Durable Complete Response With Immune Checkpoint Inhibitor in Breast Cancer With High Tumor Mutational Burden and APOBEC Signature

Nivolumab plus low-dose ipilimumab in hypermutated HER2-negative metastatic breast cancer: a phase II trial (NIMBUS)

In the phase II NIMBUS trial, patients with human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC) and high tumor mutational burden (TMB ≥ 9 mut/Mb) received nivolumab (3 mg/kg biweekly) and low-dose ipilimumab (1 mg/kg every 6 weeks) for 2 years or until progression. The primary endpoint was objective response rate (ORR) per RECIST 1.1 criteria. Among 30 patients enrolled, the median TMB was 10.9 mut/Mb (range: 9-110) and the confirmed objective response rate was 20%. Secondary endpoints included progression-free survival, overall survival, clinical benefit rate, and safety and tolerability, including immune-related adverse events (irAEs). A prespecified correlative outcome was to evaluate the ORR in patients with a TMB ≥ 14 mut/Mb. Patients with TMB ≥ 14 mut/Mb (n = 6) experienced higher response rates (60% vs 12%; p = 0.041) and showed a trend towards improved progression-free survival and overall survival compared to patients with TMB < 14 mut/Mb. Exploratory genomic analyses suggested that ESR1 and PTEN mutations may be associated with poor response, while clinical benefit was associated with a decrease or no change in tumor fraction by serial circulating tumor DNA during treatment. Stool microbiome analysis revealed that baseline blood TMB, PD-L1 positivity, and immune-related diarrhea are associated with distinct taxonomic profiles. In summary, some patients with hypermutated HER2-negative MBC experience extended clinical benefit with a dual immunotherapy regimen; a higher TMB, and additional genomic and microbiome biomarkers may optimize patient selection for therapy with nivolumab plus low-dose ipilimumab. (Funded by Bristol Myers Squibb; ClinicalTrials.gov identifier, NCT03789110).

APOBEC in breast cancer: a dual player in tumor evolution and therapeutic response

The APOBEC (Apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like) family of cytidine deaminases has emerged as pivotal a contributor to genomic instability and adaptive immunity through DNA/RNA editing. Accumulating evidence underscores their dual role in breast carcinogenesis-driving tumor heterogeneity via mutagenesis while simultaneously shaping immunogenic landscapes. This review synthesizes current insights into APOBEC-mediated molecular mechanisms, focusing on their clinical implications across breast cancer subtypes. Notably, APOBEC-driven mutagenesis correlates with elevated tumor mutational burden (TMB), replication stress vulnerability, and immune checkpoint inhibitor (ICI) responsiveness. Paradoxically, these mutations also accelerate endocrine therapy resistance and subclonal diversification. We propose APOBEC mutational signatures as predictive biomarkers for ICI efficacy and discuss therapeutic strategies leveraging APOBEC activity, including ATR inhibition and hypermutagenic immunotherapy. Harnessing APOBEC's duality-balancing its pro-immunogenic effects against genomic chaos-may redefine precision oncology in breast cancer.

DNA damage response in breast cancer and its significant role in guiding novel precise therapies

DNA damage response (DDR) deficiency has been one of the emerging targets in treating breast cancer in recent years. On the one hand, DDR coordinates cell cycle and signal transduction, whose dysfunction may lead to cell apoptosis, genomic instability, and tumor development. Conversely, DDR deficiency is an intrinsic feature of tumors that underlies their response to treatments that inflict DNA damage. In this review, we systematically explore various mechanisms of DDR, the rationale and research advances in DDR-targeted drugs in breast cancer, and discuss the challenges in its clinical applications. Notably, poly (ADP-ribose) polymerase (PARP) inhibitors have demonstrated favorable efficacy and safety in breast cancer with high homogenous recombination deficiency (HRD) status in a series of clinical trials. Moreover, several studies on novel DDR-related molecules are actively exploring to target tumors that become resistant to PARP inhibition. Before further clinical application of new regimens or drugs, novel and standardized biomarkers are needed to develop for accurately characterizing the benefit population and predicting efficacy. Despite the promising efficacy of DDR-related treatments, challenges of off-target toxicity and drug resistance need to be addressed. Strategies to overcome drug resistance await further exploration on DDR mechanisms, and combined targeted drugs or immunotherapy will hopefully provide more precise or combined strategies and expand potential responsive populations.

Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort

Introduction

The programmed cell death (PCD) plays a key role in the development and progression of lung adenocarcinoma. In addition, immune-related genes also play a crucial role in cancer progression and patient prognosis. However, further studies are needed to investigate the prognostic significance of the interaction between immune-related genes and cell death in LUAD.

Methods

In this study, 10 clustering algorithms were applied to perform molecular typing based on cell death-related genes, immune-related genes, methylation data and somatic mutation data. And a powerful computational framework was used to investigate the relationship between immune genes and cell death patterns in LUAD patients. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations, and we constructed an immune-associated programmed cell death model (PIGRS) using the machine learning model that exhibited the best performance. Finally, based on a series of in vitro experiments used to explore the role of PSME3 in LUAD.

Results

We used 10 clustering algorithms and multi-omics data to categorize TCGA-LUAD patients into three subtypes. patients with the CS3 subtype had the best prognosis, whereas patients with the CS1 and CS2 subtypes had a poorer prognosis. PIGRS, a combination of 15 high-impact genes, showed strong prognostic performance for LUAD patients. PIGRS has a very strong prognostic efficacy compared to our collection. In conclusion, we found that PSME3 has been little studied in lung adenocarcinoma and may be a novel prognostic factor in lung adenocarcinoma.

Discussion

Three LUAD subtypes with different molecular features and clinical significance were successfully identified by bioinformatic analysis, and PIGRS was constructed using a powerful machine learning framework. and investigated PSME3, which may affect apoptosis in lung adenocarcinoma cells through the PI3K/AKT/Bcl-2 signaling pathway.

Comprehensive genomic profiling and therapeutic implications for Taiwanese patients with treatment-naïve breast cancer

BACKGROUND

Breast cancer is a heterogeneous disease categorized based on molecular characteristics, including hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression levels. The emergence of profiling technology has revealed multiple driver genomic alterations within each breast cancer subtype, serving as biomarkers to predict treatment outcomes. This study aimed to explore the genomic landscape of breast cancer in the Taiwanese population through comprehensive genomic profiling (CGP) and identify diagnostic and predictive biomarkers.

METHODS

Targeted next-generation sequencing-based CGP was performed on 116 archived Taiwanese breast cancer specimens, assessing genomic alterations (GAs), including single nucleotide variants, copy number variants, fusion genes, tumor mutation burden (TMB), and microsatellite instability (MSI) status. Predictive variants for FDA-approved therapies were evaluated within each subtype.

RESULTS

In the cohort, frequent mutations included PIK3CA (39.7%), TP53 (36.2%), KMT2C (9.5%), GATA3 (8.6%), and SF3B1 (6.9%). All subtypes had low TMB, with no MSI-H tumors. Among HR + HER2- patients, 42% (27/65) harbored activating PIK3CA mutations, implying potential sensitivity to PI3K inhibitors and resistance to endocrine therapies. HR + HER2- patients exhibited intrinsic hormonal resistance via FGFR1 gene gain/amplification (15%), exclusive of PI3K/AKT pathway alterations. Aberrations in the PI3K/AKT/mTOR and FGFR pathways were implicated in chemoresistance, with a 52.9% involvement in triple-negative breast cancer. In HER2+ tumors, 50% harbored GAs potentially conferring resistance to anti-HER2 therapies, including PIK3CA mutations (32%), MAP3K1 (2.9%), NF1 (2.9%), and copy number gain/amplification of FGFR1 (18%), FGFR3 (2.9%), EGFR (2.9%), and AKT2 (2.9%).

CONCLUSION

This study presents CGP findings for treatment-naïve Taiwanese breast cancer, emphasizing its value in routine breast cancer management, disease classification, and treatment selection.

Tumor microenvironment characteristics and prognostic role of m6A modification in lung squamous cell carcinoma

Background

It has recently been determined that N6-methyladenosine (m6A) RNA methylation regulators have prominent effects on several cancers. However, the potential role of m6A modification in lung squamous cell carcinoma (LUSC) remains unclear.

Methods

We evaluated the modification pattern of m6A and studied the biological function of m6A regulators in LUSC. Then, we constructed the m6Ascore to predict the prognosis of LUSC and analyzed the relationship between the m6Ascore and tumor mutation burden, immune cell infiltration, and immunotherapy.

Result

In the unsupervised consensus cluster analysis, three different m6Aclusters were identified, which correspond to an immune activation state, a moderate immune activation state, and an immune tolerance state. Forty-two genes related to the m6A phenotype were used to construct the m6Ascore; subsequently, multiple validations of the m6Ascore were carried out to determine the relationship between the score and immune cell infiltration and response to CTLA-4/PD-1 inhibitor treatment. Further analysis revealed that the m6Ascore could effectively predict the prognosis of LUSC and that the m6A phenotype-related genes, FAM162A and LOM4, might be potential biomarkers.

Conclusion

These findings highlight the potential role of m6A modification in the prognosis, TME, and immunotherapy of LUSC and have profound implications for developing more effective personalized treatment strategies for LUSC.

cGAS-STING pathway expression correlates with genomic instability and immune cell infiltration in breast cancer

Genomic instability, as caused by oncogene-induced replication stress, can lead to the activation of inflammatory signaling, involving the cGAS-STING and JAK-STAT pathways. Inflammatory signaling has been associated with pro-tumorigenic features, but also with favorable response to treatment, including to immune checkpoint inhibition. In this study, we aim to explore relations between inflammatory signaling, markers of replication stress, and immune cell infiltration in breast cancer. Expression levels of cGAS-STING signaling components (STING, phospho-TBK1, and phospho-STAT1), replication stress markers (γH2AX and pRPA), replication stress-related proto-oncogenes (Cyclin E1 and c-Myc) and immune cell markers (CD20, CD4, and CD57) are determined immunohistochemically on primary breast cancer samples (n = 380). RNA-sequencing data from TCGA (n = 1082) and METABRIC (n = 1904) are used to calculate cGAS-STING scores. pTBK1, pSTAT1 expression and cGAS-STING pathway scores are all increased in triple-negative breast cancers compared to other subtypes. Expression of γH2AX, pRPA, Cyclin E1, c-Myc, and immune cell infiltration positively correlate with p-STAT1 expression (P < 0.001). Additionally, we observe significant positive associations between expression of pTBK1 and γH2AX, pRPA, c-Myc, and number of CD4+ cells and CD20+ cells. Also, cGAS-STING scores are correlated with genomic instability metrics, such as homologous recombination deficiency (P < 0.001) and tumor mutational burden (P < 0.01). Moreover, data from the I-SPY2 clinical trial (n = 71) confirms that higher cGAS-STING scores are observed in breast cancer patients who responded to immunotherapy combined with chemotherapy. In conclusion, the cGAS-STING pathway is highly expressed in TNBCs and is correlated with genomic instability and immune cell infiltration.

Prognostic and predictive biomarkers with therapeutic targets in breast cancer: A 2022 update on current developments, evidence, and recommendations

OBJECTIVE

To evaluate and validate the recent and emerging data for prognostic and predictive biomarkers with therapeutic targets in breast cancer.

DATA SOURCES

A literature search from January 2015 to March 2022 was performed using the key terms breast cancer, clinical practice guidelines, gene mutations, genomic assay, immune cancer therapy, predictive and/or prognostic biomarkers, and targeted therapies.

STUDY SELECTION AND DATA EXTRACTION

Relevant clinical trials, meta-analyses, seminal articles, and published evidence- and consensus-based clinical practice guidelines in the English language were identified, reviewed and evaluated.

DATA SYNTHESIS

Breast cancer is a biologically heterogeneous disease, leading to wide variability in treatment responses and survival outcomes. Biomarkers for breast cancer are evolving from traditional biomarkers in immunohistochemistry (IHC) such as estrogen receptor (ER), progesterone receptor (PR) and epidermal growth factor receptor type 2 (HER2) to genetic biomarkers with therapeutic implications (e.g. breast cancer susceptibility gene 1/2 [BRCA1/2], estrogen receptor α [ESR1] gene mutation, HER2 gene mutation, microsatellite instability [MSI], phosphatidylinositol 3-kinase catalytic subunit 3Cα [PIK3CA] gene mutation, neurotrophic tyrosine receptor kinase [NTRK] gene mutation). In addition, current data are most robust for biomarkers in immunotherapy (e.g. programmed cell death receptor ligand-1 [PD-L1], microsatellite instability-high [MSI-H] or deficient mismatch repair [dMMR]). Oncotype DX assay remains the best validated gene expression assay that is both predictive and prognostic whereas MammaPrint is prognostic for genomic risk.

CONCLUSIONS

Biomarker-driven therapies have the potential to confer greater therapeutic advantages than standard-of-care therapies. The purported survival benefits associated with biomarker-driven therapies should be weighed against their potential harms.

Tumor Mutational Burden in Breast Cancer: Current Evidence, Challenges, and Opportunities

Tumor mutational burden (TMB) correlates with tumor neoantigen burden, T cell infiltration, and response to immune checkpoint inhibitors in many solid tumor types. Based on data from the phase II KEYNOTE-158 study, the anti-PD-1 antibody pembrolizumab was granted approval for treating patients with advanced solid tumors and TMB ≥ 10 mutations per megabase. However, this trial did not include any patients with metastatic breast cancer; thus, several questions remain unanswered about the true role of TMB as a predictive biomarker of benefit to immune checkpoint inhibitor therapy in breast cancer. In this review, we will discuss the challenges and opportunities in establishing TMB as a predictive biomarker of benefit to immunotherapy in metastatic breast cancer.

Construction of a T-cell exhaustion-related gene signature for predicting prognosis and immune response in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy with a rising prevalence worldwide. Immunotherapy has been shown to improve treatment outcomes for HCC. We aimed to construct a T-cell exhaustion-related gene prognostic model (TEXPM) for HCC and to elucidate the immunologic characteristics and advantages of immunotherapy in T-cell exhaustion-Related Gene-defined HCC groups.

METHODS

Single-cell RNA sequencing data were used in conjunction with TCGA Differentially expressed genes (DEGs) to screen for T-cell exhaustion-Related Genes (TEXGs) for subsequent evaluation. Using univariate Cox regression analysis and LASSO regression analysis, five genes (FTL, GZMA, CD14, NPC2, and IER3) were subsequently selected for the construction of a TEXPM. Then, we evaluated the immunologic characteristics and advantages of immunotherapy in groups identified by TEXPM.

RESULTS

The TEXPM was formed with FTL, GZMA, CD14, NPC2, and IER3. The results of the training and validation team studies were consistent, with the low TEXPM group surviving longer than the high TEXPM group (P < 0.001). Multivariate Cox regression analysis demonstrated that TEXPM (HR: 2.347, 95%CI: 1.844-2.987; HR: 2.172, 95% CI: 1.689-2.793) was an independent prognostic variable for HCC patients. The low-TEXPM group was linked to active immunity, less aggressive phenotypes, strong infiltration of CD8+ T cells, CD4 + T cells, and M1 macrophages, and a better response to ICI treatment. A high TEXPM group, on the other hand, was associated with suppressive immunity, more aggressive phenotypes, a significant infiltration of B cells, M0 macrophages, and M2 macrophages, and a reduced response to ICI treatment. FTL is an independent prognostic variable in HCC patients and the knockdown of FTL can affect the biological behavior of hepatocellular carcinoma cells.

CONCLUSIONS

TEXPM is a promising prognostic biomarker connected to the immune system. Differentiating immunological and molecular features and predicting patient outcomes may be facilitated by TEXPM grouping. Furthermore, the expression of FTL was found to be an independent prognostic factor for HCC. Knockdown of FTL significantly inhibited proliferation, migration, and invasive activity in liver cancer cells.

Efficacy relevance of PD-L1 expression on circulating tumor cells in metastatic breast cancer patients treated with anti-PD-1 immunotherapy

PURPOSE

Breast cancer has become the leading cause of cancer mortality in women. Although immune checkpoint inhibitors targeting programmed death-1 (PD-1) are promising, it remains unclear whether PD-L1 expression on circulating tumor cells (CTCs) has predictive and prognostic values in predicting and stratifying metastatic breast cancer (MBC) patients who can benefit from anti-PD-1 immunotherapy.

METHODS

Twenty six MBC patients that received anti-PD-1 immunotherapy were enrolled in this study. The peptide-based Pep@MNPs method was used to isolate and enumerate CTCs from 2.0 ml of peripheral venous blood. The expression of PD-L1 on CTCs was evaluated by an established immunoscoring system categorizing into four classes (negative, low, medium, and high).

RESULTS

Our data showed that 92.3% (24/26) of patients had CTCs, 83.3% (20/26) of patients had PD-L1-positive CTCs, and 65.4% (17/26) of patients had PD-L1-high CTCs. We revealed that the clinical benefit rate (CBR) of patients with a cut-off value of ≥ 35% PD-L1-high CTCs (66.6%) was higher than the others (29.4%). We indicated that PD-L1 expression on CTCs from MBC patients treated with anti-PD-1 monotherapy was dynamic. We demonstrated that MBC patients with a cut-off value of ≥ 35% PD-L1-high CTCs had longer PFS (P = 0.033) and OS (P = 0.00058) compared with patients with a cut-off value of < 35% PD-L1-high CTCs.

CONCLUSION

Our findings suggested that PD-L1 expression on CTCs could predict the therapeutic response and clinical outcomes, providing a valuable predictive and prognostic biomarker for patients treated with anti-PD-1 immunotherapy.

Identification of a novel glycolysis-related prognosis risk signature in triple-negative breast cancer

Introduction

Triple-negative breast cancer (TNBC) is a particularly aggressive cluster of breast cancer characterized by significant molecular heterogeneity. Glycolysis is a metabolic pathway that is significantly associated with cancer progression, metastasis, recurrence and chemoresistance. However, the potential roles of glycolysis-related genes in TNBC remain unclear.

Methods

In the present study, we identified 108 glycolysis-related differentially expressed genes (DEGs) between breast cancer (BRCA) tumor tissues and normal tissues, and we divided patients into two different clusters with significantly distinct molecular characteristics, clinicopathological features, prognosis, immune cell infiltration and mutation burden. We then constructed a 10-gene signature that classified all TNBCs into low- and high-risk groups.

Results

The high-risk group had significantly lower survival than the low-risk group, which implied that the risk score was an independent prognostic indicator for TNBC patients. Consequently, we constructed and validated a prognostic nomogram, which accurately predicted individual overall survival (OS) of TNBC. Moreover, the risk score predicted the drug sensitivity of chemotherapeutic agents and immunotherapy for TNBC patients.

Discussion

The present comprehensive analysis of glycolysis-related DEGs in TNBC provides new methods for prognosis prediction and more effective treatment strategies.

Role of Surgical Pathologist for Detection of Predictive Immuno-oncological Factors in Breast Cancer

Immune checkpoint inhibitors (ICIs) have changed therapy strategies in breast cancer (BC) patients suffering from triple-negative breast cancer (TNBC). For example, in Europe the anti-programmed cell death 1 ligand 1 (PD-L1) ICI Azetolizumab is approved for adult patients with locally advanced or metastasized TNBC (mTNBC), depending on the immunohistochemical (IHC) PD-L1 expression of immune cells in the tumor area [immune cell (IC) score ≥1%); the anti-programmed cell death 1 (PD-1) ICI pembrolizumab is approved for mTNBC if PD-L1 Combined Positive Score (CPS), that is PD-L1 expression on tumor and/or immune cells, is ≥10. For early TNBC, in contrast, neoadjuvant use of pembrolizumab is approved in the United States and Europe independent from PD-L1 IHC expression. The determination of PD-L1 expression in tumor tissue to predict response to ICI therapy requires sensitive immunostaining with appropriate primary antibodies and staining protocols and a standardized and meticulous assessment of PD-L1 IHC stained breast cancer tissue slides. For the selection of the test material and continuous quality control of the dyeing, high standards must be applied. The evaluation is carried out according to various evaluation algorithms (scores). Here, the role of PD-L1 in BC and the currently most relevant PD-L1 assays and scores for TNBC will be explained. Furthermore, other tissue-based biomarkers potentially predictive for ICI therapy response in BC, for example, tumor mutational burden (TMB), will be presented in this review.

Immunotherapy of thymic epithelial tumors: molecular understandings and clinical perspectives

Immunotherapy has emerged to play a rapidly expanding role in the treatment of cancers. Currently, many clinical trials of therapeutic agents are on ongoing with majority of immune checkpoint inhibitors (ICIs) especially programmed death receptor 1 (PD-1) and its ligand 1 (PD-L1) inhibitors. PD-1 and PD-L1, two main immune checkpoints, are expressed at high levels in thymic epithelial tumors (TETs) and could be predictors of the progression and immunotherapeutic efficacy of TETs. However, despite inspiring efficacy reported in clinical trials and clinical practice, significantly higher incidence of immune-related adverse events (irAEs) than other tumors bring challenges to the administration of ICIs in TETs. To develop safe and effective immunotherapeutic patterns in TETs, understanding the clinical properties of patients, the cellular and molecular mechanisms of immunotherapy and irAEs occurrence are crucial. In this review, the progress of both basic and clinical research on immune checkpoints in TETs, the evidence of therapeutic efficacy and irAEs based on PD-1 /PD-L1 inhibitors in TETs treatment are discussed. Additionally, we highlighted the possible mechanisms underlying irAEs, prevention and management strategies, the insufficiency of current research and some worthy research insights. High PD-1/PD-L1 expression in TETs provides a rationale for ICI use. Completed clinical trials have shown an encouraging efficacy of ICIs, despite the high rate of irAEs. A deeper mechanism understanding at molecular level how ICIs function in TETs and why irAEs occur will help maximize the immunotherapeutic efficacy while minimizing irAEs risks in TET treatment to improve patient prognosis.

Comprehensive analysis of cuproptosis-related long non-coding RNA signature and personalized therapeutic strategy of breast cancer patients

Background

Breast cancer (BC) is considered to be one of the primary causes of cancer deaths in women. Cuproptosis was suggested to play an important role in tumor proliferation and tumor immune microenvironment. Therefore, an investigation was conducted to identify the relationship between cuproptosis-related long non-coding RNAs (lncRNAs) and BC prognosis.

Method

Based on The Cancer Genome Atlas (TCGA), nine cuproptosis-related lncRNAs were identified by Pearson's analysis and Cox regression analysis to create a cuproptosis-related lncRNA signature. Subsequently, patients with BC were divided into high-risk and low-risk groups. The Kaplan-Meier curves and a time-dependent receiver operating characteristic (ROC) analysis were employed to elucidate the predictive capability of the signature. After that, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted by Gene Set Enrichment Analysis (GSEA), and the lncRNA-mRNA co-expression network was established by Cytoscape software. Furthermore, the ESTIMATE score was calculated, and the immune cell type component analysis was conducted. Eventually, immunotherapy response analysis was applied to identify the predictive power of cuproptosis-related lncRNAs to tumor immunotherapy response, including immune checkpoint gene expression levels, tumor mutational burden (TMB), and microsatellite instability (MSI).

Results

Patients with BC in the low-risk groups showed better clinical outcomes. The KEGG pathways in the high-risk groups were mainly enriched in immune response and immune cell activation. Furthermore, the ESTIMATE scores were higher in the low-risk groups, and their immune cell infiltrations were dramatically different from those of the high-risk groups. The low-risk groups were shown to have higher infiltration levels of CD8+ T cells and TMB-high status, resulting in better response to immunotherapies.

Conclusion

The findings of this study revealed that the nine-cuproptosis-related lncRNA risk score was an independent prognostic factor for BC. This signature was a potential predictor for BC immunotherapy response. What we found will provide novel insight into immunotherapeutic treatment strategies in BC.

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.

APOBEC Mutational Signatures in Hormone Receptor-Positive Human Epidermal Growth Factor Receptor 2-Negative Breast Cancers Are Associated With Poor Outcomes on CDK4/6 Inhibitors and Endocrine Therapy

PURPOSE

APOBEC mutagenesis underlies somatic evolution and accounts for tumor heterogeneity in several cancers, including breast cancer (BC). In this study, we evaluated the characteristics of a real-world cohort for time-to-treatment discontinuation (TTD) and overall survival on CDK4/6 inhibitors (CDK4/6i) plus endocrine therapy (ET) and immune checkpoint inhibitors.

METHODS

Comprehensive genomic profiling results from 29,833 BC samples were analyzed for tumor mutational burden and APOBEC signatures. For clinical outcomes, a deidentified nationwide (United States-based) BC Clinico-Genomic Database (CGDB) was evaluated with log-rank and Cox models. Patients with hormone receptor-positive (HR+) human epidermal growth factor receptor 2-negative (HER2-) BC who received first-line ET and CDK4/6i were included. Eligible patients from Mayo Clinic and Duke University were HR+ HER2- BC with sequencing data between September 2013 and July 2020.

RESULTS

Of 29,833 samples sequenced, 7.9% were APOBEC+ with a high rate in invasive lobular carcinoma (16.7%) and in metastatic tumors (9.7%) relative to locally biopsied BC (4.3%; P < .001). In CGDB, 857 patients with HR+ HER2- BC received ET plus CDK4/6i in the first line. APOBEC+ patients had significantly shorter TTD on ET plus CDK4/6i than APOBEC- patients, 7.8 (95% CI, 4.3 to 14.6) versus 12.4 months (95% CI, 11.2 to 14.1; hazard ratio, 1.6; 95% CI, 1.03 to 2.39; P = .0036). Clinical benefit to immune checkpoint inhibitors was observed in HR+ HER2-, APOBEC+, tumor mutational burden-high patients, with four of nine CGDB patients (TTD 0.3-11.3 months) and four of six patients in Duke/Mayo cohorts (TTD 0.9-40.5 months) with a TTD of ≥ 3 months.

CONCLUSION

APOBEC+ HR+ HER2- patients had shorter TTD on first-line ET plus CDK4/6i relative to APOBEC- patients. Further research is needed to optimize the treatment of APOBEC+ HR+ HER2- BC and to investigate the efficacy of immunotherapeutic strategies in this population.

Aberrant APOBEC3C expression induces characteristic genomic instability in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a well-known lethal and heterogeneous disease. Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) is an important mutagenic driver that has seldom been investigated in PDAC. Therefore, this study investigated the significance of APOBEC3C in PDAC. First, cytosine deamination-associated mutation signatures were identified in the PDAC cohorts from TCGA and Fudan University Shanghai Cancer Center (FUSCC) datasets, and C > X-enriched kataegis regions were identified in the FUSCC cohort (12 to 27 counts per sample). Patients were stratified according to APOBEC3C expression, and high APOBEC3C expression was found to correlate with a higher motif enrichment score of 5'-CC-3' and an elevated kataegis count within PCSK5 and NES genes. Second, we compared APOBEC expression in PDAC and normal pancreatic tissues and found that APOBEC3C was substantially upregulated in PDAC. APOBEC3C-overexpressing cell lines were generated to substantiate the effects of APOBEC3C on PDAC genome, including alterations in single-nucleotide variant (SNV) classes (higher proportion of C > T conversions) and the formation of kataegis regions (newly occurring kataegis regions detected in ACHE and MUC6 genes). Three different PDAC cohorts (FUSCC, TCGA, and QCMG) were analysed to evaluate the prognostic value of APOBEC3C, and APOBEC3C overexpression predicted shorter survival. Finally, the APOBEC3C overexpression correalted with the PDAC tumour microenvironment (TME) remodelling, APOBEC3C expression was associated with the invasion of CD4 + T lymphocytes and CD8 + T lymphocytes (cytotoxic T lymphocytes, CTLs), indicating enhanced immune activity and validating the practicality of APOBEC3C for guiding immunotherapy.

Up-Regulated MISP Is Associated With Poor Prognosis and Immune Infiltration in Pancreatic Ductal Adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant disease with a poor prognosis. More effective biomarkers and treatment options remain to be discovered. Mitotic Spindle Positioning (MISP), also called C19orf21, has been reported to be upregulated in several malignancies. However, the effects of MISP on PDAC have yet to be investigated.

Materials and Methods

The differential expression of MISP at the mRNA and protein levels were evaluated using Gene Expression Profiling Interactive Analysis 2 (GEPIA 2), Gene Expression Omnibus (GEO), and the Human Protein Atlas (HPA) databases, and was further verified by quantitative real-time PCR and western blotting in PDAC cell lines. Correlations between MISP expression and clinical characteristics were explored using Kaplan-Meier Plotter Database and clinical data from The Cancer Genome Atlas (TCGA). CCK-8 assays, Transwell assays, and immunoblotting were used to determine the role of MISP in PDAC proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in vitro. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were executed by the R package ‘clusterProfiler’. Correlations between MISP expression and immune cell infiltration, immune checkpoints, immunophenoscore (IPS) and the tumor mutational burden (TMB) in PDAC were explored using the R package ‘CIBERSORT’, the Tumor Immune Estimation Resource 2.0 (TIMER2.0), and The Cancer Immunome Atlas (TCIA) database based on TCGA data.

Result

MISP expression was significantly higher in pancreatic cancer tissues compared to normal pancreas tissues, which was associated with a poor prognosis. Increased expression of MISP was related to the proliferation, migration and invasion of PDAC cell lines. GO and KEGG pathway analyses determined that MISP is involved in the Ras signaling pathway and immune regulation. Higher expression of MISP was associated with decreased infiltration levels of activated CD4+ memory T cells, CD8+ T cells, M2 macrophages and neutrophils. Furthermore, increased MISP was associated with lower expression of immune checkpoint molecules, higher gene mutation burden and IPS.

Conclusions

This study reveals that MISP, which is associated with the progression and prognosis of PDAC, may exert a potential regulatory effect on immune infiltration and predict the response to immunotherapy in PDAC.

Pyroptosis-Related lncRNAs Predict the Prognosis and Immune Response in Patients With Breast Cancer

Background: Breast cancer (BC) is the most common malignant tumor and the leading cause of cancer-related death in women worldwide. Pyroptosis and long noncoding RNAs (lncRNAs) have been demonstrated to play vital roles in the tumorigenesis and development of BC. However, the clinical significance of pyroptosis-related lncRNAs in BC remains unclear.

Methods: Using the mRNA and lncRNA profiles of BC obtained from TCGA dataset, a risk model based on the pyroptosis-related lncRNAs for prognosis was constructed using univariate and multivariate Cox regression model, and least absolute shrinkage and selection operator. Patients were divided into high- and low-risk groups based on the risk model, and the prognosis value and immune response in different risk groups were analyzed. Furthermore, functional enrichment annotation, therapeutic signature, and tumor mutation burden were performed to evaluate the risk model we established. Moreover, the expression level and clinical significance of the selected pyroptosis-related lncRNAs were further validated in BC samples.

Results: 3,364 pyroptosis-related lncRNAs were identified using Pearson’s correlation analysis. The risk model we constructed comprised 10 pyroptosis-related lncRNAs, which was identified as an independent predictor of overall survival (OS) in BC. The nomogram we constructed based on the clinicopathologic features and risk model yielded favorable performance for prognosis prediction in BC. In terms of immune response and mutation status, patients in the low-risk group had a higher expression of immune checkpoint markers and exhibited higher fractions of activated immune cells, while the high-risk group had a highly percentage of TMB. Further analyses in our cohort BC samples found that RP11-459E5.1 was significantly upregulated, while RP11-1070N10.3 and RP11-817J15.3 were downregulated and significantly associated with worse OS.

Conclusion: The risk model based on the pyroptosis-related lncRNAs we established may be a promising tool for predicting the prognosis and personalized therapeutic response in BC patients.

Combination of Tumor Mutational Burden and Specific Gene Mutations Stratifies Outcome to Immunotherapy Across Recurrent and Metastatic Head and Neck Squamous Cell Carcinoma

Purpose: To investigate the prognostic significance of tumor mutational burden (TMB) combined with specific prognosis-related gene mutations in immunotherapy for recurrent and metastatic head and neck squamous cell carcinoma (r/m HNSCC).

Methods: One hundred thirty-two r/m HNSCC patients from the Morris and Allen cohorts had undergone immunotherapy. We constructed the immunotherapy-related gene prognostic index TP-PR combining TMB and PIK3CA, TP53, or ROS1 mutation. And we analyzed the differences in overall survival (OS) and immune cell infiltration between samples in different groups. The association of each signature’s single-sample gene set enrichment analysis scores with TP-PR was tested using Spearman’s correlation test.

Results: The median OS of the patients with high TMB (TMB ≥10 mut/Mb) who received immunotherapy for r/m HNSCC was 2.5 times as long as that of the patients with low TMB (25 vs. 10 months). More importantly, the high TP-PR (TP-PR >0) group had better median OS (25 vs. 8 months) than the low TP-PR (TP-PR ≤0) group. CD8⁺ T cells and activated memory CD4⁺ T cells in the tissues of the patients with high TP-PR were higher than those in the patients with low TP-PR. Results showed that TP-PR stratification had a higher area under the curve (AUC) value (0.77, 95% CI 0.86–0.68) compared with TMB stratification (0.56, 95% CI 0.68–0.44). The differential gene expression in the high and low TP-PR groups mainly influenced metabolism-related signaling pathways.

Conclusion: TP-PR was an effective predictor of immunotherapy outcome for r/m HNSCC, which might be better than TMB alone. Patients with high TP-PR had a better survival benefit than had the patients with low TP-PR.

Biomarkers of immunotherapy response in breast cancer beyond PD-L1

Immune checkpoint inhibitors have modified the treatment algorithm in a variety of cancer types, including breast cancer. Nevertheless, optimal selection of ideal candidates to these drugs remains an unmet need. Although PD-L1 expression by immunohistochemistry seems to be the most promising biomarker to date, its predictive ability is far from ideal. Thus, the development of new predictive biomarkers is essential for a better selection of patients. Here, we discuss potential biomarkers beyond PD-L1 that could play an important role in precision cancer immunotherapy.

Tissue-agnostic drug approvals: how does this apply to patients with breast cancer?

Precision medicine has provided new perspectives in oncology, yielding research on the use of targeted therapies across different tumor types, regardless of their site of origin, a concept known as tissue-agnostic indication. Since 2017, the Food and Drug Administration (FDA) has approved the use of three different agents for tumor-agnostic treatment: pembrolizumab (for patients with microsatellite instability or high tumor mutational burden) and larotrectinib and entrectinib (both for use in patients harboring tumors with NTRK fusions). Importantly, the genomic alterations targeted by these agents are uncommon or rare in breast cancer, and little information exists regarding their efficacy in advanced breast cancer. In this review, we discuss the prevalence of these targets in breast cancer, their detection methods, the clinical characteristics of patients whose tumors have these alterations, and available data regarding the efficacy of these agents in breast cancer.

Immunotherapy in Breast Cancer Patients: A Focus on the Use of the Currently Available Biomarkers in Oncology

Immune checkpoint inhibitors (ICIs) have remarkably modified the way solid tumors are managed, including breast cancer. Unfortunately, only a relatively small number of breast cancer patients significantly respond to these treatments. To maximize the immunotherapy benefit in breast cancer, several efforts are currently being put forward for the identification of i) the best therapeutic strategy (i.e. ICI monotherapy or in association with chemotherapy, radiotherapy, or other drugs); ii) the optimal timing for administration (e.g. early/advanced stage of disease; adjuvant/neoadjuvant setting); iii) the most effective and reliable predictive biomarkers of response (e.g. tumor-infiltrating lymphocytes, programmed death-ligand 1, microsatellite instability associated with mismatch repair deficiency, and tumor mutational burden). This article reviews the impacts and gaps in the characterization of immune-related biomarkers raised by clinical and translational research studies with immunotherapy treatments. Particular emphasis has been put on the documented evidence of significant clinical benefits of ICI in different randomized clinical trials, along with preanalytical and analytical issues in predictive biomarkers pathological assessment.

Tumor mutational burden as a predictor of immunotherapy response in breast cancer

Tumor mutational burden (TMB) is a promising tool to help define patients with triple-negative breast cancer (TNBC) most likely to benefit from immune checkpoint blockade (ICB) therapies. Roughly reflecting the degree of neo-antigens that tumors present to immune cells, TMB associates with multiple measures of tumoral immunogenicity and has proven clinically useful in cancers with relatively high mutation burden. TNBC carries higher TMB than other breast cancer subtypes, and recent data suggest that high-TMB TNBC cases may derive particular benefit from ICB in combination with chemotherapy (GeparNuevo, IMpassion130) or even ICB alone (KEYNOTE-119, TAPUR). Given the recent approval of pembrolizumab and atezolizumab in combination with chemotherapy for PD-L1-positive, metastatic TNBC, standardizing TMB calculation methods and cut-off values is of critical importance to deploy this clinical biomarker.

Update Breast Cancer 2020 Part 4 - Advanced Breast Cancer

Substances with good effectiveness that intervene in specific signalling pathways have been used increasingly in recent years in the treatment of patients with advanced breast cancer, and new therapies and approaches have now been added, which actually relate to quite specific changes, such as the treatment of patients with HR+/HER2 tumours with a PIK3CA mutation. The treatment of patients with a BRCA1 or BRCA2 mutation has also been improved by the introduction of PARP inhibitors. Attempts are now being made increasingly to extend treatment indications based on molecular patterns, to identify other patients who could benefit from a treatment and to integrate the newly established treatment methods in existing therapy sequences. This review articles summarises the latest information in this connection.

Are we ready to use TMB in breast cancer clinical practice?

We discussed the potentialities of tumor mutation burden (TMB) as a predictive marker for immunotherapy in breast cancer, also highlighting the limits that have hindered its introduction in the clinical practice. Although some studies have demonstrated the possibility to select patients more responsive to immune-checkpoint inhibitors by evaluating TMB, some issues emerged regarding the complexity of the methodologies for its determination, the costs of the analysis, and the necessity to improve the TMB determination with that of neoantigen identification.