MDR1-EXPRESSING CD4+ T CELLS WITH TH1.17 FEATURES RESIST TO NEOADJUVANT CHEMOTHERAPY AND ARE ASSOCIATED WITH BREAST CANCER CLINICAL RESPONSE

Anoikis-related genes in breast cancer patients: reliable biomarker of prognosis

BACKGROUND

Breast cancer (BC) is the most common cancer in women, and its progression is closely related to the phenomenon of anoikis. Anoikis, the specific programmed death resulting from a lack of contact between cells and the extracellular matrix, has recently been recognized as playing a critical role in tumor initiation, maintenance, and treatment. The ability of cancer cells to resist anoikis leads to cancer progression and metastatic colonization. However, the impact of anoikis on the prognosis of BC patients remains unclear.

METHOD

This study utilized data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to collect transcriptome and clinical data of BC patients. Anoikis-related genes (ARGs) were classified into subtypes A and B through consensus clustering. Subsequently, survival prognosis analysis, immune cell infiltration analysis, and functional enrichment analysis were performed for both subtypes. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a set of 10 ARGs related to prognosis was identified. Immune cell infiltration and tumor microenvironment analyses were conducted on these 10 ARGs to develop a prognostic model. Furthermore, single-cell data analysis and real-time polymerase chain reaction (RT-PCR) analysis were employed to study the expression of the 10 identified prognostic ARGs in BC cells.

RESULTS

One hundred thirty-five ARGs were identified as differentially expressed genes in the TCGA and GEO databases, with 42 of them associated with the survival prognosis of BC patients. Analyses involving Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP) revealed distinct expression patterns of ARGs between types A and B. Patients in type A exhibited worse survival prognosis and lower immune cell infiltration compared to type B. Subsequent analyses identified 10 key ARGs (YAP1, PIK3R1, BAK1, PHLDA2, EDA2R, LAMB3, CD24, SLC2A1, CDC25C, and SLC39A6) relevant to BC prognosis. Kaplan-Meier analysis indicated that high-risk patients based on these ARGs had a poorer BC prognosis. Additionally, Cox regression analysis established gender, age, T (tumor), N (nodes), and risk score as predictive factors in a nomogram model for BC. The model demonstrated diagnostic value for BC patients at 1, 3, and 5 years. Decision curve analysis (DCA) verified the risk score as a reliable predictor of BC patient survival rates. Moreover, RT-PCR results confirmed differential expressions of YAP1, PIK3R1, BAK1, PHLDA2, CD24, SLC2A1, and CDC25C in BC cells, with SLC39A6, EDA2R, and LAMB3 showing low expression levels.

CONCLUSION

ARGs markers can be used as BC biomarkers for risk stratification and survival prediction in BC patients. Besides, ARGs can be used as stratification factors for individualized and precise treatment of BC patients.

The ubiquitin-proteasome system in the tumor immune microenvironment: a key force in combination therapy

The ubiquitin-proteasome system (UPS) plays a crucial role in modulating the proliferation, activation, and normal functioning of immune cells through the regulation of protein degradation and function. By influencing the expression of immune checkpoint-associated proteins, the UPS modulates T cell-mediated anti-tumor immune responses and can potentially facilitate the immune escape of tumor cells. Additionally, the UPS contributes to the remodeling of the tumor immunosuppressive microenvironment (TIME) by regulating B cells, dendritic cells (DCs), macrophages, and Treg cells. Targeting the UPS in conjunction with immune checkpoint-associated proteins, and combining these with other therapeutic approaches, may significantly enhance the efficacy of combination therapies and pave the way for novel cancer treatment strategies. In this review, we first summarize the composition and alterations of the TIME, with a particular emphasis on the role of the UPS in TIME and its interactions with various immune cell types. Finally, we explore the potential of combining UPS-targeted therapies with immunotherapy to substantially improve the effectiveness of immunotherapy and enhance patient survival outcomes.

Enhancing breast cancer treatment through pharmacogenomics: A narrative review

Pharmacogenomics has become integral to personalised medicine in breast cancer, utilising genetic insights to customize treatment strategies and enhance patient outcomes. Understanding how genetic variations influence drug metabolism, response, and toxicity is crucial for guiding treatment selection and dosing regimens. Genetic polymorphisms in drug-metabolizing enzymes and transporters significantly impact pharmacokinetic variability, influencing the efficacy and safety of chemotherapy agents and targeted therapies. Biomarkers associated with the hormone receptor status of breast cancer and mutations serve as key determinants of treatment response, aiding in the selection of therapies. Despite substantial progress in understanding the pharmacogenomic landscape of breast cancer, efforts to identify novel genetic markers and refine treatment optimisation strategies are required. Genome-wide association studies and advanced sequencing technologies hold promise for uncovering genetic determinants of drug response variability and elucidating complex pharmacogenomic interactions. The future of pharmacogenomics in breast cancer lies in real-time treatment monitoring, the discovery of additional predictive markers, and the seamless integration of pharmacogenomic data into clinical decision-making processes. However, translating pharmacogenomic discoveries into routine clinical practice requires collaborative efforts among stakeholders to address implementation challenges and ensure equitable access to genetic testing. By embracing pharmacogenomics, clinicians can tailor treatment approaches to individual patients, maximizing therapeutic benefits while minimizing adverse effects. This review discusses the integration of pharmacogenomics in breast cancer treatment, highlighting the significance of understanding genetic influences on treatment response and toxicity, and the potential of advanced technologies in refining treatment strategies.

Distinct host preconditioning regimens differentially impact the antitumor potency of adoptively transferred Th17 cells

BACKGROUND

How distinct methods of host preconditioning impact the efficacy of adoptively transferred antitumor T helper cells is unknown.

METHODS

CD4+ T cells with a transgenic T-cell receptor that recognize tyrosinase-related peptide (TRP)-1 melanoma antigen were polarized to the T helper 17 (Th17) phenotype and then transferred into melanoma-bearing mice preconditioned with either total body irradiation or chemotherapy.

RESULTS

We found that preconditioning mice with a non-myeloablative dose of total body irradiation (TBI of 5 Gy) was more effective than using an equivalently dosed non-myeloablative chemotherapy (cyclophosphamide (CTX) of 200 mg/kg) at augmenting therapeutic activity of antitumor TRP-1 Th17 cells. Antitumor Th17 cells engrafted better following preconditioning with TBI and regressed large established melanoma in all animals. Conversely, only half of mice survived long-term when preconditioned with CTX and infused with anti-melanoma Th17 cells. Interleukin (IL)-17 and interferon-γ, produced by the infused Th17 cells, were detected in animals given either TBI or CTX preconditioning. Interestingly, inflammatory cytokines (granulocyte colony stimulating factor, IL-6, monocyte chemoattractant protein-1, IL-5, and keratinocyte chemoattractant) were significantly elevated in the serum of mice preconditioned with TBI versus CTX after Th17 therapy. The addition of fludarabine (FLU, 200 mg/kg) to CTX (200 mg/kg) improved the antitumor response to the same degree mediated by TBI, whereas FLU alone with Th17 therapy was ineffective.

CONCLUSIONS

Our results indicate, for the first time, that the antitumor response, persistence, and cytokine profiles resulting from Th17 therapy are impacted by the specific regimen of host preconditioning. This work is important for understanding mechanisms that promote long-lived responses by adoptive cellular therapy, particularly as CD4+ based T-cell therapies are now emerging in the clinic.

Single-cell transcriptome reveals highly complement activated microglia cells in association with pediatric tuberculous meningitis

Background

Tuberculous meningitis (TBM) is a devastating form of tuberculosis (TB) causing high mortality and disability. TBM arises due to immune dysregulation, but the underlying immune mechanisms are unclear.

Methods

We performed single-cell RNA sequencing on peripheral blood mononuclear cells (PBMCs) and cerebrospinal fluid (CSF) cells isolated from children (n=6) with TBM using 10 xGenomics platform. We used unsupervised clustering of cells and cluster visualization based on the gene expression profiles, and validated the protein and cytokines by ELISA analysis.

Results

We revealed for the first time 33 monocyte populations across the CSF cells and PBMCs of children with TBM. Within these populations, we saw that CD4_C04 cells with Th17 and Th1 phenotypes and Macro_C01 cells with a microglia phenotype, were enriched in the CSF. Lineage tracking analysis of monocyte populations revealed myeloid cell populations, as well as subsets of CD4 and CD8 T-cell populations with distinct effector functions. Importantly, we discovered that complement-activated microglial Macro_C01 cells are associated with a neuroinflammatory response that leads to persistent meningitis. Consistently, we saw an increase in complement protein (C1Q), inflammatory markers (CRP) and inflammatory factor (TNF-α and IL-6) in CSF cells but not blood. Finally, we inferred that Macro_C01 cells recruit CD4_C04 cells through CXCL16/CXCR6.

Discussion

We proposed that the microglial Macro_C01 subset activates complement and interacts with the CD4_C04 cell subset to amplify inflammatory signals, which could potentially contribute to augment inflammatory signals, resulting in hyperinflammation and an immune response elicited by Mtb-infected tissues.

Distinct host preconditioning regimens differentially impact the antitumor potency of adoptively transferred Th17 cells

Background

Mechanisms by which distinct methods of host preconditioning impact the efficacy of adoptively transferred antitumor T helper cells is unknown.

Methods

CD4 + T cells with a transgenic TCR that recognize TRP-1 melanoma antigen were polarized to the T helper 17 (Th17) phenotype and then transferred into melanoma-bearing mice preconditioned with either total body irradiation or chemotherapy.

Results

We found that preconditioning mice with a non-myeloablative dose of total body irradiation (TBI of 5 Gy) was more effective than using an equivalently dosed non-myeloablative chemotherapy (CTX at 200 mg/kg) at augmenting therapeutic activity of anti-tumor TRP-1 Th17 cells. Anti-tumor Th17 cells engrafted better following preconditioning with TBI and regressed large established melanoma in all animals. Conversely, only half of mice survived long-term when preconditioned with CTX and infused with anti-melanoma Th17 cells. IL-17 and IFN-g produced by the infused Th17 cells, were detected in animals given either TBI or CTX preconditioning. Interestingly, inflammatory cytokines (G-CSF, IL-6, MCP-1, IL-5, and KC) were significantly elevated in the serum of mice preconditioned with TBI versus CTX after Th17 therapy.

Conclusions

Our results indicate, for the first time, that the antitumor response, persistence, and cytokine profiles resulting from Th17 therapy are impacted by the specific regimen of host preconditioning. This work is important for understanding mechanisms that promote long-lived responses by ACT, particularly as CD4 + based T cell therapies are now emerging in the clinic.