Roles of HLA-G/KIR2DL4 in Breast Cancer Immune Microenvironment

Peptide-based drugs in immunotherapy: current advances and future prospects

In immunotherapy, peptide-based medications are showing great promise as a new class of therapies that can be used to treat autoimmune diseases, cancer, and other immune-related conditions. Peptides are being created for use in immunotherapy as vaccines, immunological modulators, and adjuvants because of their capacity to precisely alter immune responses. They can imitate endogenous signals or interact with immune cells, improving the body's capacity to identify and combat malignancies or reestablishing immunological tolerance in autoimmune disorders. Notably, peptide-based treatments have demonstrated promise in promoting tumor-specific immune responses and improving the effectiveness of already available immunotherapies, such as immune checkpoint inhibitors. Notwithstanding its potential, peptide-based medications' clinical translation is fraught with difficulties, such as those pertaining to immunogenicity, bioavailability, and peptide stability. Overcoming these obstacles has been made possible by developments in peptide engineering, including pharmacokinetic optimization, receptor-binding affinity enhancement, and the creation of innovative delivery systems. The targeted distribution and effectiveness of peptide medications can be improved by using liposomes, nanoparticles, and other delivery methods, increasing their therapeutic utility. With an emphasis on recent scientific developments, mechanisms of action, and therapeutic uses, this review examines the present status of peptide-based medications in immunotherapy. We also look at the obstacles that still need to be overcome in order to get peptide-based treatments from the lab to the clinic and offer suggestions for future research initiatives. By tackling these important problems, we hope to demonstrate how peptide-based medications have the ability to revolutionize immunotherapeutic treatment approaches.

Unraveling the breast cancer tumor microenvironment: crucial factors influencing natural killer cell function and therapeutic strategies

Natural killer (NK) cells have emerged as a novel and effective treatment for breast cancer. Nevertheless, the breast cancer tumor microenvironment (TME) manifests multiple immunosuppressive mechanisms, impeding the proper execution of NK cell functions. This review summarizes recent research on the influence of the TME on the functionality of NK cells in breast cancer. It delves into the effects of the internal environment of the TME on NK cells and elucidates the roles of diverse stromal components, immune cells, and signaling molecules in regulating NK cell activity within the TME. It also summarizes therapeutic strategies based on small-molecule inhibitors, antibody therapies, and natural products, as well as the progress of research in preclinical and clinical trials. By enhancing our understanding of the immunosuppressive TME and formulating strategies to counteract its effects, we could fully harness the therapeutic promise of NK cells in breast cancer treatment.

Unveiling the key mechanisms of FOLR2+ macrophage-mediated antitumor immunity in breast cancer using integrated single-cell RNA sequencing and bulk RNA sequencing

Breast cancer (BRCA) is a common malignant tumor, and its immune microenvironment plays a crucial role in disease progression. In this research, we utilized single-cell RNA sequencing and bulk RNA sequencing technologies, combined with in vivo and in vitro experiments, to thoroughly investigate the immunological functions and mechanisms of FOLR2+ macrophages in BRCA. Our findings demonstrate a significant enhancement in the interaction between FOLR2+ macrophages and CD8+ T cells within the tumor tissues of BRCA patients. FOLR2 is closely associated with T cell infiltration in the tumor microenvironment of BRCA patients, particularly with CD8+ T cells. By secreting CXCL9 and engaging with CXCR3, FOLR2+ macrophages can activate the functionality of CD8+ T cells, thereby promoting cancer cell apoptosis. Further animal experiments confirm that FOLR2+ macrophages activate CD8+ T cells through the CXCL9-CXCR3 axis, exhibiting an antitumor immunity effect in BRCA. FOLR2+ macrophages play a crucial role in antitumor immunity in BRCA through the CXCL9-CXCR3 axis.

Resistance mechanisms and prospects of trastuzumab

Breast cancer that overexpresses Human Epidermal Growth Factor Receptor 2 (HER2+) due to gene amplification or overexpression constitutes 15-20% of all breast cancer cases. Trastuzumab, the first FDA-approved monoclonal antibody targeting HER2, serves as the standard first-line treatment for HER2-positive advanced breast cancer, as recommended by multiple clinical guidelines.Currently, accumulated clinical evidence reveals a considerable degree of variability in the response of HER2+ breast cancer to trastuzumab treatment. Specifically, over 50% of patients either do not respond to or develop resistance against trastuzumab.The specific mechanisms of resistance to trastuzumab are currently unclear. This paper aims to review the existing research on the resistance mechanisms of trastuzumab, based on its target, from aspects such as genetic loci, molecular structure, signaling pathways, and the tumor microenvironment and to outline current research progress and new strategies.

Establishment and verification of a prognostic immune cell signature-based model for breast cancer overall survival

Background

Breast cancer (BRCA) is a prevalent and aggressive disease. Despite various treatments being applied, a significant number of patients continue to experience unfavorable prognoses. Accurate prognosis prediction in BRCA is crucial for tailoring individualized treatment plans and improving patient outcomes. Recent studies have highlighted the significance of immune cell infiltration in the tumor microenvironment (TME), but predicting survival remains challenging due to the heterogeneity of BRCA. The aim of this study was thus to produce an immune cell signature-based framework capable of predicting the prognosis of patients with BRCA.

Methods

The GSE169246 dataset was from the Gene Expression Omnibus (GEO) database, comprising single-cell RNA sequencing (scRNA-seq) data from 95 individuals with BRCA. Seurat, principal component analysis (PCA), the unified matrix polynomial approach (UMAP) algorithm, and linear dimensionality reduction were used to determine the heterogeneity of T cells. Overlapping analysis of differentially expressed genes (DEGs), genes associated with prognosis, and T-cell pharmacodynamics-related genes were used to obtain the T-cell core pharmacodynamics-related genes. The dimensionality of the T-cell core pharmacodynamics-related genes was reduced employing the least absolute shrinkage and selection operator (LASSO) Cox regression model and the LASSO model. The prognostic model was built via a Cox analysis of the overall survival (OS) information. The clinical sample included 95 patients with BRCA who underwent surgical treatment from October 2018 to October 2021 at the Second Affiliated Hospital of Qiqihar Medical University. Patients were divided into a good prognosis group and a poor prognosis group based on their prognostic outcomes. The predictive value of tumor characteristics and immune responses was validated through correlation analysis, logistic regression analysis, and receiver operating characteristic (ROC) analysis.

Results

A group of 95 genes was used to establish a prognostic model. In the GEO clinical sample, with a high-risk group demonstrating shorter median survival times (2,447 vs. 6,498 days, P=4.733e-12). Area under the curve (AUC) values of 0.75, 0.75, and 0.72 were obtained for 2-, 4-, and 6-year OS predictions, respectively. Clinical validation found that the 6-year OS of the favorable prognosis group was significantly higher than that of the unfavorable prognosis group (92.06% vs. 65.62%; P=0.005). Poor prognosis was positively correlated with age, tumor size, B-cell level, and CTLA4 level and negatively correlated with tumor stage (T1/T2), lymph node metastasis stage (N0), clinical stage I-II, CD3+T-cell, CD4+T-cell, CD8+T-cell, neutrophil, lymphocyte, natural kill cell, TIGIT expression and OS. The combined model of clinical parameters had an AUC value of 0.898.

Conclusions

This study established a prognostic model that demonstrated excellent predictive value for OS of BRCA. The predictive model developed offers valuable insights into prognosis and treatment planning, emphasizing the importance of tumor characteristics and immune cell infiltration.

Construction and validation of a SASP-related prognostic signature in patients with acute myeloid leukaemia

Acute myeloid leukaemia (AML) is a common and highly aggressive haematological malignancy in adults. Senescence-associated secretory phenotype (SASP) plays important roles in tumorigenesis and progression of tumour. However, the prognostic value of SASP in patients with AML has not been clarified. The present study aims to explore the prognostic value of SASP and develop a prognostic risk signature for AML. The RNA-sequencing data was collected from the TCGA, GTEx and TARGET databases. Subsequently, differentially expressed gene analysis, univariate Cox regression and LASSO regression were applied to identified prognostic SASP-related genes and construct a prognostic risk-scoring model. The risk score of each patient were calculated and patients were divided into high- or low-risk groups by the median risk score. This novel prognostic signature included 11 genes: G6PD, CDK4, RPS6KA1, UBC, H2BC12, KIR2DL4, HSF1, IFIT3, PIM1, RUNX3 and TRIM21. The patients with AML in the high-risk group had shorter OS, demonstrating that the risk score acted as a prognostic predictor, which was validated in the TAGET-AML dataset. Univariate and multivariate analysis revealed the risk score was an independent prognostic factor in patients with AML. Furthermore, the present study revealed that the risk score was associated with immune landscape, immune checkpoint gene expression and chemotherapeutic efficacy. In the present study, we constructed and validated a unique SASP-related prognostic model to assess therapeutic effect and prognosis in patients with AML, which might contribute to understanding the role of SASP in AML and guiding the treatment for AML.

The prognostic genes model of breast cancer drug resistance based on single-cell sequencing analysis and transcriptome analysis

Breast cancer (BC) represents a multifaceted malignancy, with escalating incidence and mortality rates annually. Chemotherapy stands as an indispensable approach for treating breast cancer, yet drug resistance poses a formidable challenge. Through transcriptome data analysis, we have identified two sets of genes exhibiting differential expression in this context. Furthermore, we have confirmed the overlap between these genes and those associated with exosomes, which were subsequently validated in cell lines. The investigation screened the identified genes to determine prognostic markers for BC and utilized them to formulate a prognostic model. The disparities in prognosis and immunity between the high- and low-risk groups were validated using the test dataset. We have discerned different BC subtypes based on the expression levels of prognostic genes in BC samples. Variations in prognosis, immunity, and drug sensitivity among distinct subtypes were examined. Leveraging data from single-cell sequencing and prognostic gene expression, the AUCell algorithm was employed to score individual cell clusters and analyze the pathways implicated in high-scoring groups. Prognostic genes (CCT4, CXCL13, MTDH, PSMD2, and RAB27A) were subsewoquently validated using RT-qPCR. Consequently, we have established a model for predicting prognosis in breast cancer that hinges on drug resistance and ERGs. Furthermore, we have evaluated the prognostic value of this model. The genes identified as prognostic markers can now serve as a reference for precise treatment of this condition.

Impact of HLA Class I Antigen, Killer Inhibitory Receptor, and FCGR3A Genotypes on Breast Cancer Susceptibility and Tumor Stage

BACKGROUND

The identification in breast cancer (BC) of novel genetic biomarkers regulating natural killer (NK) cell function, including the HLA, KIR, and CD16A (FCGR3A), may be still a challenge.

OBJECTIVE

We aimed to evaluate whether the combined effect of these polymorphisms has an impact on BC susceptibility and progression.

METHODS

47 BC Italian patients and healthy individuals (39 females and 66 males/ females) were genotyped by Sanger sequencing (HLA-C exon 2-4 and FCGR3A- 158V/F, 48L/R/H) and PCR-SSP typing (KIR genes).

RESULTS

HLA-C gene allele analysis showed the group C1, with HLA-C*07:02:01 allele, to be significantly associated with tumor progression (16.7% vs. 4.0%, p=0.04, OR=4.867), and instead, group C2, with HLA-C*05:01:01, was protective against disease susceptibility (0.0% vs. 7.2%, p=0.019, OR=0.087). In addition, we highlighted a significant reduction of the KIR2DS4ins in BC patients (pcorr.=0.022) and an increased combined presence of KIR2DL1 and KIR2DS1 genes in advanced BC patients compared to earlier stages (66.7% vs. 19.2%, p=0.002). The concurrent lack of KIR2DL2 and KIR2DS4 genes in the presence of HLA-C2 alleles was significantly associated with increased susceptibility to BC (p=0.012, OR=5.020) or with lymph node involvement (p=0.008, OR=6.375). Lastly, we identified different combinations of the FCGR3A-48/158 variants and KIR genes in BC patients compared to controls.

CONCLUSION

Our findings suggest that in the development of BC probably exists a disorder of the NK innate immunity influenced by KIR/HLA-C gene content and FCGR3A-158 polymorphisms and that the combined analysis of these biomarkers might help predict genetic risk scores for tailored screening of BC patients in therapy.

Prognostic significance of HLA-G in patients with colorectal cancer: a meta-analysis and bioinformatics analysis

PURPOSE

Human leukocyte antigen-G (HLA-G) has been reported to be aberrantly expressed in colorectal cancer (CRC); however, its prognostic value remains controversial. Hence, our meta-analysis aims to assess the prognostic value of HLA-G in CRC patients based on published literature and The Cancer Genome Atlas (TCGA) datasets.

METHODS

A systematic search was conducted on relevant studies retrieved from four electronic databases including PubMed, Embase, Web of Science and Cochrane Library. Hazard ratios (HRs) with 95% confidence intervals (CIs) were recorded to be applied as effective values. Fixed-effects models or random-effects models were applied on the basis of the value of heterogeneity (I 2). Publication bias was analyzed by Begg's and Egger's tests. In addition, the results were validated by using TCGA datasets.

RESULTS

Thirteen studies comprising 3896 patients were incorporated into this meta-analysis. The pooled results showed that HLA-G expression was significantly associated with poor overall survival (OS) in both the univariate analysis (HR = 1.44, 95% CI: 1.14-1.83, P = 0.002) and the multivariate analysis (HR = 1.55, 95% CI: 1.23-1.95, P < 0.001). Nevertheless, the expression of HLA-G is not related to age, sex, tumor type, tumor differentiation, TNM stage, or distant metastasis but lymph node metastasis. Notably, the prognosis of colorectal cancer was not consistent with the analysis result from TCGA data.

CONCLUSION

HLA-G expression was significantly related to poor OS in CRC according to the results of our meta-analysis. However, we found that the prognostic significance was inconsistent with our results according to the TCGA data in CRC. Hence, more research is still needed to further illustrate the prognostic role of HLA-G in CRC.

Revisiting Concurrent Radiation Therapy, Temozolomide, and the Histone Deacetylase Inhibitor Valproic Acid for Patients with Glioblastoma-Proteomic Alteration and Comparison Analysis with the Standard-of-Care Chemoirradiation

BACKGROUND

Glioblastoma (GBM) is the most common brain tumor with an overall survival (OS) of less than 30% at two years. Valproic acid (VPA) demonstrated survival benefits documented in retrospective and prospective trials, when used in combination with chemo-radiotherapy (CRT).

PURPOSE

The primary goal of this study was to examine if the differential alteration in proteomic expression pre vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA as compared to standard-of-care CRT. The second goal was to explore the associations between the proteomic alterations in response to VPA/RT/TMZ correlated to patient outcomes. The third goal was to use the proteomic profile to determine the mechanism of action of VPA in this setting.

MATERIALS AND METHODS

Serum obtained pre- and post-CRT was analyzed using an aptamer-based SOMAScan® proteomic assay. Twenty-nine patients received CRT plus VPA, and 53 patients received CRT alone. Clinical data were obtained via a database and chart review. Tests for differences in protein expression changes between radiation therapy (RT) with or without VPA were conducted for individual proteins using two-sided t-tests, considering p-values of <0.05 as significant. Adjustment for age, sex, and other clinical covariates and hierarchical clustering of significant differentially expressed proteins was carried out, and Gene Set Enrichment analyses were performed using the Hallmark gene sets. Univariate Cox proportional hazards models were used to test the individual protein expression changes for an association with survival. The lasso Cox regression method and 10-fold cross-validation were employed to test the combinations of expression changes of proteins that could predict survival. Predictiveness curves were plotted for significant proteins for VPA response (p-value < 0.005) to show the survival probability vs. the protein expression percentiles.

RESULTS

A total of 124 proteins were identified pre- vs. post-CRT that were differentially expressed between the cohorts who received CRT plus VPA and those who received CRT alone. Clinical factors did not confound the results, and distinct proteomic clustering in the VPA-treated population was identified. Time-dependent ROC curves for OS and PFS for landmark times of 20 months and 6 months, respectively, revealed AUC of 0.531, 0.756, 0.774 for OS and 0.535, 0.723, 0.806 for PFS for protein expression, clinical factors, and the combination of protein expression and clinical factors, respectively, indicating that the proteome can provide additional survival risk discrimination to that already provided by the standard clinical factors with a greater impact on PFS. Several proteins of interest were identified. Alterations in GALNT14 (increased) and CCL17 (decreased) (p = 0.003 and 0.003, respectively, FDR 0.198 for both) were associated with an improvement in both OS and PFS. The pre-CRT protein expression revealed 480 proteins predictive for OS and 212 for PFS (p < 0.05), of which 112 overlapped between OS and PFS. However, FDR-adjusted p values were high, with OS (the smallest p value of 0.586) and PFS (the smallest p value of 0.998). The protein PLCD3 had the lowest p-value (p = 0.002 and 0.0004 for OS and PFS, respectively), and its elevation prior to CRT predicted superior OS and PFS with VPA administration. Cancer hallmark genesets associated with proteomic alteration observed with the administration of VPA aligned with known signal transduction pathways of this agent in malignancy and non-malignancy settings, and GBM signaling, and included epithelial-mesenchymal transition, hedgehog signaling, Il6/JAK/STAT3, coagulation, NOTCH, apical junction, xenobiotic metabolism, and complement signaling.

CONCLUSIONS

Differential alteration in proteomic expression pre- vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA. Using pre- vs. post-data, prognostic proteins emerged in the analysis. Using pre-CRT data, potentially predictive proteins were identified. The protein signals and hallmark gene sets associated with the alteration in the proteome identified between patients who received VPA and those who did not, align with known biological mechanisms of action of VPA and may allow for the identification of novel biomarkers associated with outcomes that can help advance the study of VPA in future prospective trials.

Perturbed epigenetic transcriptional regulation in AML with IDH mutations causes increased susceptibility to NK cells

Isocitrate dehydrogenase (IDH) mutations are found in 20% of acute myeloid leukemia (AML) patients. However, only 30-40% of the patients respond to IDH inhibitors (IDHi). We aimed to identify a molecular vulnerability to tailor novel therapies for AML patients with IDH mutations. We characterized the transcriptional and epigenetic landscape with the IDH2i AG-221, using an IDH2 mutated AML cell line model and AML patient cohorts, and discovered a perturbed transcriptional regulatory network involving myeloid transcription factors that were partly restored after AG-221 treatment. In addition, hypermethylation of the HLA cluster caused a down-regulation of HLA class I genes, triggering an enhanced natural killer (NK) cell activation and an increased susceptibility to NK cell-mediated responses. Finally, analyses of DNA methylation data from IDHi-treated patients showed that non-responders still harbored hypermethylation in HLA class I genes. In conclusion, this study provides new insights suggesting that IDH mutated AML is particularly sensitive to NK cell-based personalized immunotherapy.

HLA-G 14 bp Ins/Del (rs66554220) Variant Is Not Associated with Breast Cancer in Women from Western Mexico

HLA-G is a physiology and pathologic immunomodulator detrimentally related to cancer. Its gene is heavily transcriptionally and post-transcriptionally regulated by variants located in regulator regions like 3'UTR, being the most studied Ins/Del of 14-bp (rs66554220), which is known to influence the effects of endogen cell factors; nevertheless, the reports are discrepant and controversial. Herein, the relationship of the 14-bp Ins/Del variant (rs66554220) with breast cancer (BC) and its clinical characteristics were analyzed in 182 women with non-familial BC and 221 disease-free women as a reference group. Both groups from western Mexico and sex-age-matched (sm-RG). The rs66554220 variant was amplified by SSP-PCR and the fragments were visualized in polyacrylamide gel electrophoresis. The variant rs66554220 was not associated with BC in our population. However, we suggest the Ins allele as a possible risk factor for developing BC at clinical stage IV (OR = 3.05, 95% CI = 1.16-7.96, p = 0.01); nevertheless, given the small stratified sample size (n = 11, statistical power = 41%), this is inconclusive. In conclusion, the 14-bp Ins/Del (rs66554220) variant of HLA-G is not associated with BC in the Mexican population, but might be related to advanced breast tumors. Further studies are required.

Dimerization of Transmembrane Proteins in Cancer Immunotherapy

Transmembrane proteins (TMEMs) are integrated membrane proteins that span the entire lipid bilayer and are permanently anchored to it. TMEMs participate in various cellular processes. Some TMEMs usually exist and perform their physiological functions as dimers rather than monomers. TMEM dimerization is associated with various physiological functions, such as the regulation of enzyme activity, signal transduction, and cancer immunotherapy. In this review, we focus on the dimerization of transmembrane proteins in cancer immunotherapy. This review is divided into three parts. First, the structures and functions of several TMEMs related to tumor immunity are introduced. Second, the characteristics and functions of several typical TMEM dimerization processes are analyzed. Finally, the application of the regulation of TMEM dimerization in cancer immunotherapy is introduced.

Managing the immune microenvironment of osteosarcoma: the outlook for osteosarcoma treatment

Osteosarcoma, with poor survival after metastasis, is considered the most common primary bone cancer in adolescents. Notwithstanding the efforts of researchers, its five-year survival rate has only shown limited improvement, suggesting that existing therapeutic strategies are insufficient to meet clinical needs. Notably, immunotherapy has shown certain advantages over traditional tumor treatments in inhibiting metastasis. Therefore, managing the immune microenvironment in osteosarcoma can provide novel and valuable insight into the multifaceted mechanisms underlying the heterogeneity and progression of the disease. Additionally, given the advances in nanomedicine, there exist many advanced nanoplatforms for enhanced osteosarcoma immunotherapy with satisfactory physiochemical characteristics. Here, we review the classification, characteristics, and functions of the key components of the immune microenvironment in osteosarcoma. This review also emphasizes the application, progress, and prospects of osteosarcoma immunotherapy and discusses several nanomedicine-based options to enhance the efficiency of osteosarcoma treatment. Furthermore, we examine the disadvantages of standard treatments and present future perspectives for osteosarcoma immunotherapy.

HLA-G 3'UTR polymorphism diplotypes and soluble HLA-G plasma levels impact cervical cancer susceptibility and prognosis

Background

Human leukocyte antigen G (HLA-G) is an immune checkpoint molecule with relevance in several cancers. The aim of this study was to evaluate the potential role of soluble HLA-G (sHLA-G), its genetic polymorphisms and its haplotype structure in the susceptibility and prognosis of primary cervical cancer in a Chinese Han population.

Methods

We investigated sHLA-G plasma levels and 3' untranslated region (3'UTR) polymorphisms through ELISA and direct DNA sequencing, respectively, in cervical cancer patients (120 cases) and healthy control women (96 cases). The data were analyzed for associations using PowerMarker, Haploview, and GraphPad Prism.

Results

In this study, 8 polymorphic sites, 16 haplotypes and 23 diplotypes in the HLA-G 3'UTR were identified in our study population. We observed that each pair of 8 polymorphic sites exhibited linkage disequilibrium. The heterozygote CT genotype at position +3422 (rs17875408) was more common in cervical cancer patients than in healthy women (OR=5.285, P<0.05). Haplotypes UTR-1, UTR-3, and UTR-7 accounted for more than 85% of both groups, but no significant difference was found. The frequency of the UTR-1/UTR-3 diplotype in patients was significantly higher than that in controls (P<0.05). In addition, we further observed that HLA-G 3'UTR polymorphisms may influence the sHLA-G plasma level in patients' peripheral blood, especially 14 bp Ins/Del (rs371194629) and +3142 C/G (rs1063320). A receiver operating characteristic (ROC) curve analysis showed that the sHLA-G level had good diagnostic performance in differentiating patients with cervical cancer from healthy women (AUC>0.7). Among patients, mean sHLA-G levels increased with increasing FIGO stages but were not related to the overall survival time.

Conclusions

The results of the present study enhance our understanding of how HLA-G 3'UTR polymorphisms can influence the peripheral sHLA-G plasma level and play a key role in cervical carcinogenesis. This study further confirmed that sHLA-G may represent a novel plasma biomarker for the prognosis and potential therapeutic target of cervical cancer.

Multiplexed In Situ Spatial Protein Profiling in the Pursuit of Precision Immuno-Oncology for Patients with Breast Cancer

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of many solid tumors. In breast cancer (BC), immunotherapy is currently approved in combination with chemotherapy, albeit only in triple-negative breast cancer. Unfortunately, most patients only derive limited benefit from ICIs, progressing either upfront or after an initial response. Therapeutics must engage with a heterogeneous network of complex stromal-cancer interactions that can fail at imposing cancer immune control in multiple domains, such as in the genomic, epigenomic, transcriptomic, proteomic, and metabolomic domains. To overcome these types of heterogeneous resistance phenotypes, several combinatorial strategies are underway. Still, they can be predicted to be effective only in the subgroups of patients in which those specific resistance mechanisms are effectively in place. As single biomarker predictive performances are necessarily suboptimal at capturing the complexity of this articulate network, precision immune-oncology calls for multi-omics tumor microenvironment profiling in order to identify unique predictive patterns and to proactively tailor combinatorial treatments. Multiplexed single-cell spatially resolved tissue analysis, through precise epitope colocalization, allows one to infer cellular functional states in view of their spatial organization. In this review, we discuss-through the lens of the cancer-immunity cycle-selected, established, and emerging markers that may be evaluated in multiplexed spatial protein panels to help identify prognostic and predictive patterns in BC.

Drug-resistant HER2-positive breast cancer: Molecular mechanisms and overcoming strategies

Breast cancer is one of the most common malignancies and the leading cause of cancer-related death in women. HER2 overexpression is a factor for poor prognosis in breast cancer, and anti-HER2 therapy improves survival in these patients. A dual-targeted combination of pertuzumab and trastuzumab, alongside cytotoxic chemotherapy, constitutes the primary treatment option for individuals with early-stage, HER2-positive breast cancer. Antibody-drug conjugate (ADC) and tyrosine kinase inhibitors (TKI) also increase the prognosis for patients with metastatic breast cancer. However, resistance to targeted therapy eventually occurs. Therefore, it is critical to investigate how HER2-positive breast cancer is resistant to targeted therapy and to develop novel drugs or strategies to overcome the resistance simultaneously. This review aims to provide a comprehensive discussion of the HER2-targeted agents currently in clinical practice, the molecular mechanisms of resistance to these drugs, and the potential strategies for overcoming resistance.

Interaction between human leukocyte antigen (HLA-C) and killer cell Ig-like receptors (KIR2DL) inhibits the cytotoxicity of natural killer cells in patients with hepatoblastoma

BACKGROUND

Hepatoblastoma (HB) is the most common liver malignancy in childhood with poor prognosis and lack of effective therapeutic targets. Single-cell transcriptome sequencing technology has been widely used in the study of malignant tumors, which can understand the tumor microenvironment and tumor heterogeneity.

MATERIALS AND METHODS

Two children with HB and a healthy child were selected as the research subjects. Peripheral blood and tumor tissue were collected for single-cell transcriptome sequencing, and the sequencing data were compared and analyzed to describe the differences in the immune microenvironment between children with HB and normal children.

RESULTS

There were significant differences in the number and gene expression levels of natural killer cells (NK cells) between children with HB and normal children. More natural killer cells were seen in children with HB compared to normal control. KIR2DL were highly expressed in children with HB.

CONCLUSION

Single-cell transcriptome sequencing of peripheral blood mononuclear cells (PBMC) and tumor tissue from children with HB revealed that KIR2DL was significantly up-regulated in NK cells from children with HB. HLA-C molecules on the surface of tumor cells interact with inhibitory receptor KIR2DL on the surface of NK cells, inhibiting the cytotoxicity of NK cells, resulting in immune escape of tumors. Inhibitors of related immune checkpoints to block the interaction between HLA-C and KIR2DL and enhance the cytotoxicity of NK cells, which may be a new strategy for HB treatment.