregulation is implicated in the progression of a wide array of human diseases, making NRF2 a compelling target for therapeutic interventions. However, challenges persist in drug discovery and safe targeting of NRF2, as unresolved questions remain especially regarding its context-specific role in diseases and off-target effects. This comprehensive review discusses the dualistic role of NRF2 in disease pathophysiology, covering its protective and/or destructive roles in autoimmune, respiratory, cardiovascular, and metabolic diseases, as well as diseases of the digestive system and cancer. Additionally, we also review the development of drugs that either activate or inhibit NRF2, discuss main barriers in translating NRF2-based therapies from bench to bedside, and consider the ways to monitor NRF2 activation in vivo.

Stromal Stiffness-Regulated IGF2BP2 in Pancreatic Cancer Drives Immune Evasion via Sphingomyelin Metabolism

BACKGROUND AND AIMS

Immunotherapy has shown promising results in cancer treatment; however, it remains largely ineffective for pancreatic ductal adenocarcinoma (PDAC). N6-methyladenosine (m6A), known for its crucial role in cancer biology, is not yet fully understood regarding immune evasion. This study aims to elucidate the associations and mechanisms linking m6A modification with immune evasion in PDAC and propose strategies for clinical intervention.

METHODS

A multimodal PDAC cohort of 122 patients was developed, integrating transcriptomic profiling, imaging mass cytometry, and m6A quantification to identify m6A regulators associated with immunosuppressive tumor microenvironment (TME) and clinical outcomes. Findings were validated across 6 independent PDAC cohorts. Assays including MeRIP, RIP, and RNA pull-down confirmed that IGF2BP2 binds to targets, whereas scRNA-seq, flow cytometry, and mIHC profiled the TME. Preclinical interventions were tested in PDAC organoids, patient-derived tissue fragments, and humanized mouse models.

RESULTS

Our comprehensive analysis identified the m6A reader protein IGF2BP2 as a critical factor associated with poor prognosis in PDAC, linked to reduced effector cell infiltration and a fibrotic TME. High matrix stiffness in PDAC stabilized IGF2BP2, which subsequently promoted sphingomyelin synthesis via SGMS2 up-regulation. This pathway facilitates PD-L1 localization on membrane lipid rafts, enhancing immune evasion. The elastographic properties of PDAC enabled noninvasive screening of patients with overexpressed IGF2BP2/SGMS2. Disrupting sphingomyelin synthesis improved antitumor immunity and suppressed PDAC growth in humanized mice, highlighting immunotherapeutic opportunities for PDAC.

CONCLUSIONS

These findings emphasize the critical interplay between extrinsic matrix stiffness and intrinsic IGF2BP2-regulated sphingomyelin synthesis, identifying a promising target for immunotherapeutic strategies in PDAC.

Dual role of interferon-gamma in the response of melanoma patients to immunotherapy with immune checkpoint inhibitors

Interferon-gamma (IFN-γ) is a cytokine produced mainly by immune cells and can affect cancer cells by modulating the activity of multiple signaling pathways, including the canonical Janus-activated kinase/signal transducer and activator of transcription (JAK/STAT) cascade. In melanoma, IFN-γ can exert both anticancer effects associated with cell-cycle arrest and cell death induction and protumorigenic activity related to immune evasion leading to melanoma progression. Notably, IFN-γ plays a crucial role in the response of melanoma patients to immunotherapy with immune checkpoint inhibitors (ICIs), which are currently used in the clinic. As these agents target programmed death-1 (PD-1) and its ligand (PD-L1), cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) and lymphocyte-activation gene 3 (LAG-3), they are designed to restore the antimelanoma immune response. In this respect, IFN-γ produced by cells in the tumor microenvironment in response to ICIs has a beneficial influence on both immune and melanoma cells by increasing antigen presentation, recruiting additional T-cells to the tumor site, and inducing direct antiproliferative effects and apoptosis in melanoma cells. Therefore, IFN-γ itself and IFN-γ-related gene signatures during the response to ICIs can constitute biomarkers or predictors of the clinical outcome of melanoma patients treated with ICIs. However, owing to its multifaceted roles, IFN-γ can also contribute to developing mechanisms associated with the acquisition of resistance to ICIs. These mechanisms can be associated with either decreased IFN-γ levels in the tumor microenvironment or diminished responsiveness to IFN-γ due to changes in the melanoma phenotypes associated with affected activity of other signaling pathways or genetic alterations e.g., in JAK, which restricts the ability of melanoma cells to respond to IFN-γ. In this respect, the influence of IFN-γ on melanoma-specific regulators of the dynamic plasticity of the cell phenotype, including microphthalmia-associated transcription factor (MITF) and nerve growth factor receptor (NGFR)/CD271 can affect the clinical efficacy of ICIs. This review comprehensively discusses the role of IFN-γ in the response of melanoma patients to ICIs with respect to its positive influence and role in IFN-γ-related mechanisms of resistance to ICIs as well as the potential use of predictive markers on the basis of IFN-γ levels and signatures of IFN-γ-dependent genes.

Identifying distinct prognostic and predictive contributions of tumor epithelium versus tumor microenvironment in colorectal cancer

BACKGROUND

Accumulating evidence has suggested that cancer progression and therapeutic response depend on both tumor epithelium (EPI) and tumor microenvironment (TME). However, the dependency of clinical outcomes on the tumor EPI vs. the TME has neither been clearly defined nor quantified.

METHODS

We classified 2373 colorectal cancer (CRC) tumors into the consensus molecular subtypes (CMS1-4) and generated the 10-gene TMES and the 10-gene EPIS signatures as the serendipitous derivatives of the most (positively vs. negatively) correlated genes of a highly-prognostic, ~ 500-gene signature we previously identified. Distinct TME vs. EPI cellular features of the signature genes were identified by CIBERSORT deconvolution and validated by scRNASEQ in an independent public dataset.

RESULTS

The TMES signature was strongly associated with the immune/stromal TME-rich CMS1/CMS4 subtypes that portended worse survival, whereas the EPIS signature was predominantly related to the TME-poor, epithelial CMS2/CMS3 classes that portended better survival. Multivariable Cox regression analysis against 29 TME-related signatures revealed that the TMES signature was the most strikingly impacted by the "Cancer-associated fibroblasts" signature (HR: 10.87 vs. 0.13, both P < 0.0001). Moreover, the TMES score was strongly correlated with EMT, SRC activation and MEK inhibitor resistance in 2373 CRC tumors (Spearman r = 0.727, 0.802, 0.824, respectively), which was validated in two independent CRC datasets (n = 626 and n = 566). By contrast, the EPIS score was the dominant force in associating with longer progression free survival in cetuximab-treated metastatic CRC patients derived from two independent clinical trials (Logrank trend P = 0.0005/n = 80; P = 0.0013/n = 44). This finding was further validated in a large real-world clinico-genomics dataset with EGFR inhibitor therapy, which demonstrated that higher EPIS scores were associated with increased overall survival (EGFRi, Logrank trend P < 0.0001/n = 2343) and time on treatment (cetuximab, P = 0.003/n = 953; panitumumab, P < 0.0001/n = 1307).

CONCLUSIONS

Here we identified a pair of new, distinct 10-gene signatures (the EPIS vs. the TMES) capable of distinguishing the cellular contribution of the tumor EPI vs. the TME in determining CRC prognosis and therapeutic outcomes. With targeted approaches emerging to address both tumor epithelial cells and the TME, the EPIS vs. TMES signature scores may have a novel biomarker role to permit optimization of CRC therapy by identifying sensitive vs. resistant subpopulations.

Cross-Talk Between Cancer and Its Cellular Environment-A Role in Cancer Progression

The tumor microenvironment is a dynamic and complex three-dimensional network comprising the extracellular matrix and diverse non-cancerous cells, including fibroblasts, adipocytes, endothelial cells and various immune cells (lymphocytes T and B, NK cells, dendritic cells, monocytes/macrophages, myeloid-derived suppressor cells, and innate lymphoid cells). A constantly and rapidly growing number of studies highlight the critical role of these cells in shaping cancer survival, metastatic potential and therapy resistance. This review provides a synthesis of current knowledge on the modulating role of the cellular microenvironment in cancer progression and response to treatment.

Identification of a conserved subset of cold tumors responsive to immune checkpoint blockade

BACKGROUND

The efficacy of immune checkpoint blockade (ICB) depends on restoring immune recognition of cancer cells that have evaded immune surveillance. Transforming growth factor-beta (TGFβ) is associated with immune-poor, so-called cold tumors whereas loss of its signaling promotes DNA misrepair that could stimulate immune response.

METHODS

We analyzed transcriptomic data from IMvigor210, The Cancer Genome Atlas, and Tumor Immune Syngeneic MOuse data sets to evaluate the predictive value of high βAlt, a score representing low expression of a signature consisting of TGFβ targets and high expression of genes involved in error-prone DNA repair. The immune context of βAlt was assessed by evaluating tumor-educated immune signatures. An ICB-resistant, high βAlt preclinical tumor model was treated with a TGFβ inhibitor, radiation, and/or ICB and assessed for immune composition and tumor control.

RESULTS

We found that a high βAlt score predicts ICB response yet is paradoxically associated with an immune-poor tumor microenvironmentcancer in both human and mouse tumors. We postulated that high βAlt cancers consist of cancer cells in which loss of TGFβ signaling generates a TGFβ rich, immunosuppressive tumor microenvironment. Accordingly, preclinical modeling showed that TGFβ inhibition followed by radiotherapy could convert an immune-poor, high βAlt tumor to an immune-rich, ICB-responsive tumor. Mechanistically, TGFβ inhibition increased activated natural killer (NK) cells, which were required to recruit lymphocytes to respond to ICB in irradiated tumors. NK cell activation signatures were also increased in high βAlt, cold mouse and human tumors that responded to ICB.

CONCLUSIONS

These studies indicate that loss of TGFβ signaling competency and gain of error-prone DNA repair identifies a subset of cold tumors that are responsive to ICB. Our mechanistic studies show that inhibiting TGFβ activity can convert a high βAlt, cold tumor into ICB-responsive tumors via NK cells. A biomarker consisting of combined TGFβ, DNA repair, and immune context signatures is a means to prospectively identify patients whose cancers may be converted from cold to hot with appropriate therapy.

Pathogenic germline variants in Chinese pancreatic adenocarcinoma patients

Putting pancreatic adenocarcinoma (PAAD) screening into perspective for high-risk individuals could significantly reduce cancer morbidity and mortality. Previous studies have profiled somatic mutations in PAAD. In contrast, the prevalence of mutations in PAAD predisposition genes has not been defined, especially in the Asian population. Using a multi-tier cohort design and whole genome/exome sequencing, we create a comprehensive germline mutation map of PAAD in 1,123 Chinese cancer patients in comparison with 11 pan-ethnic studies. For well-known pathogenic/likely pathogenic germline variants, Chinese patients exhibit overlapping but distinct germline mutation patterns comparing with Western cohorts, highlighted by lower mutation rates in known PAAD genes including BRCA1, BRCA2, ATM, CDKN2A, and CHEK2, and distinct mutations in CFTR, RAD51D, FANCA, ERCC2, and GNAS exclusive to Chinese patients. CFTR emerges as a top candidate gene following loss of heterozygosity analysis. Using an integrative multi-omics and functional validation paradigm, we discover that deleterious variants of uncertain significance may compromise CFTR's tumor suppressor function, and demonstrate the clinical relevance by using patient derived organoids for drug screen. Our multifaceted approach not only deepens the knowledge of population differences in PAAD germline mutations but also unveils potential avenues for targeted therapeutic interventions.

Regulation of histone H3K27 methylation in inflammation and cancer

Inflammation is a multifaceted defense mechanism of the immune system against infection. Chronic inflammation is intricately linked to all stages of tumorigenesis and is therefore associated with an elevated risk of developing serious cancers. Epigenetic mechanisms have the capacity to trigger inflammation as well as facilitate tumor development and transformation within an inflammatory context. They achieve this by dynamically modulating the expression of both pro-inflammatory and anti-inflammatory cytokines, which in turn sustains chronic inflammation. The aberrant epigenetic landscape reconfigures the transcriptional programs of inflammatory and oncogenic genes. This reconfiguration is pivotal in dictating the biological functions of both tumor cells and immune cells. Aberrant histone H3 lysine 27 site (H3K27) methylation has been shown to be involved in biological behaviors such as inflammation development, tumor progression, and immune response. The establishment and maintenance of this repressive epigenetic mark is dependent on the involvement of the responsible histone modifying enzymes enhancer of zeste homologue 2 (EZH2), jumonji domain containing 3 (JMJD3) and ubiquitously transcribed tetratricopeptide repeat gene X (UTX) as well as multiple cofactors. In addition, specific pharmacological agents have been shown to modulate H3K27 methylation levels, thereby modulating inflammation and carcinogenesis. This review comprehensively summarises the current characteristics and clinical significance of epigenetic regulation of H3K27 methylation in the context of inflammatory response and tumor progression.

Blocking WNT7A Enhances MHC-I Antigen Presentation and Enhances the Effectiveness of Immune Checkpoint Blockade Therapy

The limited infiltration of CD8+ T cells in tumors hampers the effectiveness of T cell-based immunotherapy, yet the mechanisms that limit tumor infiltration by CD8+ T cells remain unclear. Through bulk RNA sequencing of human tumors, we identified a strong correlation between WNT7A expression and reduced CD8+ T-cell infiltration. Further investigation demonstrated that inhibiting WNT7A substantially enhanced MHC-I expression on tumor cells. Mechanistically, WNT7A inhibition inactivated the Wnt/β-catenin signaling pathway and thus resulted in reduced physical interaction between β-catenin and p65 in the cytoplasm, which increased the nuclear translocation of p65 and activated the NF-κB pathway, ultimately promoting the transcription of genes encoding MHC-I molecules. We found that our lead compound, 1365-0109, disrupted the protein-protein interaction between WNT7A and its receptor FZD5, resulting in the upregulation of MHC-I expression. In murine tumor models, both genetic and pharmaceutical suppression of WNT7A led to increased MHC-I levels on tumor cells, and consequently enhanced the infiltration and functionality of CD8+ T cells, which bolstered antitumor immunity and improved the effectiveness of immune checkpoint blockade therapy. These findings have elucidated the intrinsic mechanisms of WNT7A-induced immune suppression, suggesting that therapeutic interventions targeting WNT7A hold promise for enhancing the efficacy of immunotherapy.

Androgen Receptor Inhibition Increases MHC Class I Expression and Improves Immune Response in Prostate Cancer

SIGNIFICANCE

Immunotherapy options for immune cold tumors, like prostate cancer, are limited. We show that AR downregulates MHCI expression/antigen presentation and that AR inhibition improves T-cell responses and tumor control. This suggests that treatments combining AR inhibitors and checkpoint blockade may improve tumor immune surveillance and antitumor immunity in patients.

Targeting HER2 in Gastroesophageal Cancer: A New Appetite for an Old Plight

The incidence of gastroesophageal cancers is rising, driven, in part, by an increasing burden of risk factors of obesity and gastroesophageal reflux. Despite efforts to address these risk factors, and a growing interest in methods of population screening, the bulk of these tumours are unresectable at diagnosis. In this setting, effective systemic treatments are paramount to improve survival and quality of life. Early and accurate identification of oncogenic drivers, such as human epidermal growth factor receptor 2 (HER2), present in 5-30% of gastroesophageal adenocarcinomas (GEAs), is integral to guide choice of therapies due to the clear predictive implications that arise from overexpression of this receptor. After trastuzumab, the first anti-HER2 agent with approved use in HER2-positive GEA, the addition of pembrolizumab to first-line trastuzumab-chemotherapy and trastuzumab deruxtecan in the refractory space have more recently changed practice. Yet, the response to these agents has been vastly different across patients with HER2-positive disease, underpinning the need for reliable biomarkers of response. Emergent data have suggested that levels of HER2 expression on tissue or liquid biopsies may predict response to first-generation HER2 therapies while HER2 heterogeneity, receptor changes, co-occurring molecular alterations and oncogenic genomic and metabolic reprogramming may be implicated in resistance. A robust knowledge of the mechanisms of resistance and response to HER2-directed therapies is necessary to inform novel strategies of HER2-targeting and guide choice combinations with other biomarker-directed therapies, to improve outcomes from a new generation of clinical trials in HER2-positive GEA. Understanding and close examination of previous failures in this space form an important part of this assessment, as does correlative biomarker and translational work pertaining to the role of HER2 and dynamic changes that result through treatment exposure. In this review, we aim to provide an overview of strategies for HER2 targeting, summarising both the successes and disappointments in this therapeutic landscape and discuss existing challenges and future perspectives on development in this highly morbid tumour type.

Pretrained transformers applied to clinical studies improve predictions of treatment efficacy and associated biomarkers

Cancer treatment has made significant advancements in recent decades, however many patients still experience treatment failure or resistance. Attempts to identify determinants of response have been hampered by a lack of tools that simultaneously accommodate smaller datasets, sparse or missing measurements, multimodal clinicogenomic data, and that can be interpreted to extract biological or clinical insights. We introduce the Clinical Transformer, an explainable transformer-based deep-learning framework that addresses these challenges. Our framework maximizes data via self-supervised, gradual, and transfer learning, and yields survival predictions surpassing performance of state-of-the-art methods across diverse, independent datasets. The framework's generative capability enables in silico perturbation experiments to test counterfactual hypotheses. By perturbing immune-associated features in immunotherapy-naive patients, we identify a patient subset that may benefit from immunotherapy, and we validate this finding across three independent immunotherapy-treated cohorts. We anticipate our work will empower the scientific community to further harness data for the benefit of patients.

IL-27 elicits a cytotoxic CD8+ T cell program to enforce tumour control

Although cytotoxic CD8+ T lymphocytes (CTLs) are essential for anti-tumour immunity, they are frequently dysfunctional in tumours1. Cytokines that sustain CTL activity are attractive for cancer immunotherapy, but avoiding inflammatory toxicity remains a challenge for their clinical use2. Here we show that expression of a CTL signature is strongly associated with IL27 expression in human and mouse tumours. In mice, IL-27 acts directly on tumour-specific CTLs to promote their persistence and effector function in the tumour microenvironment. Moreover, treatment with inducible IL-27 overexpression or a half-life-extended IL-27 protein in vivo is well tolerated, induces regression of established tumours, drives an enhanced cytotoxic program in anti-tumour CTLs and synergizes with PD-L1 blockade. In patients with cancer who were treated with anti-PD-1/PD-L1 therapy, high expression of IL-27 correlates with a favourable clinical response, and IL-27 supports human CTL function during chronic antigen stimulation ex vivo. Our data demonstrate that endogenous IL-27 is essential for anti-tumour immunity and that IL-27 receptor agonism can safely improve anti-tumour T cell responses alone or in combination with PD-L1 blockade.

Oronasal mucosal melanoma is defined by two transcriptional subtypes in humans and dogs with implications for diagnosis and therapy

Mucosal melanoma is a rare melanoma subtype associated with a poor prognosis and limited existing therapeutic interventions, in part due to a lack of actionable targets and translational animal models for preclinical trials. Comprehensive data on this tumour type are scarce, and existing data often overlooks the importance of the anatomical site of origin. We evaluated human and canine oronasal mucosal melanoma (OMM) to determine whether the common canine disease could inform the rare human equivalent. Using a human and canine primary OMM cohort of treatment-naive archival tissue, alongside clinicopathological data, we obtained transcriptomic, immunohistochemical, and microbiome data from both species. We defined the transcriptomic landscape in both species and linked our findings to immunohistochemical, microbiome, and clinical data. Human and dog OMM stratified into two distinctive transcriptional groups, which we defined using a species-independent 41-gene signature. These two subgroups are termed CTLA4-high and MET-high and indicate actionable targets for OMM patients. To guide clinical decision-making, we developed immunohistochemical diagnostic tools that distinguish between transcriptomic subgroups. We found that OMM had conserved transcriptomic subtypes and biological similarity between human and canine OMM, with significant implications for patient classification, treatment, and clinical trial design. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Hepatic Stellate Cells Functional Heterogeneity in Liver Cancer

Hepatic stellate cells (HSCs) are the liver's pericytes, and play key roles in liver homeostasis, regeneration, fibrosis, and cancer. Upon injury, HSCs activate and are the main origin of myofibroblasts and cancer-associated fibroblasts (CAFs) in liver fibrosis and cancer. Primary liver cancer has a grim prognosis, ranking as the third leading cause of cancer-related deaths worldwide, with hepatocellular carcinoma (HCC) being the predominant type, followed by intrahepatic cholangiocarcinoma (iCCA). Moreover, the liver hosts 35% of all metastatic lesions. The distinct spatial distribution and functional roles of HSCs across these malignancies represent a significant challenge for universal therapeutic strategies, requiring a nuanced and tailored understanding of their contributions. This review examines the heterogeneous roles of HSCs in liver cancer, focusing on their spatial localization, dynamic interactions within the tumor microenvironment (TME), and emerging therapeutic opportunities, including strategies to modulate their activity, and harness their potential as targets for antifibrotic and antitumor interventions.

Impact of PSMD2 on Gastric Cancer Tissue Stiffness Investigated via Motor-Piezoceramic Coupled Atomic Force Microscopy

Gastric cancer is one of the deadliest malignant tumors of the digestive tract, and its development and metastasis are regulated by various factors. Some studies have shown that PSMD2 is involved in cancer development by regulating the tumor microenvironment stiffness. However, the exact mechanism is unclear, and effective means to quantify the effect of PSMD2 on gastric cancer tissue hardness are lacking. Herein, we revealed the mechanical heterogeneity of tumor tissues in gastric cancer patients using a large-scale AFM-based in situ method. Gastric cancer cryosections were probed by this method under aqueous condition. The in situ fluorescence images were measured to correlate tissue stiffness with PSMD2 expression. Experimental results clearly revealed the specific distribution of mechanics in gastric cancer tissues under differences in PSMD2 expression. The study unveils the effect of PSMD2 expression levels on cancer invasion and increased matrix stiffness, providing a novel insight into gastric cancer research.

Effect of prior and first-line immunotherapy on baseline immune biomarkers and modulation of the tumor microenvironment in response to nivolumab and relatlimab combination therapy in patients with melanoma from RELATIVITY-020

BACKGROUND

Some patients with melanoma experience disease progression during immunotherapy (IO) and may benefit from novel combinations of immune checkpoint inhibitors (ICIs). We report results from exploratory biomarker analyses to characterize the responses of patients with advanced melanoma to treatment with nivolumab (anti-programmed cell death-1 (PD-1)) and relatlimab (anti-lymphocyte-activation gene 3 (LAG-3)) combination therapy in RELATIVITY-020 (NCT01968109).

METHODS

Tumor biopsies collected at baseline and ≤4 weeks after treatment initiation were evaluated for % LAG-3-positive and % CD8-positive immune cells and % programmed death-ligand 1 (PD-L1) expression on tumor cells. Baseline biomarker expression was compared among patients with IO-refractory melanoma based on last prior therapy and IO-resistance type, and between patients with IO-refractory and IO-naïve melanoma. Change in biomarker expression after treatment was evaluated in patients with IO-refractory and IO-naïve melanoma. Immune-related gene expression was compared among resistance groups and by the last prior treatment.

RESULTS

Among patients with IO-refractory melanoma (N=505), elevated baseline LAG-3, PD-L1, and CD8 expression (p≤0.01, p≤0.05, p≤0.001, respectively) was observed in patients whose last prior therapy was IO versus non-IO, and in those who responded (complete/partial per Response Evaluation Criteria in Solid Tumors V.1.1) to nivolumab and relatlimab combination therapy versus those who did not (stable/progressive disease). Inflammation-related gene expression was significantly higher (p<0.05) in patients with secondary versus primary resistance to prior IO treatment, and in those whose last prior therapy was IO versus non-IO. IO-refractory patients whose tumors responded to nivolumab and relatlimab combination therapy had higher inflammation-related gene expression than non-responders (p<0.05); proliferation and hypoxia-related gene expression were enriched in non-responders. During treatment with nivolumab and relatlimab combination therapy, LAG-3 expression increased significantly in patients with IO-refractory (p≤0.01) and IO-naïve melanoma (p≤0.001), and PD-L1 and CD8 increased significantly (p≤0.01 and p≤0.05, respectively) in patients with IO-naïve melanoma.

CONCLUSIONS

Nivolumab and relatlimab combination therapy can modulate the tumor microenvironment in patients with both IO-refractory and IO-naïve melanoma. Further research is needed to identify patients who will most benefit from anti-LAG-3/PD-(L)1 agents, and to elucidate the mechanisms of action of, and resistance to, this combination therapy in patients with advanced melanoma.

TRIAL REGISTRATION NUMBER

NCT01968109.

Mathematically mapping the network of cells in the tumor microenvironment

Cell-cell interaction (CCI) networks are key to understanding disease progression and treatment response. However, existing methods for inferring these networks often aggregate data across patients or focus on cell-type level interactions, providing a generalized overview but overlooking patient heterogeneity and local network structures. To address this, we introduce "random cell-cell interaction generator" (RaCInG), a model based on random graphs to derive personalized networks leveraging prior knowledge on ligand-receptor interactions and bulk RNA sequencing data. We applied RaCInG to 8,683 cancer patients to extract 643 network features related to the tumor microenvironment and unveiled associations with immune response and subtypes, enabling prediction and explanation of immunotherapy responses. RaCInG demonstrated robustness and showed consistencies with state-of-the-art methods. Our findings highlight RaCInG's potential to elucidate patient-specific network dynamics, offering insights into cancer biology and treatment responses. RaCInG is poised to advance our understanding of complex CCI s in cancer and other biomedical domains.

Construction of hot tumor classification models in gastrointestinal cancers

BACKGROUND

Gastrointestinal (GI) cancers account for more than one-third of cancer-related mortality, and the prognosis for late-stage patients remains poor. Immunotherapy has been proven to extend the survival of patients at advanced stages; however, challenges persist in patient selection and overcoming drug resistance. Tumor-infiltrating lymphocytes (TILs) and tertiary lymphoid structures (TLS) in the tumor microenvironment (TME) have been found to be associated with anti-tumor immune responses. 'Hot tumors' with high levels of infiltration tend to respond better to immune checkpoint inhibitor (ICI) therapy, making them potential biomarkers for ICI treatment.

METHODS

To explore potential biomarkers for predicting immunotherapy response and prognosis in GI cancers, we downloaded the gene expression profiles of seven GI cancers from The Cancer Genome Atlas (TCGA) database and characterized their TME, classifying the samples into hot/cold tumor subgroups. Furthermore, we developed a computational framework to construct cancer-specific hot tumor classification models with only a few genes. External independent datasets and qPCR experiments were used to verify the performance of our few-gene models.

RESULTS

We constructed cancer-specific few-gene models to identify hot tumors for GI cancers with only two to nine genes. The results showed that B cells are important for hot tumor determination, and the identified hot tumors are significantly associated with TLS. They not only overexpress TLS marker genes but are also associated with the presence of TLS in whole-slide images. Further, a two-gene qPCR model was developed to effectively distinguish between hot and cold tumor subgroups in cholangiocarcinoma, providing an opportunity for stratifying patients with hot tumors in clinical settings.

CONCLUSIONS

In conclusion, our established few-gene models, which can be easily integrated into clinical practice, can distinguish hot and cold tumor subgroups, and may serve as potential biomarkers for predicting ICI response.

The Breast Cancer Classifier refines molecular breast cancer classification to delineate the HER2-low subtype

Current breast cancer classification methods, particularly immunohistochemistry and PAM50, face challenges in accurately characterizing the HER2-low subtype, a therapeutically relevant entity with distinct biological features. This notable gap can lead to misclassification, resulting in inappropriate treatment decisions and suboptimal patient outcomes. Leveraging RNA-seq and machine-learning algorithms, we developed the Breast Cancer Classifier (BCC), a unique transcriptomic classifier for more precise breast cancer subtyping, specifically by delineating and incorporating HER2-low as a distinct subtype. BCC also redefined the PAM50 Normal subtype into other subtypes, disputing its classification as a unique molecular group. Our statistical analysis not only confirmed the reproducibility and accuracy of BCC, but also revealed similarities in prognostic characteristics between the HER2-low and Basal subtypes. Addressing this gap in breast cancer classification is clinically significant because it not only improves treatment stratification, but also uncovers novel molecular and immunohistochemical features associated with the HER2-low and HER2-high subtypes, thereby advancing our understanding of breast cancer heterogeneity and providing guidance in precision oncology.

A conserved subset of cold tumors responsive to immune checkpoint blockade

Background

The efficacy of immune checkpoint blockade (ICB) depends on restoring immune recognition of cancer cells that have evaded immune surveillance. At the time of diagnosis, patients with lymphocyte-infiltrated cancers are the most responsive to ICB, yet a considerable fraction of patients have immune-poor tumors.

Methods

We analyzed transcriptomic data from IMvigor210, TCGA, and TISMO datasets to evaluate the predictive value of βAlt, a score representing the negative correlation of signatures consisting of transforming growth factor beta (TGFβ) targets and genes involved in error-prone DNA repair. The immune context of βAlt was assessed by evaluating tumor-educated immune signatures. An ICB-resistant, high βAlt preclinical tumor model was treated with a TGFβ inhibitor, radiation, and/or ICB and assessed for immune composition and tumor control.

Results

Here, we show that high βAlt is associated with an immune-poor context yet is predictive of ICB response in both humans and mice. A high βAlt cancer in which TGFβ signaling is compromised generates a TGFβ rich, immunosuppressive tumor microenvironment. Accordingly, preclinical modeling showed that TGFβ inhibition followed by radiotherapy could convert an immune-poor, ICB-resistant tumor to an immune-rich, ICB-responsive tumor. Mechanistically, TGFβ blockade in irradiated tumors activated natural killer cells that were required to recruit lymphocytes to respond to ICB. In support of this, natural killer cell activation signatures were also increased in immune-poor mouse and human tumors that responded to ICB.

Conclusions

These studies suggest that loss of TGFβ competency identifies a subset of cold tumors that are candidates for ICB. Our mechanistic studies show that inhibiting TGFβ activity converts high βAlt, cold tumors into ICB-responsive tumors via NK cells. Thus, a biomarker consisting of combined TGFβ, DNA repair, and immune context signatures provides a means to prospectively identify patients whose cancers may be converted from 'cold' to 'hot,' which could be exploited for therapeutic treatment.

A Systematic Review and Meta-Analysis of 16S rRNA and Cancer Microbiome Atlas Datasets to Characterize Microbiota Signatures in Normal Breast, Mastitis, and Breast Cancer

The breast tissue microbiome has been increasingly recognized as a potential contributor to breast cancer development and progression. However, inconsistencies in microbial composition across studies have hindered the identification of definitive microbial signatures. We conducted a systematic review and meta-analysis of 11 studies using 16S rRNA sequencing to characterize the bacterial microbiome in 1260 fresh breast tissue samples, including normal, mastitis-affected, benign, cancer-adjacent, and cancerous tissues. Studies published until 31 December 2023 were included if they analyzed human breast tissue using Illumina short-read 16S rRNA sequencing with sufficient metadata, while non-human samples, non-breast tissues, non-English articles, and those lacking metadata or using alternative sequencing methods were excluded. We also incorporated microbiome data from The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort to enhance our analyses. Our meta-analysis identified Proteobacteria, Firmicutes, Actinobacteriota, and Bacteroidota as the dominant phyla in breast tissue, with Staphylococcus and Corynebacterium frequently detected across studies. While microbial diversity was similar between cancer and cancer-adjacent tissues, they both exhibited a lower diversity compared to normal and mastitis-affected tissues. Variability in bacterial genera was observed across primer sets and studies, emphasizing the need for standardized methodologies in microbiome research. An analysis of TCGA-BRCA data confirmed the dominance of Staphylococcus and Corynebacterium, which was associated with breast cancer proliferation-related gene expression programs. Notably, high Staphylococcus abundance was associated with a 4.1-fold increased mortality risk. These findings underscore the potential clinical relevance of the breast microbiome in tumor progression and emphasize the importance of methodological consistency. Future studies to establish causal relationships, elucidate underlying mechanisms, and assess microbiome-targeted interventions are warranted.

Induction chemotherapy followed by camrelizumab plus apatinib and chemotherapy as first-line treatment for extensive-stage small-cell lung cancer: a multicenter, single-arm trial

Chemo-immunotherapy is the current first-line treatment for patients with extensive-stage small cell lung cancer (ES-SCLC), but survival benefits are modest. We aimed to evaluate the safety, antitumor activity and biomarkers of first-line camrelizumab and apatinib plus chemotherapy in untreated ES-SCLC patients. In this single-arm trial (ClinicalTrials.gov NCT05001412), eligible patients received 2 cycles of etoposide and carboplatin (EC) as induction treatment followed by 2-4 cycles of camrelizumab, apatinib plus EC, then maintenance camrelizumab plus apatinib. Primary endpoint was safety. Secondary endpoints included objective response rate (ORR), duration of response, progression-free survival (PFS), and overall survival (OS). Targeted sequencing and whole transcriptome sequencing were performed to explore biomarkers. All enrolled 40 patients were treated and analyzed for safety. During the entire treatment, treatment-emergent adverse events (TEAEs) occurred in 40 patients (100%), and 30 (75.0%) were grade ≥3. The most common grade ≥3 TEAEs were neutropenia (35.0%), anemia (15.0%) and increased alanine aminotransferase (15.0%). No treatment-related deaths occurred. Among 36 evaluable patients, ORR was 88.9% (95% CI: 73.9%-96.9%), median PFS was 7.3 months (95% CI: 6.6-9.2) and median OS was 17.3 months (11.8-not reached). Mutations in RB1, high levels of tumor mutation burden, natural killer cells, and interferons, and low levels of cancer-associated fibroblasts, correlated with prolonged PFS. Induction chemotherapy followed by camrelizumab, apatinib plus EC demonstrated acceptable safety and promising antitumor activity in untreated ES-SCLC patients. The identified biomarkers need further validation.Trial Registration ClinicalTrials.gov Identifier: NCT05001412.

Next-Generation Sequencing-Based MSI Scoring Predicts Benefit in Mismatch Repair-Deficient Tumors Treated with Nivolumab: Follow-up on NCI-MATCH Arm Z1D

PURPOSE

Mismatch repair-deficient (dMMR) tumors have demonstrated favorable responses to immune checkpoint inhibition targeting PD-1. However, more in-depth identification of predictors of response could further refine patient selection for immunotherapy treatment.

PATIENTS AND METHODS

We undertook integrated evaluation performed on samples collected from 28 of 42 patients enrolled on the NCI-Molecular Analysis for Therapy Choice arm Z1D trial that evaluated PD-1 inhibition treatment with nivolumab in patients with noncolorectal dMMR tumors. Genomic analyses were performed using next-generation sequencing (NGS), whole-exome sequencing, and RNA sequencing and supplemented by multiplex immunofluorescence performed on tissue samples.

RESULTS

In this dMMR population, more extensive alterations of microsatellites as assessed by measures of NGS were associated with clinical benefit and tumor mutational burden. RNA sequencing further revealed associations between clinical benefit and immune infiltration index. Gene sets enriched in patients with clinical benefit included IFN signaling, antigen processing, and PI3K-AKT-mTOR signaling, whereas hedgehog signaling was found to be enriched in subjects lacking clinical benefit.

CONCLUSIONS

These genomic data highlight the importance of immune infiltration and antigen presentation in dMMR tumors that respond to immune checkpoint blockade. In addition, they suggest that, even within a dMMR population, NGS-based measures of microsatellite instability could serve as biomarkers of immunotherapy response.

Identification of T cell dysfunction molecular subtypes and exploration of potential immunotherapy targets in BRAF V600E-mutant colorectal cancer

BACKGROUND

Immunotherapy is an effective treatment for BRAF V600E-mutant colorectal cancer, but currently, only a few benefit from it. Therefore, exploring new immunotherapy strategies is essential.

METHODS

We obtained RNA sequencing data and clinical information of colorectal cancer patients from the TCGA and GEO databases. The impact of the BRAF V600E mutation on tumor microenvironment characteristics, gene expression, and signaling pathways was evaluated using bioinformatics approaches. Weighted gene co-expression network analysis (WGCNA) were used to identify core genes associated with T cell dysfunction. Consensus clustering was applied for subtype construction. Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF) algorithms were employed to filter potential immunotherapy targets.

RESULTS

We found that BRAF V600E mutation has a complex impact on the immune profile of colorectal cancer. It increases immune cell infiltration and activates immune-related signaling pathways, yet it also severely restricts T cell function. We subsequently identified 39 core genes associated with T cell dysfunction and constructed subtypes of BRAF V600E colorectal cancer based on their expression profiles. Significant heterogeneity was observed between these subtypes in immune signaling pathway activity, immune infiltration patterns, immune phenotype scores, and mechanisms of resistance to immunotherapy. Ultimately, using machine learning algorithms and bioinformatics validation, we identified IDO1 as a potential immunotherapy targets for BRAF V600E-mutant colorectal cancer.

CONCLUSION

This study constructed novel T cell dysfunction molecular subtypes for BRAF V600E-mutant colorectal cancer and identified IDO1 as a potential immunotherapy target, providing a new strategy for immunotherapy.