Single cell dynamics of tumor specificity vs bystander activity in CD8+ T cells define the diverse immune landscapes in colorectal cancer

Functional proteomics of colon cancer Consensus Molecular Subtypes

BACKGROUND

The Colorectal Cancer Subtyping Consortium established four Consensus Molecular Subtypes (CMS) in colorectal cancer: CMS1 (microsatellite-instability [MSI], Immune), CMS2 (Canonical, epithelial), CMS3 (Metabolic), and CMS4 (Mesenchymal). However, only MSI tumour patients have seen a change in their disease management in clinical practice. This study aims to characterise the proteome of colon cancer CMS and broaden CMS's clinical utility.

METHODS

One-hundred fifty-eight paraffin samples from stage II-III colon cancer patients treated with adjuvant chemotherapy were analysed through DIA-based mass-spectrometry proteomics.

RESULTS

CMS1 exhibited overexpression of immune-related proteins, specifically related to neutrophils, phagocytosis, antimicrobial response, and a glycolytic profile. These findings suggested potential therapeutic strategies involving immunotherapy and glycolytic inhibitors. CMS3 showed overexpression of metabolic proteins. CMS2 displayed a heterogeneous protein profile. Notably, two proteomics subtypes within CMS2, with different protein characteristics and prognoses, were identified. CMS4 emerged as the most distinct group, featuring overexpression of proteins related to angiogenesis, extracellular matrix, focal adhesion, and complement activation. CMS4 showed a high metastatic profile and suggested possible chemoresistance that may explain its worse prognosis.

CONCLUSIONS

DIA proteomics revealed new features for each colon cancer CMS subtype. These findings provide valuable insights into potential therapeutic targets for colorectal cancer subtypes in the future.

A spatial architecture-embedding HLA signature to predict clinical response to immunotherapy in renal cell carcinoma

An important challenge in the real-world management of patients with advanced clear-cell renal cell carcinoma (aRCC) is determining who might benefit from immune checkpoint blockade (ICB). Here we performed a comprehensive multiomics mapping of aRCC in the context of ICB treatment, involving discovery analyses in a real-world data cohort followed by validation in independent cohorts. We cross-connected bulk-tumor transcriptomes across >1,000 patients with validations at single-cell and spatial resolutions, revealing a patient-specific crosstalk between proinflammatory tumor-associated macrophages and (pre-)exhausted CD8+ T cells that was distinguished by a human leukocyte antigen repertoire with higher preference for tumoral neoantigens. A cross-omics machine learning pipeline helped derive a new tumor transcriptomic footprint of neoantigen-favoring human leukocyte antigen alleles. This machine learning signature correlated with positive outcome following ICB treatment in both real-world data and independent clinical cohorts. In experiments using the RENCA-tumor mouse model, CD40 agonism combined with PD1 blockade potentiated both proinflammatory tumor-associated macrophages and CD8+ T cells, thereby achieving maximal antitumor efficacy relative to other tested regimens. Thus, we present a new multiomics and spatial map of the immune-community architecture that drives ICB response in patients with aRCC.

CXCR6+CD69+ CD8+ T cells in ascites are associated with disease severity in patients with cirrhosis

Background & Aims

Patients with advanced cirrhosis often develop hepatic decompensation, which is accompanied by systemic inflammation and may eventually lead to acute-on-chronic liver failure. One important cause of systemic hyperinflammation is a dysregulated overshooting immune response in ascites in the abdominal cavity. In this study, we analyzed the role of CD8+ T cells in the ascites immune compartment.

Methods

Peripheral blood and ascites fluid were collected from 50 patients with decompensated cirrhosis. Phenotype and functional responses of CD8+ T cells were analyzed, and obtained data were compared with each other as well as with healthy controls and patients with compensated cirrhosis.

Results

High-dimensional flow cytometry revealed that CD8+ T cells are abundant in the ascites of patients with cirrhosis and exhibit a chronically activated bystander phenotype with innate-like functions. Indeed, we identified distinct CXCR6+CD69+ clusters of late effector memory CD8+ T cells that were rarely found in blood and correlated with clinical parameters of disease severity. Moreover, this CD8+ T-cell population was hyperresponsive to innate cytokines and exhibited cytokine-mediated bystander activation. Interestingly, the Janus kinase (JAK) inhibitor tofacitinib was able to effectively block bystander-activated CXCR6+CD69+ CD8+ T cells and significantly suppress effector molecule production.

Conclusions

The results indicate that CXCR6+CD69+ CD8+ T cells in ascites are associated with disease severity and may contribute to inflammation in patients with decompensated cirrhosis, suggesting that targeted inhibition of this immune cell subset may be a viable therapeutic option.

Impact and Implications

Patients with advanced cirrhosis often develop hepatic decompensation, which is accompanied by systemic inflammation and eventually leads to acute-on-chronic liver failure. One important cause of systemic hyperinflammation is a dysregulated overshooting immune response in ascites in the abdominal cavity. In this study, we demonstrate that CXCR6+CD69+ CD8+ T cells are abundant in the ascites of patients with cirrhosis, exhibit a chronically activated bystander phenotype, and correlate with clinical parameters of disease severity. Moreover, we show that the Janus kinase (JAK) inhibitor tofacitinib can effectively block these bystander-activated CXCR6+CD69+ CD8+ T cells, suggesting that targeted inhibition of this immune cell subset may be a potential therapeutic strategy.

Clinical trial number

Prospective registry: INFEKTA (DRKS00010664).

Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways

BACKGROUND

Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery from genetic data.

METHOD

We propose a Quantum Neural Networks architecture to discover genetic biomarkers for input activation pathways. The Maximum Relevance-Minimum Redundancy criteria score biomarker candidate sets. Our proposed model is economical since the neural solution can be delivered on constrained hardware.

RESULTS

We demonstrate the proof of concept on four activation pathways associated with CTLA4, including (1) CTLA4-activation stand-alone, (2) CTLA4-CD8A-CD8B co-activation, (3) CTLA4-CD2 co-activation, and (4) CTLA4-CD2-CD48-CD53-CD58-CD84 co-activation.

CONCLUSION

The model indicates new genetic biomarkers associated with the mutational activation of CLTA4-associated pathways, including 20 genes: CLIC4, CPE, ETS2, FAM107A, GPR116, HYOU1, LCN2, MACF1, MT1G, NAPA, NDUFS5, PAK1, PFN1, PGAP3, PPM1G, PSMD8, RNF213, SLC25A3, UBA1, and WLS. We open source the implementation at: https://github.com/namnguyen0510/Biomarker-Discovery-with-Quantum-Neural-Networks .

Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine

Colorectal cancer (CRC) is one of the most heterogeneous and deadly diseases, with a global incidence of 1.5 million cases per year. Genomics has revolutionized the clinical management of CRC by enabling comprehensive molecular profiling of cancer. However, a deeper understanding of the molecular factors is needed to identify new prognostic and predictive markers that can assist in designing more effective therapeutic regimens for the improved management of CRC. Recent breakthroughs in single-cell analysis have identified new cell subtypes that play a critical role in tumor progression and could serve as potential therapeutic targets. Spatial analysis of the transcriptome and proteome holds the key to unlocking pathogenic cellular interactions, while liquid biopsy profiling of molecular variables from serum holds great potential for monitoring therapy resistance. Furthermore, gene expression signatures from various pathways have emerged as promising prognostic indicators in colorectal cancer and have the potential to enhance the development of equitable medicine. The advancement of these technologies for identifying new markers, particularly in the domain of predictive and personalized medicine, has the potential to improve the management of patients with CRC. Further investigations utilizing similar methods could uncover molecular subtypes specific to emerging therapies, potentially strengthening the development of personalized medicine for CRC patients.

Lymph node and tumor-associated PD-L1+ macrophages antagonize dendritic cell vaccines by suppressing CD8+ T cells

Current immunotherapies provide limited benefits against T cell-depleted tumors, calling for therapeutic innovation. Using multi-omics integration of cancer patient data, we predict a type I interferon (IFN) responseHIGH state of dendritic cell (DC) vaccines, with efficacious clinical impact. However, preclinical DC vaccines recapitulating this state by combining immunogenic cancer cell death with induction of type I IFN responses fail to regress mouse tumors lacking T cell infiltrates. Here, in lymph nodes (LNs), instead of activating CD4+/CD8+ T cells, DCs stimulate immunosuppressive programmed death-ligand 1-positive (PD-L1+) LN-associated macrophages (LAMs). Moreover, DC vaccines also stimulate PD-L1+ tumor-associated macrophages (TAMs). This creates two anatomically distinct niches of PD-L1+ macrophages that suppress CD8+ T cells. Accordingly, a combination of PD-L1 blockade with DC vaccines achieves significant tumor regression by depleting PD-L1+ macrophages, suppressing myeloid inflammation, and de-inhibiting effector/stem-like memory T cells. Importantly, clinical DC vaccines also potentiate T cell-suppressive PD-L1+ TAMs in glioblastoma patients. We propose that a multimodal immunotherapy and vaccination regimen is mandatory to overcome T cell-depleted tumors.

Single-cell analysis of T lymphocytes infiltrating colorectal carcinoma: the dilemma of specificity

Advances in single-cell RNA and T cell receptor (TCR) sequencing allow to study the specificity and functionality of tumor-infiltrating T lymphocytes. A recent study unravels fundamental differences between microsatellite-instable (MSI) colorectal cancers, in which T cells tend to be tumor-specific, and microsatellite-stable (MSS) cancers, in which T cells exhibit bystander features.

Unraveling the Phenotypic States of Human innate-like T Cells: Comparative Insights with Conventional T Cells and Mouse Models

The "innate-like" T cell compartment, known as Tinn, represents a diverse group of T cells that straddle the boundary between innate and adaptive immunity, having the ability to mount rapid responses following activation. In mice, this ability is acquired during thymic development. We explored the transcriptional landscape of Tinn compared to conventional T cells (Tconv) in the human thymus and blood using single cell RNA sequencing and flow cytometry. We reveal that in human blood, the majority of Tinn cells, including iNKT, MAIT, and Vδ2+Vγ9+ T cells, share an effector program characterized by the expression of unique chemokine and cytokine receptors, and cytotoxic molecules. This program is driven by specific transcription factors, distinct from those governing Tconv cells. Conversely, only a fraction of thymic Tinn cells displays an effector phenotype, while others share transcriptional features with developing Tconv cells, indicating potential divergent developmental pathways. Unlike the mouse, human Tinn cells do not differentiate into multiple effector subsets but develop a mixed type I/type III effector potential. To conduct a comprehensive cross-species analysis, we constructed a murine Tinn developmental atlas and uncovered additional species-specific distinctions, including the absence of type II Tinn cells in humans, which implies distinct immune regulatory mechanisms across species. The study provides insights into the development and functionality of Tinn cells, emphasizing their role in immune responses and their potential as targets for therapeutic interventions.