Tumor Mutation Burden and Immune Invasion Characteristics in Triple Negative Breast Cancer: Genome High-Throughput Data Analysis

Modulatory Effects of XIAOPI Formula on CXCL1 and Selected Outcomes in Triple-Negative Breast Cancer: A Randomized Controlled Clinical Trial

Background

Triple-negative breast cancer (TNBC) is the most aggressive malignancy. Psychological distress and elevated CXCL1 level have been reported to be closely associated with the poor prognosis and quality of life of patients with TNBC. In preclinical studies using xenograft mouse models, XIAOPI formula, a nationally approved drug prescribed to patients at high risk for breast cancer, inhibited CXCL1 expression and improved survival. Traditional Chinese medicine has unique advantages in improving patients' emotional disorders and quality of life. However, the impact of XIAOPI formula on the serum level of CXCL1, psychological distress, and quality of life among patients with TNBC is currently unknown.

Methods

In this study, we designed a randomized, double-blind, placebo-controlled trial. Patients with TNBC were randomly assigned to receive either the XIAOPI formula or a placebo for three months. The primary outcomes include serum CXCL1 expression, Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS). Secondary outcomes included the Pittsburgh Sleep Quality Index (PSQI) and the Functional Assessment of Cancer Therapy-Breast (FACT-B).

Results

A total of 60 patients with TNBC were enrolled in the investigation. The results showed that the XIAOPI formula significantly decreased CXCL1 expression compared with the control group. Moreover, in comparison to the placebo, the XIAOPI formula increased FACT-B scores while decreasing SDS, SAS, and PSQI scores.

Conclusion

In patients with TNBC, XIAOPI formula may be effective in reducing CXCL1 levels, enhancing psychological well-being, and quality of life. While our research offers a natural alternative therapy that may enhance the prognosis of TNBC, future validation of its therapeutic effects will require large-scale, long-term clinical trials.

Clinical Registration Number

Registration website: www.chictr.org.cn, Registration date: 2018-1-19, Registration number: ChiCTR1800014535.

Tumour mutation burden and infiltrating immune cell subtypes influenced the breast cancer prognosis

Background

Most of its issues are still undecided on the relationship between tumour mutation burden (TMB) and immune-related genes in the breast cancer. This study explores their relationship based on gene mutation and transcription data in The Cancer Genome Atlas (TCGA) database, and the effects of immune cells in TMB and tumour microenvironments on prognosis of breast cancer patients.

Methods

Cases were divided into low-TMB and high-TMB subgroups. Differentially expressed immune-related genes were identified in different TMB subgroups, and patient prognosis was predicted by gene function enrichment analysis, invasive immune cells and different clinical pathological features were compared among different TMB subgroups.

Results

A total of 986 mutation data from breast cancer patients were obtained. Compared with low-TMB group, the survival period of high-TMB group was relatively longer. A total of 337 differential expression genes were identified in this study. Of these genes, seven differentially expressed immune-related genes were associated with prognosis. In the high-TMB group, activated CD4+ memory T cells and other cells had high expression, the expression ratio of memory B cells and other cells in low-TMB group was high.

Conclusions

TMB-related immunological infiltration characteristics showed meaningful value for prognosis prediction for breast cancer patients. Differentially expressed immune-related genes in TMB subgroups provide important information on the survival prediction.

Antitumor immunity and prognosis value elicited by FAT3 and LRP1B co-mutation in endometrial cancer

OBJECTIVE

FAT3 and LRP1B are two tumor suppressor genes with high mutation frequency in multiple cancer types, we sought to investigate the prognostic and immunological significance of these two genes in EC.

METHODS

Based on a cohort of 502 EC samples, we conducted a comprehensive analysis of its multidimensional data types including genomic, transcriptomic, and clinical information, the potential impact of FAT3 and LRP1B co-mutation on antitumor immune response and prognosis were systematically discussed.

RESULTS

We observed that FAT3 and LRP1B co-mutation was not only defined a dataset with prominently increased TMB, decreased tumor aneuploidy, and specially enriched in MSI-H subtype, but also manifested increased expression of immune-related markers, especially exclusive upregulation of PD-L1 levels and higher PD-L1+/CD8A+ proportion. Further analysis focused on lymphocyte infiltration and pathway enrichment explored the immune cell composition of the microenvironment and underlying molecular mechanisms affecting tumor development. Furthermore, EC patients with FAT3 and LRP1B co-mutation possessed significantly prolonged PFS and OS, and the co-mutation status was proved to be an independent prognostic factor. And a nomogram with high predictive performance was constructed by incorporating co-mutation with clinical features. More strikingly, the prognosis of MSI-H patients in EC with co-mutation was significantly improved, and their survival reached a level consistent with the POLE subtype.

CONCLUSIONS

In endometrial cancer, co-mutation of FAT3 and LRP1B not only leads to activation of the immune state, but also represents a subgroup with an improved prognosis, particularly in the MSI-H subtype.

Neutrophil extracellular trap-associated risk index for predicting outcomes and response to Wnt signaling inhibitors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a type of breast cancer with poor prognosis, which is prone to distant metastasis and therapy resistance. The presence of neutrophil extracellular traps (NETs) contributes to the progression of breast cancer and is an efficient predictor of TNBC. We obtained the bulk and single-cell RNA sequencing data from public databases. Firstly, we identified five NET-related genes and constructed NET-related subgroups. Then, we constructed a risk index with three pivotal genes based on the differentially expressed genes between subgroups. Patients in the high-risk group had worse prognosis, clinicopathological features, and therapy response than low-risk group. Functional enrichment analysis revealed that the low-risk group was enriched in Wnt signaling pathway, and surprisingly, the drug sensitivity prediction showed that Wnt signaling pathway inhibitors had higher drug sensitivity in the low-risk group. Finally, verification experiments in vitro based on MDA-MB-231 and BT-549 cells showed that tumor cells with low-risk scores had less migration, invasion, and proliferative abilities and high drug sensitivity to Wnt signaling pathway inhibitors. In this study, multi-omics analysis revealed that genes associated with NETs may influence the occurrence, progression, and treatment of TNBC. Moreover, the bioinformatics analysis and cell experiments demonstrated that the risk index could predict the population of TNBC likely to benefit from treatment with Wnt signaling pathway inhibitors.

Artificial Intelligence for Precision Oncology of Triple-Negative Breast Cancer: Learning from Melanoma

Thanks to new technologies using artificial intelligence (AI) and machine learning, it is possible to use large amounts of data to try to extract information that can be used for personalized medicine. The great challenge of the future is, on the one hand, to acquire masses of biological data that nowadays are still limited and, on the other hand, to develop innovative strategies to extract information that can then be used for the development of predictive models. From this perspective, we discuss these aspects in the context of triple-negative breast cancer, a tumor where a specific treatment is still lacking and new therapies, such as immunotherapy, are under investigation. Since immunotherapy is already in use for other tumors such as melanoma, we discuss the strengths and weaknesses identified in the use of immunotherapy with melanoma to try to find more successful strategies. It is precisely in this context that AI and predictive tools can be extremely valuable. Therefore, the discoveries and advancements in immunotherapy for melanoma provide a foundation for developing effective immunotherapies for triple-negative breast cancer. Shared principles, such as immune system activation, checkpoint inhibitors, and personalized treatment, can be applied to TNBC to improve patient outcomes and offer new hope for those with aggressive, hard-to-treat breast cancer.

Predictive biomarkers of response and survival following immunotherapy with a PD-L1 inhibitor benmelstobart (TQB2450) and antiangiogenic therapy with a VEGFR inhibitor anlotinib for pretreated advanced triple negative breast cancer

In our phase Ib trial (ClinialTrials.gov Identifier: NCT03855358), benmelstobart (TQB2450), a novel humanized IgG1 antibody against PD-L1, plus antiangiogenic multikinase inhibitor, anlotinib, demonstrated promising antitumor activities in pretreated triple negative breast cancer (TNBC) patients. We conducted explorative analyses of genomic biomarkers to explore the associations with treatment response and survival outcomes. Targeted next generation sequencing (NGS) was undertaken toward circulating tumor DNA (ctDNA) collected from peripheral blood samples prior to the start of treatment and after disease progression. A total of 31 patients received targeted NGS and functional driver mutations in 29 patients were analyzed. The most frequent mutations were TP53 (72%), MLL3 (28%), and PIK3CA (17%). At a blood-based tumor mutational burden (bTMB) cutoff of 6.7 mutations per megabase, patients with low bTMB showed better response to anlotinib plus TQB2450 (50% vs. 7%, P = 0.015) and gained greater PFS benefits (7.3 vs. 4.1 months, P = 0.012) than those with high bTMB. At a maximum somatic allele frequency (MSAF) cutoff of 10%, a low MSAF indicated a better objective response (43% vs. 20%) as well as a significantly longer median PFS (7.9 vs. 2.7 months, P < 0.001). Patients with both low MSAF and low bTMB showed a notably better objective response to anlotinib plus TQB2450 (70% vs. 11%, P < 0.001) and a significantly longer median PFS (11.0 vs. 2.9 months, P < 0.001) than patients with other scenarios. Our findings support future studes and validation of MSAF and the combined bTMB-MSAF classification as predictive biomarkers of immune checkpoint inhibitor-based regimens in advanced TNBC patients.

Identification of immune infiltration-related biomarkers in carotid atherosclerotic plaques

Atherosclerosis is a chronic lipid-driven inflammatory response of the innate and adaptive immune systems, and it is responsible for several cardiovascular ischemic events. The present study aimed to determine immune infiltration-related biomarkers in carotid atherosclerotic plaques (CAPs). Gene expression profiles of CAPs were extracted from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between the CAPs and control groups were screened by the "limma" package in R software. Immune cell infiltration between the CAPs and control groups was evaluated by the single sample gene set enrichment analysis. Key infiltrating immune cells in the CAPs group were screened by the Wilcoxon test and least absolute shrinkage and selection operator regression. The weighted gene co-expression network analysis was used to identify immune cell-related genes. Hub genes were identified by the protein-protein interaction (PPI) network. Receiver operating characteristic curve analysis was performed to assess the gene's ability to differentiate between the CAPs and control groups. Finally, we constructed a miRNA-gene-transcription factor network of hub genes by using the ENCODE database. Eleven different types of immune infiltration-related cells were identified between the CAPs and control groups. A total of 1,586 differentially expressed immunity-related genes were obtained through intersection between DEGs and immune-related genes. Twenty hub genes were screened through the PPI network. Eventually, 7 genes (BTK, LYN, PTPN11, CD163, CD4, ITGAL, and ITGB7) were identified as the hub genes of CAPs, and these genes may serve as the estimable drug targets for patients with CAPs.

N7-methylguanosin regulators-mediated methylation modification patterns and characterization of the immune microenvironment in lower-grade glioma

N7-methylguanosine (m7G) modification signature has recently emerged as a crucial regulator of tumor progression and treatment in cancer. However, there is limited information available on the genomic profile of lower-grade gliomas (LGGs) related to m7G methylation modification genes' function in tumorigenesis and progression. In this study, we employed bioinformatics methods to characterize m7G modifications in individuals with LGG from The Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). We used gene set enrichment analysis (GSEA), single sample GSEA (ssGSEA), CIBERSORT algorithm, ESTIMATE algorithm, and TIDE to evaluate the association between m7G modification patterns, tumor microenvironment (TME) cell infiltration properties, and immune infiltration markers. The m7G scoring scheme using principal component analysis (PCA) was employed to investigate the m7G modification patterns quantitatively. We examined the m7G modification hub genes' expression levels in normal samples, refractory epilepsy samples, and LGG samples using immunohistochemistry, western-blotting, and qRT-PCR. Our findings revealed that individuals with LGG could be categorized into two groups based on m7G scores (high and low) according to the properties of m7G. Moreover, we observed that high m7G score was associated with significant clinical benefit and prolonged survival duration in the anti-PD-1 cohort, while low m7G score was associated with improved prognostic outcomes and increased likelihood of complete or partial response in the anti-PD-L1 cohort. Different m7G subtypes also showed varying Tumor Mutational Burden (TMB) and immune profiles and might have distinct responses to immunotherapy. Furthermore, we identified five potential genetic markers that were highly correlated with the m7G score signature index. These findings provide insight into the features and classification associated with m7G methylation modifications and may aid in improving the clinical outcome of LGG.

Integrated tumor genomic and immune microenvironment analysis identifies predictive biomarkers associated with the efficacy of neoadjuvant therapy for triple-negative breast cancer

BACKGROUND

Although neoadjuvant chemotherapy (NAC) is currently the best therapy for triple-negative breast cancer (TNBC), resistance still occurs in a considerable proportion, thus it is crucial to understand resistance mechanisms and identify predictive biomarkers for patients selection.

METHODS

Biopsy samples were collected from 21 patients with TNBC who underwent NAC. Whole-exome sequencing (WES), targeted sequencing, and multiplex immunohistochemistry (mIHC) were carried out on the clinical samples and used to identify and validate potential biomarkers associated with response to NAC. In addition, data on 190 TNBC patients who had undergone chemotherapy were obtained from The Cancer Genome Atlas (TCGA) and analyzed to further validate our findings.

RESULTS

Both the tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were significantly higher in responders than in non-responders. Higher response rates and longer survival rates were observed in patients with higher TMB. Patients with higher ratios of CD8 to M2 macrophages had higher response rates and improved survival rates. Finally, the integrated analysis demonstrated that the combination of TMB and the ratio of CD8 T cells to M2 macrophages could further distinguish patients who benefitted from the treatment in both enrolled patients and public data.

CONCLUSIONS

The findings of this study indicated that the combination of TMB and the ratio of CD8 T cells to M2 macrophages may be a potential biomarker for improving the recognition of NAC responders, thereby providing a basis for developing precision NAC regimens.

The prognostic value of neutrophil-to-lymphocyte ratio in de novo stage IV breast cancer: a retrospective cohort study

Background

The presence of a high neutrophil-to-lymphocyte ratio (NLR) has been associated with increased mortality in several malignancies. And the majority of studies on breast cancer (BC) analyzed patients with early-stage. Fewer studies focused on metastatic BC (MBC). De novo stage IV BC with no prior treatment is more suitable for analyzing prognostic factors. Herein, we examined the prognostic value of baseline NLR in de novo stage IV BC patients.

Methods

We retrospectively screened the medical records of female patients who were diagnosed with de novo stage IV BC at Peking University Cancer Hospital between January 2011 and December 2020. All patients were followed up by telephone every 6 months. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff value of NLR for progression-free survival (PFS). Peripheral blood lymphocyte subsets and tumor infiltrating lymphocytes (TILs) were analyzed by flow cytometry and immunohistochemistry, respectively. Correlations of PFS and overall survival (OS) with NLR and other clinicopathological factors were evaluated using Kaplan-Meier method and Cox regression analyses.

Results

A total of 128 patients between January 2011 and December 2020 were enrolled. 70 (54.7%) cases were hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative, 79 (61.7%) patients had visceral metastasis and 67 (52.3%) patients had more than 2 metastatic sites. The cutoff values of NLR were 2.9, optimized by ROC curve analysis. Totals of 77 and 51 patients were assigned to the NLR-low (≤2.9) and NLR-high (>2.9) groups, respectively. Compared with NLR-high patients, the NLR-low patients had significantly longer median PFS (14.8 vs. 7.2 months; hazard ratio =1.791; P=0.003). The OS showed no significant difference (64.1 vs. 56.0 months, P=0.980). The patients with NLR-low had a higher level of peripheral CD3⁺ T cells (P=0.028) and a lower level of peripheral CD4⁺CD25⁺ regulatory T (Treg) cells (P=0.041). Patient samples with NLR-low also demonstrated higher levels of TILs than those with NLR-high (P=0.025).

Conclusions

The baseline NLR-high is associated with adverse PFS in patients with de novo stage IV BC. The NLR-high status may indicate immune suppression status, which can help identify patients with unfavorable prognosis and assist with physicians' treatment decision.

Novel immune-related prognostic model and nomogram for breast cancer based on ssGSEA

This study aimed to construct an immune-related prognostic model and a nomogram to predict the 1-, 3-, and 5-year overall survival (OS) of breast cancer patients. We applied single-sample gene set enrichment analysis to classify 1,053 breast cancer samples from The Cancer Genome Atlas (TCGA) database into high and low immune cell infiltration clusters. In cluster construction and validation, the R packages "GSVA," "hclust," "ESTIMATE," and "CIBERSORT" and GSEA software were utilized. ImmPort, univariate Cox regression analysis, and Venn analysis were then used to identify 42 prognostic immune-related genes. Eventually, the genes TAPBPL, RAC2, IL27RA, ULBP2, PSMB8, SOCS3, NFKBIE, IGLV6-57, CXCL1, IGHD, AIMP1, and CXCL13 were chosen for model construction utilizing least absolute shrinkage and selection operator regression analysis. The Kaplan-Meier curves of both the training and validation sets indicated that the overall survival of patients in the low-risk group was superior to that of patients in the high-risk group (p < .05). The areas under curves (AUCs) of the model at 1, 3, and 5 years were, respectively, .697, .710, and .675 for the training set and .930, .688, and .712 for the validation set. Regarding clinicopathologic characteristics, breast cancer-related genes, and tumor mutational burden, effective differentiation was achieved between high-risk and low-risk groups. A nomogram integrating the risk model and clinicopathologic factors was constructed using the "rms" R software package. The nomogram's 1-, 3-, and 5-year AUCs were .828, .783, and .751, respectively. Overall, our study developed an immune-related model and a nomogram that could reliably predict OS for breast cancer patients, and offered insights into tumor immune and pathological mechanisms.

Immune checkpoints expression patterns in early-stage triple-negative breast cancer predict prognosis and remodel the tumor immune microenvironment

Background

Currently, targeting immune checkpoint molecules holds great promise for triple-negative breast cancer (TNBC). However, the expression landscape of immune checkpoint genes (ICGs) in TNBC remains largely unknown.

Method

Herein, we systematically investigated the ICGs expression patterns in 422 TNBC samples. We evaluated the ICGs molecular typing based on the ICGs expression profile and explored the associations between ICGs molecular subtypes and tumor immune characteristics, clinical significance, and response to immune checkpoint inhibitors (ICIs).

Results

Two ICGs clusters and two ICGs-related gene clusters were determined, which were involved in different survival outcomes, biological roles and infiltration levels of immune cells. We established a quantification system ICGs riskscore (named IRS) to assess the ICGs expression patterns for individuals. TNBC patients with lower IRS were characterized by increased immune cell infiltration, favorable clinical outcomes and high sensitivity to ICIs therapy. We also developed a nomogram model combining clinicopathological variables to predict overall survival in TNBC. Genomic feature analysis revealed that high IRS group presented an increased tumor mutation burden compared with the low IRS group.

Conclusion

Collectively, dissecting the ICGs expression patterns not only provides a new insight into TNBC subtypes but also deepens the understanding of ICGs in the tumor immune microenvironment.

The prognostic role of tumor mutation burden on survival of breast cancer: a systematic review and meta-analysis

Background

As a potential genetic biomarker, tumor mutation burden (TMB) has made progress in numerous tumors. There are limited data regarding TMB and its prognostic role is controversial in breast cancer. This systematic review and meta-analysis were conducted to assess the prognostic value of TMB on survival of breast cancer.

Methods

The databases PubMed, Embase, Web of Science, and Cochrane Library were searched for articles published through May 31, 2022. Moreover, effective data were extracted from included studies and calculated pooled effects of hazard ratio (HR) for overall survival (OS) and progression-free survival (PFS) by STATA 16.0. Heterogeneity was conducted by the I² statistic and p-value. Using publication bias evaluation, sensitivity analysis, and subgroup analysis, the origin of heterogeneity was further investigated.

Results

They were up to 1,722 patients collected from sixteen cohorts for this analysis. The pooled effects of HR for both OS (HR: 1.14, 95% CI: 0.83,1.58, p > 0.01) and PFS (HR: 0.96, 95% CI: 0.53,1.71, p > 0.01) indicated no statistically significant difference in the high TMB and low TMB group. In immune checkpoint inhibitors (ICIs) subgroup, high TMB patients demonstrated benefit of OS (HR: 0.72, 95% CI: 0.59,0.87, p = 0.001) and PFS (HR: 0.52, 95% CI: 0.35,0.77, p < 0.001), whereas difference was not statistically significant in the non-ICIs subgroup (OS, HR:1.76, 95% CI: 0.97,3.20, p = 0.062; PFS, HR:2.31, 95% CI: 0.89,5.97, p = 0.086). In addition, sensitivity analysis revealed that the pooled effects were stable. The funnel plot and Begg's test suggested the absence of publication bias.

Conclusion

Meta-analysis revealed that the prognostic relevance of TMB in breast cancer is limited in scope. High TMB may be associated with longer survival only in ICIs-based treatment, but the association is not evident in non-ICIs-based treatment.

Trial registration

[https://www.crd.york.ac.uk/PROSPERO], Prospective Register of Systematic Reviews (PROSPERO), identifier: CRD42022342488.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10284-1.

Identification of HLA class I-restricted immunogenic neoantigens in triple negative breast cancer

Immune checkpoint inhibitor (ICI)-based immunotherapy in triple negative breast cancer (TNBC) is achieving limited therapeutic results, requiring the development of more potent strategies. Combination of ICI with vaccination strategies would enhance antitumor immunity and response rates to ICI in patients having poorly infiltrated tumors. In heavily mutated tumors, neoantigens (neoAgs) resulting from tumor mutations have induced potent responses when used as vaccines. Thus, our aim was the identification of immunogenic neoAgs suitable as vaccines in TNBC patients. By using whole exome sequencing, RNAseq and HLA binding algorithms of tumor samples from a cohort of eight TNBC patients, we identified a median of 60 mutations/patient, which originated a putative median number of 98 HLA class I-restricted neoAgs. Considering a group of 27 predicted neoAgs presented by HLA-A*02:01 allele in two patients, peptide binding to HLA was experimentally confirmed in 63% of them, whereas 55% were immunogenic in vivo in HLA-A*02:01⁺ transgenic mice, inducing T-cells against the mutated but not the wild-type peptide sequence. Vaccination with peptide pools or DNA plasmids expressing these neoAgs induced polyepitopic T-cell responses, which recognized neoAg-expressing tumor cells. These results suggest that TNBC tumors harbor neoAgs potentially useful in therapeutic vaccines, opening the way for new combined immunotherapies.

Identification of necroptosis-related subtypes and prognosis model in triple negative breast cancer

Background

Necroptosis is considered to be a new form of programmed necrotic cell death, which is associated with metastasis, progression and prognosis of various types of tumors. However, the potential role of necroptosis-related genes (NRGs) in the triple negative breast cancer (TNBC) is unclear.

Methods

We extracted the gene expression and relevant clinicopathological data of TNBC from The Cancer Genome Atlas (TCGA) databases and the Gene Expression Omnibus (GEO) databases. We analyzed the expression, somatic mutation, and copy number variation (CNV) of 67 NRGs in TNBC, and then observed their interaction, biological functions, and prognosis value. By performing Lasso and COX regression analysis, a NRGs-related risk model for predicting overall survival (OS) was constructed and its predictive capabilities were verified. Finally, the relationship between risk_score and immune cell infiltration, tumor microenvironment (TME), immune checkpoint, and tumor mutation burden (TMB), cancer stem cell (CSC) index, and drug sensitivity were analyzed.

Results

A total 67 NRGs were identified in our analysis. A small number of genes (23.81%) detected somatic mutation, most genes appeared to have a high frequency of CNV, and there was a close interaction between them. These genes were remarkably enriched in immune-related process. A seven-gene risk_score was generated, containing TPSG1, KRT6A, GPR19, EIF4EBP1, TLE1, SLC4A7, ESPN. The low-risk group has a better OS, higher immune score, TMB and CSC index, and lower IC50 value of common therapeutic agents in TNBC. To improve clinical practicability, we added age, stage_T and stage_N to the risk_score and construct a more comprehensive nomogram for predicting OS. It was verified that nomogram had good predictive capability, the AUC values for 1-, 3-, and 5-year OS were 0.847, 0.908, and 0.942.

Conclusion

Our research identified the significant impact of NRGs on immunity and prognosis in TNBC. These findings were expected to provide a new strategy for personalize the treatment of TNBC and improve its clinical benefit.

Somatic Mutation of FAT Family Genes Implicated Superior Prognosis in Patients With Stomach Adenocarcinoma

FAT family genes encode protocadherin, which regulates tumor cell proliferation and migration. Although transcriptional levels of FAT family members had been reported in multiple malignant tumors, the association between mutation and prognosis of the FAT family in stomach adenocarcinoma (STAD) has not been investigated. Herein, we performed a multi-omics integrative bioinformatics analysis using genomic and mRNA expression data to explore the role of gene mutations across the FAT family on clinical outcomes of STAD. The results showed that FAT mutations occurred in 174 of 435 (40%) of the samples. Patients with FAT mutations possessed significantly better progression-free survival (P = 0.019) and overall survival (P = 0.034) than those with non-FAT mutations, and FAT mutations exhibited significantly higher tumor mutational burden (TMB) and microsatellite instability. Notably, FAT mutations had a greater effect on somatic single-nucleotide variation than copy number variation and resulted in more abundant DNA damage repair (DDR) mutations. Further investigation demonstrated that FAT mutations contributed to an inflammatory tumor microenvironment (TME), as indicated by significantly increased numbers of activated CD4 and CD8 T cells, and significantly decreased numbers of mast cell, plasmacytoid dendritic cell, type 2 T helper cell, and high expression of immune-promoting genes. Moreover, biological process antigen processing and presentation, DNA replication, and DDR-related pathways were significantly upregulated in patients with FAT mutations. Collectively, FAT mutations significantly improved the survival of patients with STAD by enhancing tumor immunogenicity (e.g., TMB and DDR mutations) and an inflamed TME, indicating that the FAT family might be a potential prognostic and therapeutic biomarker for STAD.

Identification of pyroptosis related subtypes and tumor microenvironment infiltration characteristics in breast cancer

Understanding the association of pyroptosis with tumor progression, prognosis and effect on immunotherapeutic response in breast cancer (BC) is limited. This study analysed forty pyroptosis-related genes to construct the pyroptosis score. Association of the pyroptosis score with the overall survival, clinical features, tumor mutation load, immune cell infiltration, and treatment sensitivity of patients with BC was analysed. Out of 983 BC samples, 304 (30.93%) had genetic alterations with the highest TP53 frequency. We identified three separate subtypes associated with pyroptosis action. These subtypes correlate with the clinicopathological characteristics, TME immune cell infiltration, and disease prognosis. Based on the expression levels of the pyroptosis genes, we divided the pyroptosis score into a high group and a low group. The immune-activated pyroptosis subtype had a higher score with a better prognosis. We also observed that the pyroptosis score correlates with the tumor mutation burden. The pyroptosis score and disease prognosis were directly proportional. A higher pyroptosis score indicated a better prognosis. Results suggest that the pyroptosis-related gene prognosis model is closely related to the immune cell infiltration of BC. The three pyroptosis subtypes associated with BC assist in accurately identifying the tumor subtype, the prognosis of immunotherapy drugs and the patient’s therapeutic response.

Identification of mutation patterns and circulating tumour DNA-derived prognostic markers in advanced breast cancer patients

BACKGROUND

The correlations between circulating tumour DNA (ctDNA)-derived genomic markers and treatment response and survival outcome in Chinese patients with advanced breast cancer (ABC) have not been extensively characterized.

METHODS

Blood samples from 141 ABC patients who underwent first-line standard treatment in Peking University Cancer Hospital were collected. A next-generation sequencing based liquid biopsy assay (PredicineCARE) was used to detect somatic mutations and copy number variations (CNVs) in ctDNA. A subset of matched blood samples and tumour tissue biopsies were compared to evaluate the concordance.

RESULTS

Overall, TP53 (44.0%) and PIK3CA (28.4%) were the top two altered genes. Frequent CNVs included amplifications of ERBB2 (24.8%) and FGFR1 (8.5%) and deletions of CDKN2A (3.5%). PIK3CA/TP53 and FGFR1/2/3 variants were associated with drug resistance in hormone receptor-positive (HR +) and human epidermal growth factor receptor 2-positive (HER2 +) patients. The comparison of genomic variants across matched tumour tissue and ctDNA samples revealed a moderate to high concordance that was gene dependent. Triple-negative breast cancer (TNBC) patients harbouring TP53 or PIK3CA alterations had a shorter overall survival than those without corresponding mutations (P = 0.03 and 0.008). A high ctDNA fraction was correlated with a shorter progression-free survival (PFS) (P = 0.005) in TNBC patients. High blood-based tumor mutation burden (bTMB) was associated with a shorter PFS for HER2 + and TNBC patients (P = 0.009 and 0.05). Moreover, disease monitoring revealed several acquired genomic variants such as ESR1 mutations, CDKN2A deletions, and FGFR1 amplifications.

CONCLUSIONS

This study revealed the molecular profiles of Chinese patients with ABC and the clinical validity of ctDNA-derived markers, including the ctDNA fraction and bTMB, for predicting treatment response, prognosis, and disease progression.

TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT03792529. Registered January 3rd 2019, https://clinicaltrials.gov/ct2/show/NCT03792529 .

A risk model of 10 aging-related genes for predicting survival and immune response in triple-negative breast cancer

Accumulated studies showed that the clinical significance of aging on the development and malignancy of tumors, while the relationship between aging and the prognosis, immune response in triple‐negative breast cancer (TNBC) has not been well clarified. Here, we constructed a risk model of 10 prognostic aging‐related genes (ARGs) from METABRIC database. Then, TNBC patients were classified into high‐ and low‐risk groups, the survival diversity, immune response, genomic function, and tumor mutation burden (TMB) between different risk groups were explored in METABRIC, TCGA, and GSE58812 cohorts. Results showed that patients in the high‐risk group had poorer survival outcomes compared to their counterparts (all p < 0.05), and the nomogram we established showed reliable prediction ability for survival in TNBC patients. Besides, TNBC patients with high‐risk scores had a lower expression of immune checkpoint markers and a lower fraction of activated immune cells. Furthermore, GSEA showed that Notch signaling pathway was significantly enriched in the high‐risk group. Thus, a risk model based on the aging‐related genes was developed and validated in this study, which may serve as a potential biomarker for prognosis and personalized treatment in TNBCs.

Co-Expression and Combined Prognostic Value of CSPG4 and PDL1 in TP53-Aberrant Triple-Negative Breast Cancer

Background

In triple-negative breast cancer (TNBC), PDL1/PD1-directed immunotherapy is effective in less than 20% of patients. In our preliminary study, we have found CSPG4 to be highly expressed together with PDL1 in TNBCs, particularly those harboring TP53 aberrations. However, the clinical implications of co-expressed CSPG4 and PDL1 in TNBCs remain elusive.

Methods

A total of 85 advanced TNBC patients treated in the Hunan Cancer Hospital between January 2017 and August 2019 were recruited. The expressions of CSPG4 and PDL1 in TNBC tissues were investigated using immunohistochemistry (IHC). The RNA-seq dataset from the TCGA-BRCA project was further used to analyze the mRNA expression of CSPG4 and PDL1 in TP53-aberrant TNBCs. Cox proportional hazards model and Kaplan-Meier curves with Logrank test was used to analyze the effects of CSPG4 and PDL1 on survival. TNBC cell lines were further used to investigate the molecular mechanism that were involved.

Results

TP53 aberrations occurred in more than 50% of metastatic TNBCs and were related to higher tumor mutation burden (TMB). In TCGA-BRCA RNA-seq dataset analysis, both CSPG4 and PDL1 levels were high in TNBCs, especially in TP53-aberrant TNBCs. IHC assay showed nearly 60% of advanced TNBCs to be CSPG4-positive and about 25% to be both CSPG4-positive and PDL1-positive. The levels of CSPG4 and PDL1 were high in TNBC cell lines as revealed by flow cytometry and immunoblotting compared with non-TNBC cells. Univariate Cox regression analysis indicated that CSPG4 positivity was a significant risk factor for progression-free survival in metastatic TNBCs, with a hazard ratio (HR) of 2.26 (P = 0.05). KM curves with Logrank test also identified high level of CSPG4 as a significant risk factor for overall survival in advanced breast cancers in TCGA-BRCA samples (P = 0.02). The immunoblotting assays showed that EMT-related pathways were involved in CSPG4-mediated invasion.

Conclusions

CSPG4 expression level is associated with PDL1 positivity in TP53-aberrant TNBC cells. Patients with CSPG4 expression have poor treatment response and poor overall survival. Co-expressed CSPG4 and PDL1 may have an important prognostic value and provide new therapeutic targets in TNBC patients. CSPG4 might mediate tumor invasion and PDL1 overexpression through EMT-related pathway.

vWCluster: Vector-valued optimal transport for network based clustering using multi-omics data in breast cancer

In this paper, we present a network-based clustering method, called vector Wasserstein clustering (vWCluster), based on the vector-valued Wasserstein distance derived from optimal mass transport (OMT) theory. This approach allows for the natural integration of multi-layer representations of data in a given network from which one derives clusters via a hierarchical clustering approach. In this study, we applied the methodology to multi-omics data from the two largest breast cancer studies. The resultant clusters showed significantly different survival rates in Kaplan-Meier analysis in both datasets. CIBERSORT scores were compared among the identified clusters. Out of the 22 CIBERSORT immune cell types, 9 were commonly significantly different in both datasets, suggesting the difference of tumor immune microenvironment in the clusters. vWCluster can aggregate multi-omics data represented as a vectorial form in a network with multiple layers, taking into account the concordant effect of heterogeneous data, and further identify subgroups of tumors in terms of mortality.

Co-Mutation of FAT3 and LRP1B in Lung Adenocarcinoma Defines a Unique Subset Correlated With the Efficacy of Immunotherapy

Immunotherapy based on immune checkpoint inhibitors (ICIs) have demonstrated remarkable survival benefits and gained regulatory approval in non-small cell lung cancer (NSCLC) patients without an actionable driver mutation, but currently there is no well-established standard for how to screen the most suitable population for ICIs treatment. Here, we conducted a comprehensive analysis of the somatic mutation landscape of lung adenocarcinoma (LUAD) samples. After the stepwise screening of high-frequency mutated genes, two genes with prominent significance, FAT3 and LRP1B, were finally screened out. Through further analysis, we discovered that the co-mutation of FAT3 and LRP1B was associated with an earlier age of onset and occurred more frequently in Black/African American. Furthermore, co-mutation defines a unique subgroup of lung adenocarcinoma that can increase tumor mutational burden (TMB), boost cytotoxicity and tumor immunogenicity, and facilitate lymphocyte infiltration. The results of gene set enrichment analysis (GSEA) indicated that co-mutation can influence tumorigenesis through a variety of mechanisms. More strikingly, the subset of LUAD with co-mutation of FAT3 and LRP1B exhibited significantly prolonged immunotherapy progression free survival (PFS). In summary, co-mutation of FAT3 and LRP1B is a promising useful biomarker for predicting the efficacy of immunotherapy, which can improve the clinical efficiency of practicing precision medicine in lung adenocarcinoma patients.

Positive Correlation Between LTA Expression and Overall Immune Activity Suggests an Increased Probability of Survival in Uterine Corpus Endometrial Carcinoma

Mounting evidence indicates that immune status plays a crucial role in tumor progress and metastasis, while there are no effective and easily assayed biomarkers to reflect it in uterine corpus endometrial carcinoma (UCEC) patients. Here, we attempted to identify the potential biomarkers that were differentially expressed between normal and tumor tissues and involved in prognosis and immune microenvironment of UCEC patients. RNA-seq data with relevant clinical information were obtained from The Cancer Genome Atlas (TCGA). ssGSEA algorithm was applied to calculate the enrichment scores of every tumor infiltration lymphocyte (TIL) set in each sample, and patients were then divided into three clusters using multiple R packages. Cox analysis, ESTIMATE, and CIBERSORT were utilized to determine the differentially expressed immune-related genes (DEIGs) with overall survival, and to explore their roles in prognosis, immune microenvironment, and immunotherapeutic response. The TIMER and TISIDB databases were utilized to predict the effectiveness of immunotherapy in UCEC patients. LTA was finally identified to be significantly upregulated in tumor tissues and closely associated with prognosis and immunological status, which was then verified in GSE17025. In multivariate analysis, the hazard ratio of LTA was 0.42 with 95% CI (0.22–0.80) (p = 0.008). Patients with high LTA expression had better survival and apparently immune-activated phenotypes, such as more tumor mutation burden (TMB), stronger immune cell infiltrations, higher expression of immunosuppressive points, and higher immunophenoscore, meaning they had an immunotherapeutic advantage over those with low LTA expression. TIMER and TISIDB indicated that LTA was highly expressed in UCEC, and its expression was negatively correlated with stages and positively related to prognosis. Additionally, we found that LTA ectopic expression weakened the proliferation ability of RL95-2 cells. All these findings indicated that LTA could act as a novel and easily assayed biomarker to predict immunological status and clinical outcomes and even as an antioncogene to explore UCEC in depth.

Somatic mutation and expression of BAP1 in hepatocellular carcinoma: an indicator for ferroptosis and immune checkpoint inhibitor therapies

BRCA1-Associated Protein 1 (BAP1) is a deubiquitylase that is found associated with multiprotein complexes that regulate key cellular pathways, and subsequent researches have revealed that BAP1 acts independently as a tumor suppressor. Somatic BAP1 mutations occur in various malignancies, but malignancies arising from mutation of tumor suppressors have unexplained tissue proclivity. Whether somatic mutation or expression alteration of BAP1 in hepatocellular carcinoma (HCC) influence carcinogenesis or immunogenicity is still unknown. In this study, we analyzed RNA expression, immune infiltration, survival and mutation data of HCC from The Cancer Genome Atlas databases. The association between BAP1 and clinicopathological features was further investigated by immunohistochemistry on tissue microarray. We found that the prognosis of patients with high BAP1 expression was significantly worse than that of patients with low BAP1 expression, and multivariate analyses revealed that BAP1 expression was an independent prognostic factor for poor prognosis. HCC with high BAP1 expression was associated with low ESTIMATE Score, recruitment of more tumor-infiltrating macrophage, and elevated levels of tumor mutation burden, microsatellite instability, neoantigen count, as well as programmed death-ligand1 in HCC. In addition, BAP1 mutated HCC showed reduced ability to promote ferroptosis and high BAP1 expression was correlated with ferroptosis. In conclusion, high BAP1 expression reflects immunosuppression and ferroptosis in HCC. BAP1 is a promising prognostic marker for survival of HCC and may act as a complementary indicator for patients to receive ferroptosis-promoting therapy or immunotherapy.

Classification and immune invasion analysis of breast cancer based on m6A genes

Background

Breast cancer (BRCA) shows genetic, epigenetic, and phenotypic diversity. Methylation of N6-methyladenosine (m6A) affects the occurrence, development, and therapeutic efficacy of BRCA. However, the characteristics and prognostic value of m6A in BRCA remain unclear. We aimed to classify and construct a scoring system for the m6A regulatory gene in BRCA, and to explore its potential mechanisms.

Methods

In this study, we selected 23 m6A regulatory genes and analyzed their genetic variation in BRCA, including copy number variation (CNV) data, expression differences, mutations, gene types, and correlations between genes. Survival curves were drawn by the Kaplan-Meier method, and a log-rank P<0.05 was considered statistically significant. The partitioning around medoids (PAM) algorithm was used for molecular subtype analysis of m6A, single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to quantify the relative infiltration levels of various immune cell subgroups, and a scoring system was built based on principal component analysis (PCA).

Results

In BRCA, m6A regulatory gene mutation frequency is not high, while that of CNV mutation is high, which is related to gene expression and closely related to prognosis. In this study, we identified 3 different m6A subtypes, which are closely related to the level of immune cell infiltration. We further constructed an m6A score system, in which lower scores were correlated with low tumor mutation burden (TMB), later clinical staging, programmed cell death 1 ligand 1 (PD-L1) expression, and triple-negative breast cancer (TNBC).

Conclusions

This study highlights the diversity and complexity of the role of m6A in BRCA. The classification of BRCA based on the m6A regulatory gene can help us understand the characteristics of BRCA and help develop individualized immunotherapy regimens.