Immune gene expression profiling reveals heterogeneity in luminal breast tumors

Evaluation of immunophenotype and inflammation in canine mammary neoplasms with solid arrangement

Morphological and immunohistochemical studies of solid arrangement canine mammary carcinomas have shown that the different histological types may be characterized by proliferation of epithelial and/or myoepithelial cells. However, little is known about immunophenotypes and the importance of inflammation as prognostic factors in these neoplasms. The objective of the present study was to characterize the immunophenotype and degree of inflammation in the solid type of canine mammary neoplasm and to investigate their association with metastasis, Ki-67 index, tumour size, necrosis and survival. Sixty-five carcinomas with solid pattern, basaloid carcinomas, solid papillary carcinomas, malignant adenomyoepitheliomas (MAMEs) or malignant myoepitheliomas (MMEs) were investigated. Luminal A, luminal B HER2 negative and HER2 positive, HER2 overexpressed and triple negative immunophenotypes were immunolabelled as were Ki-67 protein and cyclooxygenase-2 (Cox-2). Histological peritumoural and intratumoural inflammatory infiltrates were graded (distribution × intensity) and the presence of necrosis identified. We found a statistical difference between histological types and immunophenotypes, with MME and MAME having a higher occurrence of luminal A, whereas most neoplasms had the luminal B HER-negative immunophenotype. There was no correlation between immunophenotype and degree of peri- and intratumoural inflammation, nodal metastasis, necrosis or tumour size. An increased degree of peri- and intratumoural inflammation was significantly associated with lymph node metastasis, and more severe intratumoural inflammation was associated with the presence of tumour necrosis. Tumour size, Ki-67 index and Cox-2 score were not associated with inflammation in either peri- or intratumoural regions. No difference was observed in survival in relation to immunophenotype or degree of inflammation, but the Cox regression model revealed that nodal metastasis influenced the risk of death.

High tumour-infiltrating lymphocytes correlate with distinct gene expression profile and favourable survival in single hormone receptor-positive breast cancer

Introduction

This study aimed to evaluate the impact of tumour-infiltrating lymphocytes (TILs) on the expression of immune-related genes and prognosis in single hormone receptor-positive breast cancer. Material and methods: Tumour-infiltrating lymphocytes were analysed according to the guidelines of the International TILs Working Group in a cohort of 206 patients with single hormone receptor-positive breast cancer. Of these, 44.7% were classified as ER+/PgR-/HER2-, 18.4% as ER+/PgR-/HER2+, 26.2% as ER-/PgR+/HER2-, and 10.7% as ER-/PgR+/HER2+. Moreover, in 52 samples the analysis of gene expression profiling was performed using nCounter technology.

Results

Most cases (74.3%) showed at least 1% of stromal TILs, with a median of 4%, mean of 16.3%, and interquartile range of 0-20%. ER-/PgR+ tumours displayed significantly higher TILs density than ER+/PgR- cases (p < 0.001, Wilcoxon test), regardless of HER2 status. The abundance of TILs was positively associated with ER-/PgR+ phenotype, higher Ki-67, and higher grade, but not with age, tumour size, or regional and distant metastases at diagnosis. Additionally, in ER+/PgR- subgroup higher TILs were associated with HER2-positive status. Stromal TILs > 5% were associated with better survival in the whole group, but this effect was less prominent in ER-/PgR+ patients. We identified 50 differentially expressed genes (DEGs) between single hormone receptor-positive breast tumours with high and low TILs, including 39 up-regulated and 11 down-regulated genes in the high TILs group.

Conclusions

The up-regulated expression of immune-related genes was consistent also among separately analysed single hormone receptor-positive groups (ER+/PgR- and ER-/PgR+).

Clustering of HR + /HER2- breast cancer in an Asian cohort is driven by immune phenotypes

Breast cancer exhibits significant heterogeneity, manifesting in various subtypes that are critical in guiding treatment decisions. This study aimed to investigate the existence of distinct subtypes of breast cancer within the Asian population, by analysing the transcriptomic profiles of 934 breast cancer patients from a Malaysian cohort. Our findings reveal that the HR + /HER2- breast cancer samples display a distinct clustering pattern based on immune phenotypes, rather than conforming to the conventional luminal A-luminal B paradigm previously reported in breast cancers from women of European descent. This suggests that the activation of the immune system may play a more important role in Asian HR + /HER2- breast cancer than has been previously recognized. Analysis of somatic mutations by whole exome sequencing showed that counter-intuitively, the cluster of HR + /HER2- samples exhibiting higher immune scores was associated with lower tumour mutational burden, lower homologous recombination deficiency scores, and fewer copy number aberrations, implicating the involvement of non-canonical tumour immune pathways. Further investigations are warranted to determine the underlying mechanisms of these pathways, with the potential to develop innovative immunotherapeutic approaches tailored to this specific patient population.

Clinical activity of nivolumab in combination with eribulin in HER2-negative metastatic breast cancer: A phase IB/II study (KCSG BR18-16)

AIM

We evaluated the efficacy and safety of nivolumab and eribulin combination therapy for metastatic breast cancer (BC) in Asian populations.

METHODS

In this parallel phase II study, adult patients with histologically confirmed recurrent/metastatic hormone receptor-positive/HER2-negative (HR+HER2-) or triple-negative BC (TNBC) were prospectively enroled from 10 academic hospitals in Korea (ClinicalTrials.gov Identifier: NCT04061863). They received nivolumab (360 mg) on day 1 plus eribulin (1.4 mg/m2) on days 1 and 8 every 3 weeks until disease progression or intolerable toxicity. The primary endpoint was the investigator-assessed 6-month progression-free survival (PFS) rate in each subtype. Secondary endpoints included investigator-assessed objective response rate (ORR) as per Response Evaluation Criteria in Advanced Solid Tumors version 1.1, disease control rate, overall survival, and treatment toxicity. The association between PD-L1 expression and efficacy was investigated.

RESULTS

Forty-five patients with HR+HER2- BC and 45 with TNBC were enroled. Their median age was 51 (range, 31-71) years, and 74 (82.2%) received one or two prior treatments before enrolment. Six-month PFS was 47.2% and 25.1% in the HR+HER2- and TNBC cohorts, respectively. Median PFS was 5.6 (95% confidence interval [CI]: 5.3-7.4) and 3.0 (95% CI: 2.1-5.2) months in the HR+HER2- and TNBC groups, respectively. ORRs were 53.3% (complete response [CR]: 0, partial response [PR]: 24) and 28.9% (CR: 1, PR: 12). Patients with PD-L1+ tumours (PD-L1 expression ≥1%) and PD-L1- tumours (ORR 50% versus 53.8% in HR+HER2-, 30.8% versus 29.0% in TNBC) had similar ORRs. Neutropenia was the most common grade 3/4 adverse event; the most common immune-related adverse events (AEs) were grades 1/2 hypothyroidism and pruritus. Five patients discontinued therapy because of immune-related AEs.

CONCLUSION

Nivolumab plus eribulin showed promising efficacy and tolerable safety in previously treated HER2- metastatic BC.

TRIAL REGISTRATION

NCT04061863.

YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration

PURPOSE

Thyroid cancer (TC) is one of the most common endocrine malignancies, and its morbidity continues to rise. N6-methyladenosine (m6A) RNA methylation, an epigenetic modification, is an important regulator of gene expression in TC. Therefore, it's worth finding the characteristics and predictive value of the m6A RNA methylation regulators in thyroid cancer (TC).

METHOD

RNA-seq data of TC was downloaded from the Cancer Genome Atlas (TCGA) database to screen out the differential expressed regulators. The absolute contraction selection operator (Lasso) Cox regression was used to construct the risk model of m6A methylation regulators. The predictive value of the risk scoring model was evaluated by Kaplan Meier (K-M) analysis and receiver operating characteristic (ROC) curves. The underlying mechanism of m6A methylation regulators in TC was predicted by gene set enrichment analysis (GSEA). Further validation was performed by using immunohistochemistry (IHC) and q-PCR. The correlation between risk-related gene and immune infiltration was evaluated by Tumour Immune Estimation Resource (TIMER).

RESULTS

IGF2BP2, YTHDF1 and YTHDF3 were screened out as strong independent prognostic factors of TC. Then a risk score model was established to further screen the predictors. Finally, according to the results of overall survival (OS) and clinical characteristics of TC, YTHDF3 was screened out as a potential predictor. Meanwhile, IHC and qPCR confirmed that YTHDF3 was expressed differential in TC. The expression of YTHDF3 was positively associated with the infiltration level of CD4+ T cells and macrophages. It was strongly correlated with a variety of immune markers in TC.

CONCLUSION

We confirmed that YTHDF3 can be used as a potential prognostic biomarker of TC. It not only plays a decisive role in the initiation and development of TC, but also provides a new perspective for understanding the modification of m6A RNA in TC.

Exploration of prognosis and immunometabolism landscapes in ER+ breast cancer based on a novel lipid metabolism-related signature

Introduction

Lipid metabolic reprogramming is gaining attention as a hallmark of cancers. Recent mounting evidence indicates that the malignant behavior of breast cancer (BC) is closely related to lipid metabolism. Here, we focus on the estrogen receptor-positive (ER+) subtype, the most common subgroup of BC, to explore immunometabolism landscapes and prognostic significance according to lipid metabolism-related genes (LMRGs).

Methods

Samples from The Cancer Genome Atlas (TCGA) database were used as training cohort, and samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), Gene Expression Omnibus (GEO) datasets and our cohort were applied for external validation. The survival-related LMRG molecular pattern and signature were constructed by unsupervised consensus clustering and least absolute shrinkage and selection operator (LASSO) analysis. A lipid metabolism-related clinicopathologic nomogram was established. Gene enrichment and pathway analysis were performed to explore the underlying mechanism. Immune landscapes, immunotherapy and chemotherapy response were further explored. Moreover, the relationship between gene expression and clinicopathological features was assessed by immunohistochemistry.

Results

Two LMRG molecular patterns were identified and associated with distinct prognoses and immune cell infiltration. Next, a prognostic signature based on nine survival-related LMRGs was established and validated. The signature was confirmed to be an independent prognostic factor and an optimal nomogram incorporating age and T stage (AUC of 5-year overall survival: 0.778). Pathway enrichment analysis revealed differences in immune activities, lipid biosynthesis and drug metabolism by comparing groups with low- and high-risk scores. Further exploration verified different immune microenvironment profiles, immune checkpoint expression, and sensitivity to immunotherapy and chemotherapy between the two groups. Finally, arachidonate 15-lipoxygenase (ALOX15) was selected as the most prominent differentially expressed gene between the two groups. Its expression was positively related to larger tumor size, more advanced tumor stage and vascular invasion in our cohort (n = 149).

Discussion

This is the first lipid metabolism-based signature with value for prognosis prediction and immunotherapy or chemotherapy guidance for ER+ BC.

LINC00426 is a potential immune phenotype-related biomarker and an overall survival predictor in PAM50 luminal B breast cancer

Background: Breast cancer (BRCA) represents the most frequent diagnosed malignancy in women worldwide. Despite treatment advances, BRCAs eventually develop resistance to targeted therapies, resulting in poor prognosis. The identification of new biomarkers, like immune-related long non-coding RNAs (lncRNAs), could contribute to the clinical management of BRCA patients. In this report, we evaluated the LINC00426 expression in PAM50 BRCA subtypes from two clinical independent cohorts (BRCA-TCGA and GEO-GSE96058 datasets). Methods and results: Using Cox regression models and Kaplan-Meier survival analyses, we identified that LINC00426 expression was a consistent overall survival (OS) predictor in luminal B (LB) BRCA patients. Subsequently, differential gene expression and gene set enrichment analyses identified that LINC00426 expression was associated with different immune-related and cancer-related pathways and processes in LB BRCA. Additionally, the LINC00426 expression was correlated with the infiltration level of diverse immune cell populations, alongside immune checkpoint and cytolytic activity-related gene expression. Conclusion: This evidence suggests that LINC00426 is a potential biomarker of immune phenotype and an OS predictor in PAM50 LB BRCA.

TP53 somatic mutations in Asian breast cancer are associated with subtype-specific effects

BACKGROUND

Recent genomics studies of breast cancer in Asian cohorts have found a higher prevalence of TP53 mutations in Asian breast cancer patients relative to Caucasian patients. However, the effect of TP53 mutations on Asian breast tumours has not been comprehensively studied.

METHODS

Here, we report an analysis of 492 breast cancer samples from the Malaysian Breast Cancer cohort where we examined the impact of TP53 somatic mutations in relation to PAM50 subtypes by comparing whole exome and transcriptome data from tumours with mutant and wild-type TP53.

RESULTS

We found that the magnitude of impact of TP53 somatic mutations appears to vary between different subtypes. TP53 somatic mutations were associated with higher HR deficiency scores as well as greater upregulation of gene expression pathways in luminal A and luminal B tumours compared to the basal-like and Her2-enriched subtypes. The only pathways that were consistently dysregulated when comparing tumours with mutant and wild-type TP53 across different subtypes were the mTORC1 signalling and glycolysis pathways.

CONCLUSION

These results suggest that therapies that target TP53 or other downstream pathways may be more effective against luminal A and B tumours in the Asian population.

Tumour Infiltrating Lymphocytes (TILs) and immune composition in breast cancer patients from Kenya: Spatial distributions and associations with risk factors and tumour characteristics

BACKGROUND

The immune landscape of breast cancer (BC) in patients from Sub Saharan Africa is understudied. Our aims were to describe the distribution of Tumour Infiltrating Lymphocytes (TILs) within the intratumoural stroma (sTILs) and the leading/invasive edge stroma (LE-TILs), and to evaluate TILs across BC subtypes with established risk factors and clinical characteristics in Kenyan women.

METHODS

Visual quantification of sTILs and LE-TILs were performed on Haematoxylin and eosin -stained pathologically confirmed BC cases based on the International TIL working group guidelines. Tissue Microarrays were constructed and stained with immunohistochemistry (IHC) for CD3, CD4, CD8, CD68, CD20, and FOXP3. Linear and logistic regression models were used to assess associations between risk factors and tumour features with IHC markers and total TILs, after adjusting for other covariates.

RESULTS

A total of 226 invasive BC cases were included. Overall, LE-TIL (mean = 27.9, SD = 24.5) proportions were significantly higher than sTIL (mean = 13.5, SD = 15.8). Both sTILs and LE- TILs were predominantly composed of CD3, CD8, and CD68. We found higher TILs to be associated with high KI67/high grade and aggressive tumour subtypes, although these associations varied by TIL locations. Older age at menarche (≥ 15 vs. < 15 years) was associated with higher CD3 (OR: 2.06, 95%CI:1.26-3.37), but only for the intra-tumour stroma.

CONCLUSION

The TIL enrichment in more aggressive BCs is similar to previously published data in other populations. The distinct associations of sTIL/LE-TIL measures with most examined factors highlight the importance of spatial TIL evaluations in future studies.

DNA methylation age in paired tumor and adjacent normal breast tissue in Chinese women with breast cancer

BACKGROUND

Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong.

METHODS

We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors.

RESULTS

DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA.

CONCLUSIONS

Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.

Tumor Infiltrating Lymphocytes across Breast Cancer Subtypes: Current Issues for Biomarker Assessment

Tumor-infiltrating lymphocytes (TILs) represent a surrogate biomarker of anti-tumor, lymphocyte-mediated immunity. In early, triple-negative breast cancer, TILs have level 1B of evidence to predict clinical outcomes. TILs represent a promising biomarker to select patients who can experience a better prognosis with de-intensified cancer treatments and derive larger benefits from immune checkpoint inhibitors. However, the assessment and the validation of TILs as a biomarker require a prospective and rigorous demonstration of its clinical validity and utility, provided reproducible analytical performance. With pending data about the prospective validation of TILs' clinical validity to modulate treatments in early breast cancer, this review summarizes the most important current issues and future challenges related to the implementation of TILs assessments across all breast cancer subtypes and their potential integration into clinical practice.

Racial/Ethnic Differences Among Tumor-Infiltrating Lymphocytes in Breast Cancer Tumors

PURPOSE

Tumor-infiltrating lymphocytes (TILs) have emerged as a predictor of breast cancer treatment response and patient outcomes. Current studies investigating racial/ethnic differences in TILs and immune profiles in breast cancer offer varying results. Our study provides some preliminary data in the breast cancer tumor microenvironment where there is a paucity of information, from Asian and Native Hawaiian/Pacific Islander (NHPI) racial/ethnic groups, not well represented in the literature.

METHODS

We reviewed 183 cases of women diagnosed with early stage breast cancer who received neoadjuvant treatment at 2 large health systems in Hawaii between 2008 and 2020. We evaluated clinical and demographic information including: age at diagnosis, self-reported race/ethnicity, tumor stage, tumor subtype according to ER, PR, and HER2 receptor status, the amount of TILs and pathologic complete response (pCR).

RESULTS

We found a significantly greater amount of TILs in Asians (37.7%, P = .01) and NHPI (37.2%, P = .02) patients compared to White patients on multivariate analysis. We found no significant differences in pCR among the different racial/ethnic groups.

CONCLUSIONS

Racial/ethnic differences in the amount of TILs in breast cancer tumors may suggest differences in the breast tumor microenvironment. This may in part contribute to known outcome disparities in these populations and should be further evaluated.

Characterisation of the immune microenvironment of primary breast cancer and brain metastasis reveals depleted T-cell response associated to ARG2 expression

BACKGROUND

Immune checkpoint inhibition is an established treatment in programmed death-ligand 1 (PD-L1)-positive metastatic triple-negative (TN) breast cancer (BC). However, the immune landscape of breast cancer brain metastasis (BCBM) remains poorly defined.

MATERIALS AND METHODS

The tumour-infiltrating lymphocytes (TILs) and the messenger RNA (mRNA) levels of 770 immune-related genes (NanoString™, nCounter™ Immuno-oncology IO360) were assessed in primary BCs and BCBMs. The prognostic role of ARG2 transcripts and protein expression in primary BCs and its association with outcome was determined.

RESULTS

There was a significant reduction of TILs in the BCBMs in comparison to primary BCs. 11.5% of BCs presented a high immune infiltrate (hot), 46.2% were altered (immunosuppressed/excluded) and 34.6% were cold (no/low immune infiltrate). 3.8% of BCBMs were hot, 23.1% altered and 73.1% cold. One hundred and twelve immune-related genes including PD-L1 and CTLA4 were decreased in BCBM compared to the primary BCs (false discovery rate <0.01, log2 fold-change >1.5). These genes are involved in matrix remodelling and metastasis, cytokine-chemokine signalling, lymphoid compartment, antigen presentation and immune cell adhesion and migration. Immuno-modulators such as PD-L1 (CD274), CTLA4, TIGIT and CD276 (B7H3) were decreased in BCBMs. However, PD-L1 and CTLA4 expression was significantly higher in TN BCBMs (P = 0.01), with CTLA4 expression also high in human epidermal growth factor receptor 2-positive (P < 0.01) compared to estrogen receptor-positive BCBMs. ARG2 was one of four genes up-regulated in BCBMs. High ARG2 mRNA expression in primary BCs was associated with worse distant metastasis-free survival (P = 0.038), while ARG2 protein expression was associated with worse breast-brain metastasis-free (P = 0.027) and overall survival (P = 0.019). High transcript levels of ARG2 correlated to low levels of cytotoxic and T cells in both BC and BCBM (P < 0.01).

CONCLUSION

This study highlights the immunological differences between primary BCs and BCBMs and the potential importance of ARG2 expression in T-cell depletion and clinical outcome.

Classification of Subgroups with Immune Characteristics Based on DNA Methylation in Luminal Breast Cancer

Luminal breast cancer (BC) accounts for a large proportion of patients in BC, with high heterogeneity. Determining the precise subtype and optimal selection of treatment options for luminal BC is a challenge. In this study, we proposed an MSBR framework that integrate DNA methylation profiles and transcriptomes to identify immune subgroups of luminal BC. MSBR was implemented both on a key module scoring algorithm and “Boruta” feature selection method by DNA methylation. Luminal A was divided into two subgroups and luminal B was divided into three subgroups using the MSBR. Furthermore, these subgroups were defined as different immune subgroups in luminal A and B respectively. The subgroups showed significant differences in DNA methylation levels, immune microenvironment (immune cell infiltration, immune checkpoint PD1/PD-L1 expression, immune cell cracking activity (CYT)) and pathology features (texture, eccentricity, intensity and tumor-infiltrating lymphocytes (TILs)). The results also showed that there is a subgroup in both luminal A and B that has the benefit from immunotherapy. This study proposed a classification of luminal BC from the perspective of epigenetics and immune characteristics, which provided individualized treatment decisions.

Prognostic Value of Molecular Intratumor Heterogeneity in Primary Oral Cancer and Its Lymph Node Metastases Assessed by Mass Spectrometry Imaging

Different aspects of intra-tumor heterogeneity (ITH), which are associated with the development of cancer and its response to treatment, have postulated prognostic value. Here we searched for potential association between phenotypic ITH analyzed by mass spectrometry imaging (MSI) and prognosis of head and neck cancer. The study involved tissue specimens resected from 77 patients with locally advanced oral squamous cell carcinoma, including 37 patients where matched samples of primary tumor and synchronous lymph node metastases were analyzed. A 3-year follow-up was available for all patients which enabled their separation into two groups: with no evidence of disease (NED, n = 41) and with progressive disease (PD, n = 36). After on-tissue trypsin digestion, peptide maps of all cancer regions were segmented using an unsupervised approach to reveal their intrinsic heterogeneity. We found that intra-tumor similarity of spectra was higher in the PD group and diversity of clusters identified during image segmentation was higher in the NED group, which indicated a higher level of ITH in patients with more favorable outcomes. Signature of molecular components that correlated with long-term outcomes could be associated with proteins involved in the immune functions. Furthermore, a positive correlation between ITH and histopathological lymphocytic host response was observed. Hence, we proposed that a higher level of ITH revealed by MSI in cancers with a better prognosis could reflect the presence of heterotypic components of tumor microenvironment such as infiltrating immune cells enhancing the response to the treatment.

Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates

Hepatocellular carcinoma (HCC), accounting for ~90% of all primary liver cancer, is a prevalent malignancy worldwide. The intratumor heterogeneity of its causative etiology, histology, molecular landscape, and immune phenotype makes it difficult to precisely recognize individuals with high mortality risk or tumor-intrinsic treatment resistance, especially immunotherapy. Herein, we comprehensively evaluated the activities of cancer hallmark gene sets and their correlations with the prognosis of HCC patients using gene set variation analysis (GSVA) and identified two HCC subtypes with distinct prognostic outcomes. Based on these subtypes, seven immune-related genes (TMPRSS6, SPP1, S100A9, EPO, BIRC5, PLXNA1, and CDK4) were used to construct a novel prognostic gene signature [hallmark-guided subtypes-based immunologic signature (HGSIS)] via multiple statistical approaches. The HGSIS-integrated nomogram suggested an enhanced predictive performance. Interestingly, oncogenic hallmark pathways were significantly enriched in the high-risk group and positively associated with the risk score. Distinct mutational landscapes and immune profiles were observed between different risk groups. Moreover, immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analysis showed different sensitivities of HGSIS risk groups for immune therapy efficacy, and the pRRophetic algorithm indicated distinguishable responses for targeted/chemotherapies in different groups. KIF2C was picked out as the key target concerning HGSIS, and the top 10 small molecules were predicted to bind to the active site of KIF2C via molecular docking, which might be further used for candidate drug discovery of HCC. Taken together, our study offers novel insights for clinically significant subtype recognition, and the proposed signature may be a helpful guide for clinicians to improve the treatment regimens.

Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in ER (+) and/or PR (+) and HER2 (-) Breast Cancer

Background: Although intrinsic molecular subtype has been widely used, there remains great clinical heterogeneity of prognosis in the estrogen receptor (ER)- and/or progesterone receptor (PR)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC).

Methods: The transcriptome expression data of messenger RNA (mRNA) were downloaded from The Cancer Genome Atlas (TCGA), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and the Gene Expression Omnibus (GEO) databases. Immune-related genes were acquired from the ImmPort database and additional literature search. Univariate Cox, LASSO regression, and multivariate Cox regression were used to screen prognostic immune-related genes and establish the risk signature. The correlation between the risk signature and clinical characteristics, the abundances of immune cells within the tumor microenvironment, and cancer phenotypes were further assessed.

Results: Of note, 102 immune-related prognostic genes were identified in the METABRIC dataset by univariate Cox analysis. Consecutively, 7 immune-related genes (SHMT2, AGA, COL17A1, FLT3, SLC7A2, ATP6AP1, and CCL19) were selected to establish the risk signature by LASSO regression and multivariate Cox analysis. Its performance was further verified in TCGA and GSE21653 datasets. Multivariate Cox analysis showed that the risk signature was an independent prognostic factor. The 7-gene signature showed a significant correlation with intrinsic molecular subtypes and 70-gene signature. Furthermore, the CD4⁺ memory T cells were significantly higher in the low-risk group while a significantly higher proportion of M0-type macrophages was found in the high-risk group in both METABRIC and TCGA cohorts, which may have an influence on the prognosis. Furthermore, we found that the low-risk group may be associated with the immune-related pathway and the high-risk group was with the cell cycle-related pathway, which also showed an impact on the prognosis.

Conclusion: These seven immune-related gene risk signatures provided an effective method for prognostic stratification in ER (+) and/or PR (+) and HER2 (−) BC.

Prognostic significance of different molecular typing methods and immune status based on RNA sequencing in HR-positive and HER2-negative early-stage breast cancer

BACKGROUND

This study was conducted to evaluate the prognostic significance of different molecular typing methods and immune status based on RNA sequencing (RNA-seq) in hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative (HR + /HER2-) early-stage breast cancer and develop a modified immunohistochemistry (IHC)-based surrogate for intrinsic subtype analysis.

METHODS

The gene expression profiles of samples from 87 HR + /HER2- early-stage breast cancer patients were evaluated using the RNA-seq of Oncotype Dx recurrence score (RS), PAM50 risk of recurrence (ROR), and immune score. Intrinsic tumor subtypes were determined using both PAM50- and IHC-based detection of estrogen receptor, progesterone receptor, Ki-67, epidermal growth factor receptor, and cytokeratins 14 and 5/6. Prognostic variables were analyzed through Cox regression analysis of disease-free survival (DFS) and distant metastasis-free survival (DMFS).

RESULTS

Survival analysis showed that ROR better predicted recurrence and distant metastasis compared to RS (for DFS: ROR, P = 0.000; RS, P = 0.027; for DMFS, ROR, P = 0.047; RS, P = 0.621). Patients with HR + /HER2- early-stage breast cancer was classified into the luminal A, luminal B, HER2-enriched, and basal-like subtypes by PAM50. Basal-like subgroups showed the shortest DFS and DMFS. A modified IHC-based surrogate for intrinsic subtype analysis improved the concordance with PAM50 from 66.7% to 73.6%, particularly for basal-like subtype identification. High level of TILs and high expression of immune genes predicted poor prognosis. Multi-factor Cox analysis showed that IHC-based basal-like markers were the only independent factors affecting DMFS.

CONCLUSIONS

Prognosis is better evaluated by PAM50 ROR in early-stage HR + /HER2- breast cancer and significantly differs among intrinsic subtypes. The modified IHC-based subtype can improve the basal-like subtype identification of PAM50. High immunity status and IHC-based basal-like markers are negative prognostic factors.

Prognosis of Tumor Microenvironment in Luminal B-Type Breast Cancer

Objective

Tumor microenvironment as an important element of malignancy could help predict cancer prognosis and therapeutic response; thus, a prognostic landscape map of the tumor microenvironment in luminal B breast cancers should be developed.

Methods

The GEO and TCGA databases were employed to retrieve clinical follow-up data and expression profiles of luminal B breast cancer. CIBERSORT was applied to assess the infiltration of the tumor microenvironment of 209 patients and to construct tumor microenvironment-based subtypes of luminal B breast cancer. We also conducted Cox multivariate regression analysis to select features that could be used to develop a microenvironment signature for cancer. Samples were categorized as having low and high TME scores according to the median TME score. The correlations of prognosis and TME score, expression levels of immune factors and genomic variation, and clinical features were further investigated.

Results

We found that high TME scores were correlated with poor prognosis. The current findings showed that the expressions of multiple immune-related genes, including CXCL9, CXCL10, GZMB, and PDCD1LG2, were upregulated in cancer with high TME scores. The high-risk group showed lower TP53 gene mutation frequency as opposed to that of the low-risk group. For the purpose of developing a TME scoring system, the TME infiltration levels of 209 patients with luminal B breast cancer from TCGA were comprehensively analyzed.

Conclusions

Our analysis revealed that the TME score was an indicator of patients' response to immune checkpoint modulators and an effective prognostic biomarker. TME scoring improves current immunotherapy on luminal B breast cancer.

Comparison of somatic mutation landscapes in Chinese versus European breast cancer patients

Recent genomic studies suggest that Asian breast cancer (BC) may have distinct somatic features; however, most comparisons of BC genomic features across populations did not account for differences in age, subtype, and sequencing methods. In this study, we analyzed whole-exome sequencing (WES) data to characterize somatic copy number alterations (SCNAs) and mutation profiles in 98 Hong Kong BC (HKBC) patients and compared with those from The Cancer Genome Atlas of European ancestry (TCGA-EA, N = 686), which had similar distributions of age at diagnosis and PAM50 subtypes as in HKBC. We developed a two-sample Poisson model to compare driver gene selection pressure, which reflects the effect sizes of cancer driver genes, while accounting for differences in sample size, sequencing platforms, depths, and mutation calling methods. We found that somatic mutation and SCNA profiles were overall very similar between HKBC and TCGA-EA. The selection pressure for small insertions and deletions (indels) in GATA3 (false discovery rate (FDR) corrected p < 0.01) and single-nucleotide variants (SNVs) in TP53 (nominal p = 0.02, FDR corrected p = 0.28) was lower in HKBC than in TCGA-EA. Among the 13 signatures of single-base substitutions (SBS) that are common in BC, we found a suggestively higher contribution of SBS18 and a lower contribution of SBS1 in HKBC than in TCGA-EA, while the two APOBEC-induced signatures showed similar prevalence. Our results suggest that the genomic landscape of BC was largely very similar between HKBC and TCGA-EA, despite suggestive differences in some driver genes and mutational signatures that warrant future investigations in large and diverse Asian populations.

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires

Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.

Natural and Synthetic Estrogens in Chronic Inflammation and Breast Cancer

The oncogenic role of estrogen receptor (ER) signaling in breast cancer has long been established. Interaction of estrogen with estrogen receptor (ER) in the nucleus activates genomic pathways of estrogen signaling. In contrast, estrogen interaction with the cell membrane-bound G-protein-coupled estrogen receptor (GPER) activates the rapid receptor-mediated signaling transduction cascades. Aberrant estrogen signaling enhances mammary epithelial cell proliferation, survival, and angiogenesis, hence is an important step towards breast cancer initiation and progression. Meanwhile, a growing number of studies also provide evidence for estrogen's pro- or anti-inflammatory roles. As other articles in this issue cover classic ER and GPER signaling mediated by estrogen, this review will discuss the crucial mechanisms by which estrogen signaling influences chronic inflammation and how that is involved in breast cancer. Xenoestrogens acquired from plant diet or exposure to industrial products constantly interact with and alter innate estrogen signaling at various levels. As such, they can modulate chronic inflammation and breast cancer development. Natural xenoestrogens generally have anti-inflammatory properties, which is consistent with their chemoprotective role in breast cancer. In contrast, synthetic xenoestrogens are proinflammatory and carcinogenic compounds that can increase the risk of breast cancer. This article also highlights important xenoestrogens with a particular focus on their role in inflammation and breast cancer. Improved understanding of the complex relationship between estrogens, inflammation, and breast cancer will guide clinical research on agents that could advance breast cancer prevention and therapy.

Prognostic significance of tumor-infiltrating lymphocytes in premenopausal, luminal breast cancer treated with adjuvant endocrine therapy

PURPOSE

Tumor-infiltrating lymphocytes (TILs) have strong prognostic value in triple-negative and HER2-enriched breast cancer, but their prognostic role in luminal breast cancer (LBC) is less clear. Here, we assessed the overall TIL levels and CD8+ T-cells in relation to the prognosis of LBC patients from China.

METHODS AND RESULTS

A total of 596 patients with LBC who were premenopausal and treated with adjuvant endocrine therapy were included. Among them, 160 cases were evaluated for CD8 by immunohistochemical (IHC) staining. Whole-section hematoxylin and eosin and IHC staining were visually assessed for stromal TILs (sTILs), stromal CD8+ T-cells (sCD8), and intratumoral CD8+ T-cells (iCD8). Multivariable analyses were used to test the associations between TILs and disease-free survival (DFS) and overall survival (OS) with the adjustment for clinicopathologic characteristics and treatment. High sTILs (≥10%) were associated with high histologic grade (P<0.001), luminal B/HER2- (P<0.001), luminal B/HER2+ subtype (P=0.002), and high Ki67 expression (≥25%; P=0.014). Similar associations were observed for sCD8 but not for iCD8. While sTILs and sCD8 were not associated with either DFS or OS, the presence of iCD8 (≥1%) was associated with better DFS in both univariate (HR=0.51, 95% CI 0.26-0.96, P=0.042) and multivariate (HR=0.48, 95% CI 0.25-0.92, P=0.027) analyses. Similar but less significant associations were found for iCD8 and OS (adjusted HR=0.35, 95% CI 0.11-1.10, P=0.073).

CONCLUSIONS

Among Chinese premenopausal patients with LBC, iCD8 demonstrated suggestive associations with favorable outcome. In contrast, although sTILs and sCD8 were associated with more aggressive tumor features, they did not appear to be associated with clinical outcome.

Key immune-related gene ITGB2 as a prognostic signature for acute myeloid leukemia

Background

The tumor microenvironment (TME) has an essential role in tumorigenesis, progression, and therapeutic response in many cancers. Currently, the role of TME in acute myeloid leukemia (AML) is unclear. This study investigated the correlation between immune-related genes and prognosis in AML patients.

Methods

Transcriptome RNA-Seq data for 151 AML samples were downloaded from TCGA database (https://portal.gdc.cancer.gov/), and the immune related genes (irgs) were selected from Immport database. Bioinformatics screening was used to identify irgs for AML, and genes with a critical role in the prognosis of AML were selected for further analysis. To confirm the prognostic role of irgs in AML, we undertook protein-protein interaction (PPI) network analysis of the top 30 interacting genes. We then investigated associations between immune cell infiltration and prognosis in AML patients. Immunohistochemistry was used to validate protein expression levels between AML and normal bone marrow samples. Analysis of the drug sensitivity of the selected gene was then performed.

Results

The integrin lymphocyte function-associated antigen 1 (CD11A/CD18; ITGAL/ITGB2) was identified as the key immune-related gene that significantly influenced prognosis in AML patients. Overexpression of ITGB2 indicated poor prognosis in AML patients (P=0.007). Risk modeling indicated that a high-risk score led to poor outcomes (P=3.076e−08) in AML patients. The risk model showed accuracy for predicting prognosis in AML patients, with area under curve (AUC) at 1 year, 0.816; AUC at 3 years, 0.82; and AUC at 5 years, 0.875. In addition, we found that ITGB2 had a powerful influence on immune cell infiltration into AML TME. The results of immunohistochemistry showed that AML patients had significantly higher ITGB2 protein expression than normal samples. The AML patients were divided into 2 groups based on ITGB2 risk scores. Drug sensitivity test results indicated that the high-risk group was sensitive to cytarabine, axitinib, bosutinib, and docetaxel, but resistant to cisplatin and bortezomib.

Conclusions

In the present study, we found that ITGB2 may be able to serve as a biomarker for assessing prognosis and drug sensitivity in AML patients.

Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler

Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.

Intra-Tumor Heterogeneity Revealed by Mass Spectrometry Imaging Is Associated with the Prognosis of Breast Cancer

Intra-tumor heterogeneity (ITH) results from the coexistence of genetically distinct cancer cell (sub)populations, their phenotypic plasticity, and the presence of heterotypic components of the tumor microenvironment (TME). Here we addressed the potential association between phenotypic ITH revealed by mass spectrometry imaging (MSI) and the prognosis of breast cancer. Tissue specimens resected from 59 patients treated radically due to the locally advanced HER2-positive invasive ductal carcinoma were included in the study. After the on-tissue trypsin digestion of cellular proteins, peptide maps of all cancer regions (about 380,000 spectra in total) were segmented by an unsupervised approach to reveal their intrinsic heterogeneity. A high degree of similarity between spectra was observed, which indicated the relative homogeneity of cancer regions. However, when the number and diversity of the detected clusters of spectra were analyzed, differences between patient groups were observed. It is noteworthy that a higher degree of heterogeneity was found in tumors from patients who remained disease-free during a 5-year follow-up (n = 38) compared to tumors from patients with progressive disease (distant metastases detected during the follow-up, n = 21). Interestingly, such differences were not observed between patients with a different status of regional lymph nodes, cancer grade, or expression of estrogen receptor at the time of the primary treatment. Subsequently, spectral components with different abundance in cancer regions were detected in patients with different outcomes, and their hypothetical identity was established by assignment to measured masses of tryptic peptides identified in corresponding tissue lysates. Such differentiating components were associated with proteins involved in immune regulation and hemostasis. Further, a positive correlation between the level of tumor-infiltrating lymphocytes and heterogeneity revealed by MSI was observed. We postulate that a higher heterogeneity of tumors with a better prognosis could reflect the presence of heterotypic components including infiltrating immune cells, that facilitated the response to treatment.

Crosstalk between Tumor-Infiltrating Immune Cells and Cancer-Associated Fibroblasts in Tumor Growth and Immunosuppression of Breast Cancer

Signals from the tumor microenvironment (TME) have a profound influence on the maintenance and progression of cancers. Chronic inflammation and the infiltration of immune cells in breast cancer (BC) have been strongly associated with early carcinogenic events and a switch to a more immunosuppressive response. Cancer-associated fibroblasts (CAFs) are the most abundant stromal component and can modulate tumor progression according to their secretomes. The immune cells including tumor-infiltrating lymphocytes (TILs) (cytotoxic T cells (CTLs), regulatory T cells (Tregs), and helper T cell (Th)), monocyte-infiltrating cells (MICs), myeloid-derived suppressor cells (MDSCs), mast cells (MCs), and natural killer cells (NKs) play an important part in the immunological balance, fluctuating TME between protumoral and antitumoral responses. In this review article, we have summarized the impact of these immunological players together with CAF secreted substances in driving BC progression. We explain the crosstalk of CAFs and tumor-infiltrating immune cells suppressing antitumor response in BC, proposing these cellular entities as predictive markers of poor prognosis. CAF-tumor-infiltrating immune cell interaction is suggested as an alternative therapeutic strategy to regulate the immunosuppressive microenvironment in BC.

Luminal Breast Cancer: Risk of Recurrence and Tumor-Associated Immune Suppression

Hormone-receptor positive (HR+) breast cancer (BC) (including the luminal A and the luminal B subtypes) is the most common type of tumor in women diagnosed with early-stage BC (EBC). It represents a highly heterogeneous subgroup that is characterized by different risks of relapse. The aim of this review is to discuss the possible role played by the immune response in predicting this risk, along with the most common clinical and pathological factors and molecular tools that have been developed and are already in use. As opposed to what has previously been observed in the most aggressive human epidermal growth factor receptor 2 (HER2)-positive and triple-negative breast cancer (TNBC) subtypes, a high proportion of tumor-infiltrating lymphocytes (TILs)-reflecting a spontaneous and pre-existing immune response to the tumor-has been linked to a worse prognosis in HR+ EBC. This work provides some immune biological rationale explaining these findings and provides the basics to understand the principal clinical trials that are testing immunotherapy in HR+ (luminal) BC.

Radiosensitivity index emerges as a potential biomarker for combined radiotherapy and immunotherapy

In the era of immunotherapy, there lacks of a reliable genomic predictor to identify optimal patient populations in combined radiotherapy and immunotherapy (CRI). The purpose of this study is to investigate whether genomic scores defining radiosensitivity are associated with immune response. Genomic data from Merged Microarray-Acquired dataset (MMD) were established and the Cancer Genome Atlas (TCGA) were obtained. Based on rank-based regression model including 10 genes, radiosensitivity index (RSI) was calculated. A total of 12832 primary tumours across 11 major cancer types were analysed for the association with DNA repair, cellular stemness, macrophage polarisation, and immune subtypes. Additional 585 metastatic tissues were extracted from MET500. RSI was stratified into RSI-Low and RSI-High by a cutpoint of 0.46. Proteomic differential analysis was used to identify significant proteins according to RSI categories. Gene Set Variance Analysis (GSVA) was applied to measure the genomic pathway activity (18 genes for T-cell inflamed activity). Kaplan-Meier analysis was performed for survival analysis. RSI was significantly associated with homologous DNA repair, cancer stemness and immune-related molecular features. Lower RSI was associated with higher fraction of M1 macrophage. Differential proteomic analysis identified significantly higher TAP2 expression in RSI-Low colorectal tumours. In the TCGA cohort, dominant interferon-γ (IFN-γ) response was characterised by low RSI and predicted better response to programmed cell death 1 (PD-1) blockade. In conclusion, in addition to radiation response, our study identified RSI to be associated with various immune-related features and predicted response to PD-1 blockade, thus, highlighting its potential as a candidate biomarker for CRI.

Protein-based immune profiles of basal-like vs. luminal breast cancers

Tumor-infiltrating lymphocytes play an important, but incompletely understood role in chemotherapy response and prognosis. In breast cancer, there appear to be distinct immune responses by subtype, but most studies have used limited numbers of protein markers or bulk sequencing of RNA to characterize immune response, in which spatial organization cannot be assessed. To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx® (NanoString) platform to perform digital spatial profiling of immune-related proteins in tumor whole sections and tissue microarrays (TMA). Visualization of CD45, CD68, or pan-Cytokeratin by immunofluorescence was used to select regions of interest in formalin-fixed paraffin embedded tissue sections. Forty-four antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. In whole tumor slides, immune hot spots (CD45+) had increased expression of many immune markers, suggesting a diverse and robust immune response. In epithelium-enriched areas, immune signals were also detectable and varied by subtype, with regulatory T-cell (Treg) markers (CD4, CD25, and FOXP3) being higher in Basal-like vs. Luminal breast cancer. Extending these findings to TMAs with more patients (n = 75), we confirmed subtype-specific immune profiles, including enrichment of Treg markers in Basal-likes. This work demonstrated that immune responses can be detected in epithelium-rich tissue, and that TMAs are a viable approach for obtaining important immunoprofiling data. In addition, we found that immune marker expression is associated with breast cancer subtype, suggesting possible prognostic, or targetable differences.

Prognostic Significance of BIRC5/Survivin in Breast Cancer: Results from Three Independent Cohorts

Simple Summary

Survivin, coded by the BIRC5 gene, is the cell death preventing protein, which is important for cell division in normal and cancer cells. It is intensively studied as a cancer biomarker and target for antitumor therapy. In this study we asked if we could get clinically helpful information on how active BIRC5 is in breast cancer patients? We studied the BIRC5 protein level in tumor samples for breast cancer patients from a West Swedish cohort and its mRNA level in two different public gene expression databases. Survival analysis demonstrated that a higher BIRC5 protein or mRNA level was associated with poor survival in all cohorts and for different cancer subtypes. We show that BIRC5 is a promising independent cancer survival marker.

Abstract

Breast cancer (BC) histological and molecular classifications significantly improved the treatment strategy and prognosis. Inhibitor of apoptosis BIRC5/survivin is often overexpressed in cancers, however, indications of its importance in BC are inconsistent. We integrate BIRC5 protein and mRNA measures with clinical associates and long-term outcome in three independent cohorts Protein levels of BIRC5 were measured in primary lysates of 845 patients of the West Swedish BC cohort (VGR-BC) and linked to 5- and 27-years survival. The results were externally validated in transcriptomic data from METABRIC and SCAN-B cohorts. Survival analysis showed that high levels of BIRC5 were consistently associated with a poor probability of 5-year overall survival. High BIRC5 in VGR-BC contributed negatively to the disease-specific survival at 5 and 27 years. Subsets with different status by ER (estrogen receptor) expression and presence of nodal metastasis supported independent association of high BIRC5 with poor prognosis in all cohorts. In METABRIC and SCAN-B cohorts, high levels of BIRC5 mRNA were associated with the basal-like and luminal B molecular BC subtypes and with increasing histologic grade. BIRC5 is a sensitive survival marker that acts independent of ER and nodal status, and its levels need to be considered when making treatment decisions.

Immune response drives outcomes in prostate cancer: implications for immunotherapy

The heterogeneity of the immune microenvironment leads to different responses in immune checkpoint blockade therapy. We aimed to propose a robust molecular classification system to investigate the relevance of the immune microenvironment subtype and prognosis of prostate cancer patients, as well as the therapeutic response to immune checkpoint blockade therapy. A total of 1,557 prostate cancer patients were enrolled, including 69 real-world samples from our institute (titled the AHMU-PC cohort). The non-negative matrix factorization algorithm was employed to virtually microdissect patients. The immune enrichment was characterized by a high enrichment of T cell-, B cell-, NK cell-, and macrophage-associated signatures, by which patients were subclassified into nonimmune and immune classes. Subsequently, the immune class was dichotomized into immune-activated and immune-suppressed subtypes based on the stromal signature, represented by the activation of WNT/TGF-β, TGF-β1, and C-ECM signatures. Approximately 14.9% to 24.3% of patients belonged to the immune-activated subtype, which was associated with favorable recurrence-free survival outcomes. In addition, patients in the immune-activated subtype were predicted to benefit more from anti-PD-1/PD-L1 therapy. In conclusion, our study identifies a novel immune molecular classifier that is closely related to clinical prognosis and provides novel insights into immunotherapeutic strategies for prostate cancer patients.

Identification of molecular heterogeneity of hepatocellular carcinoma based on immune gene expression signatures

Although various molecular subtypes of hepatocellular carcinoma (HCC) have been investigated, most of these studies identify HCC subtype based on genomic profiling. Few studies have investigated the classification based on immune signatures, and none have classified HCC based on Immune activation and immunosuppressive. We performed immune gene expression of tumor tissue in 374 HCC patients from The Cancer Genome Atlas (TCGA) database and used unsupervised consensus clustering to stratify tumors. We then used HCC patients from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) as replication datasets. Based on the expression of 782 immune-related genes, HCC was stratified into four distinct immune subtypes. Tumors in one cluster (high immune activation; high-IA) indicate a higher level of Immune activation, which was characterized by higher anti-tumor immunity, higher pro-tumor immune-suppressive cell types, higher fractions of CD8+ T cells and M0 Macrophages compared with other subtypes. The high-IA also presents higher cancer-related hallmark signatures, such as epithelial-mesenchymal transition (EMT), angiogenesis, and apoptosis. We also found subpopulations of regulatory and exhaustion T lymphocyte were characterized by an opposite trend in high-IA, though samples in high-IA response to immunotherapy with better survival. The comparison of the immune profile in tumor and normal tissue indicates the activation of immune responses which only occurred in high-IA patients, while we conducted comparison of cirrhosis and non-cirrhosis tumor immune signatures, immune response activation was almost occurred in high-IA, but some of immune responses occurred in low-IA (low immune activation).

Reduced expression of innate immunity-related genes in lymph node metastases of luminal breast cancer patients

Immune system plays a dual role in cancer by either targeting or supporting neoplastic cells at various stages of disease, including metastasis. Yet, the exact immune-related transcriptome profiles of primary tumours (PT) and lymph node metastases (LNM) and their evolution during luminal breast cancer (BCa) dissemination remain undiscovered. In order to identify the immune-related transcriptome changes that accompany lymphatic spread, we analysed PT-LNM pairs of luminal BCa using NanoString technology. Decrease in complement C3-one of the top-downregulated genes, in LNM was validated at the protein level using immunohistochemistry. Thirty-three of 360 analysed genes were downregulated (9%), whereas only 3 (0.8%) upregulated in LNM when compared to the corresponding PT. In LNM, reduced expression was observed in genes related to innate immunity, particularly to the complement system (C1QB, C1S, C1R, C4B, CFB, C3, SERPING1 and C3AR1). In validation cohort, complement C3 protein was less frequently expressed in LNM than in PT and it was associated with worse prognosis. To conclude, local expression of the complement system components declines during lymphatic spread of non-metastatic luminal BCa, whilst further reduction of tumoral complement C3 in LNM is indicative for poor survival. This points to context-dependent role of complement C3 in BCa dissemination.

A novel immune-related prognostic index for predicting breast cancer overall survival

PURPOSE

To find immune-related genes with prognostic value in breast cancer, and construct a prognostic risk assessment model to make a more accurate assessment. Moreover, looking for potential immune markers for breast cancer immunotherapy.

METHODS

The breast cancer (BC) data were retrieved from The Cancer Genome Atlas (TCGA) database as a training set. Through the Weighted gene co-expression network analysis (WGCNA), Kaplan-Meier (KM) analysis, lasso regression analysis and stepwise backward Cox regression analysis, screening for prognosis-related immune genes, a prognostic index was built, and external validation with two data sets of Gene Expression Omnibus (GEO) database was performed. Transcription factor (TF) regulatory network was constructed to identify key transcription factors that regulate prognostic immune genes. Gene set enrichment analysis (GSEA) was used to explore the signal pathways differences between high and low-risk groups, estimate package and TIMER database were used to evaluate the relationship between risk score and tumor immune microenvironment.

RESULTS

We obtained 10 prognosis-related immune genes, and the index showed accurate prognostic value. We also identified 7 prognostic transcription factors. Multiple signaling pathways that inhibit tumor progression were enriched in the low-risk group, and risk score was significantly negatively related to the degree of immune infiltration and the expression level of immune checkpoint genes.

CONCLUSION

We successfully constructed an independent prognostic index, which not only has a stronger predictive ability than the tumor pathological stage, but also can reflect the immune infiltration of breast cancer patients.

Identification of unanimous immune subtypes for different hormone receptor phenotypes of human breast cancer with potential prognostic significance

The immunogenicity of the breast tumor microenvironment is clinically heterogeneous. The insight into the role of tumor-infiltrating lymphocytes (TILs) might serve as a biomarker to predict a survival benefit and enable optimal patient selection for immunotherapy. In this study, we aimed at characterizing the breast cancer immune subtypes linked to CD8 T cells and associating with the patient characteristics and clinical outcomes. We analyzed the immune gene signatures of human breast cancer using The Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) database profiling of 1092 breast tumor patients. We performed hierarchical clustering to the immune gene expression by applying hormone receptor status including triple negative breast cancer to categorize 66 immune-related genes in breast tumors. The separation was characterized by dividing the breast tumors into two major immune subtypes: predominant immune (PI) subtype and low immune subtype (LI). Our results showed that both PI and LI subtypes can be observed in the different hormone receptor phenotypes of breast tumors, and PI subtype accounted for 16% and LI subtype 20% in the breast tumor patients. The estimated odds for LI subtype breast tumors were significantly higher than PI subtype breast tumors in primary tumor stages. Our data demonstrated that the PI subtype breast tumors have significantly improved survival compared with LI subtype. Our findings provide a novel perspective of breast cancer immune subtypes linked to CD8 T cells. The immune subtypes will be a valuable resource for future research to identify clinically relevant biomarkers for precision immunotherapy.

The immune-related gene CD52 is a favorable biomarker for breast cancer prognosis

Background

An increasing number of studies have demonstrated a role for the tumor microenvironment in tumorigenesis, disease progression, and therapeutic response. This present study aimed to screen the significant immune-related genes and their possible role in the prognosis of breast cancer (BRCA).

Methods

The transcriptome data and clinical data of breast cancer were collected from The Cancer Genome Atlas (TCGA), and the immune scores and stromal scores were calculated by ESTIMATE algorithm. The differentially expressed genes were screened base on immune and stromal scores (high score vs. low score), than the intersected genes were used for subsequent functional enrichment analysis and protein-protein interaction (PPI) analysis. Furthermore, the key gene was identified by the intersection of the hub genes of PPI network and the prognostic genes of breast cancer. Finally, we explored the infiltration of immune cells of BRCA base on the CIBERSORT algorithm, and analysis the relationship between key gene and immune cells.

Results

High levels of CD52 expression were detected in the early stages of breast cancer and were associated with favorable prognosis. Overexpression of CD52 led to higher infiltrations of M1 macrophages, monocytes, T follicular helper cells, and resting memory CD4 T cells. Downregulation of CD52 resulted in high infiltrations of M2 macrophages. Therefore, high expression of CD52 may negatively regulate the infiltration of M2 macrophages but accelerate the infiltration of anti-cancer immune cells, and thus, high expression of CD52 may have a protective effect in breast cancer patients.

Conclusions

CD52 can increase the infiltration of anti-cancer immune cells but inhibit the infiltration of M2 macrophages, thereby improving the prognosis of breast cancer patients.

L-Selectin expression is associated with inflammatory microenvironment and favourable prognosis in breast cancer

L-selectin is a cell adhesion molecule that plays an important role in modulating immune cell trafficking. The expression of L-selectin has been found to be upregulated in several human cancers. However, the association of L-selectin expression with the immune profile and its prognostic value in breast cancer has not been explored in detail. We utilized TCGA and Oncomine datasets to compare SELL (L-selectin gene) expression between tumor and normal breast tissues. The association of SELL expression with its promoter DNA methylation and infiltrating immune cells was evaluated by using Wanderer, TIMER, and CIBERSORT tools. Single cell RNA sequencing data was utilised to determine the cell specific expression of L-selectin in breast cancer. Furthermore, the relationship between SELL expression and patient survival was evaluated using the Kaplan-Meier plotter. Gene set enrichment analysis was performed to determine functional associations of SELL expression. We found that SELL expression was significantly higher in breast tumors and regulated by DNA methylation. L-selectin exhibited a strong positive correlation with markers of the inflammatory microenvironment, including M1 macrophages. Interestingly, single cell sequencing data analysis revealed that B-cells and T-cells exhibited comparable expression levels of SELL, suggesting both B-cells and T cells contribute to SELL expression in breast cancer. Higher expression of SELL was associated with better survival outcome in basal, Her2 + and luminal B subtypes of breast cancer. GSEA revealed association of SELL expression with several immunological features in breast cancer. SELL expression increases in breast tumor tissues with reduced DNA methylation and associated inflammatory microenvironment. Also, high SELL expression is associated with favorable survival outcomes in breast cancer.

RNA m6A Methylation Regulators Subclassify Luminal Subtype in Breast Cancer

RNA N⁶-methyladenosine (m⁶A) methylation is the most prevalent epitranscriptomic modification in mammals, with a complex and fine-tuning regulatory system. Recent studies have illuminated the potential of m⁶A regulators in clinical applications including diagnosis, therapeutics, and prognosis. Based on six datasets of breast cancer in The Cancer Genome Atlas (TCGA) database and two additional proteomic datasets, we provide a comprehensive view of all the known m⁶A regulators in their gene expression, copy number variations (CNVs), DNA methylation status, and protein levels in breast tumors and their association with prognosis. Among four breast cancer subtypes, basal-like subtype exhibits distinct expression and genomic alteration in m⁶A regulators from other subtypes. Accordingly, four representative regulators (IGF2BP2, IGF2BP3, YTHDC2, and RBM15) are identified as basal-like subtype-featured genes. Notably, luminal A/B samples are subclassified into two clusters based on the methylation status of those four genes. In line with its similarity to basal-like subtype, cluster1 shows upregulation in immune-related genes and cell adhesion molecules, as well as an increased number of tumor-infiltrating lymphocytes. Besides, cluster1 has worse disease-free and progression-free survival, especially among patients diagnosed with stage II and luminal B subtype. Together, this study highlights the potential functions of m⁶A regulators in the occurrence and malignancy progression of breast cancer. Given the heterogeneity within luminal subtype and high risk of recurrence and metastasis in a portion of patients, the prognostic stratification of luminal A/B subtypes utilizing basal-featured m⁶A regulators may help to improve the accuracy of diagnosis and therapeutics of breast cancer.

Quantification of Immune Variables from Liquid Biopsy in Breast Cancer Patients Links Vδ2+ γδ T Cell Alterations with Lymph Node Invasion

The rationale for therapeutic targeting of Vδ2+ γδ T cells in breast cancer is strongly supported by in vitro and murine preclinical investigations, characterizing them as potent breast tumor cell killers and source of Th1-related cytokines, backing cytotoxic αβ T cells. Nonetheless, insights regarding Vδ2+ γδ T cell phenotypic alterations in human breast cancers are still lacking. This paucity of information is partly due to the challenging scarcity of these cells in surgical specimens. αβ T cell phenotypic alterations occurring in the tumor bed are detectable in the periphery and correlate with adverse clinical outcomes. Thus, we sought to determine through an exploratory study whether Vδ2+ γδ T cells phenotypic changes can be detected within breast cancer patients' peripheral blood, along with association with tumor progression. By using mass cytometry, we quantified 130 immune variables from untreated breast cancer patients' peripheral blood. Supervised analyses and dimensionality reduction algorithms evidenced circulating Vδ2+ γδ T cell phenotypic alterations already established at diagnosis. Foremost, terminally differentiated Vδ2+ γδ T cells displaying phenotypes of exhausted senescent T cells associated with lymph node involvement. Thereby, our results support Vδ2+ γδ T cells implication in breast cancer pathogenesis and progression, besides shedding light on liquid biopsies to monitor surrogate markers of tumor-infiltrating Vδ2+ γδ T cell antitumor activity.

BiCoN: network-constrained biclustering of patients and omics data

Motivation

Unsupervised learning approaches are frequently used to stratify patients into clinically relevant subgroups and to identify biomarkers such as disease-associated genes. However, clustering and biclustering techniques are oblivious to the functional relationship of genes and are thus not ideally suited to pinpoint molecular mechanisms along with patient subgroups.

Results

We developed the network-constrained biclustering approach Biclustering Constrained by Networks (BiCoN) which (i) restricts biclusters to functionally related genes connected in molecular interaction networks and (ii) maximizes the difference in gene expression between two subgroups of patients. This allows BiCoN to simultaneously pinpoint molecular mechanisms responsible for the patient grouping. Network-constrained clustering of genes makes BiCoN more robust to noise and batch effects than typical clustering and biclustering methods. BiCoN can faithfully reproduce known disease subtypes as well as novel, clinically relevant patient subgroups, as we could demonstrate using breast and lung cancer datasets. In summary, BiCoN is a novel systems medicine tool that combines several heuristic optimization strategies for robust disease mechanism extraction. BiCoN is well-documented and freely available as a python package or a web interface.

Availability and implementation

PyPI package: https://pypi.org/project/bicon.

Web interface

https://exbio.wzw.tum.de/bicon.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genomic Signatures in Luminal Breast Cancer

Background

Breast cancer is a very heterogeneous disease and luminal breast carcinomas represent the hormone receptor-positive tumors among all breast cancer subtypes. In this context, multigene signatures were developed to gain further prognostic and predictive information beyond clinical parameters and traditional immunohistochemical markers.

Summary

For early breast cancer patients these molecular tools can guide clinicians to decide on the extension of endocrine therapy to avoid over- and undertreatment by adjuvant chemotherapy. Beside the predictive and prognostic value, a few genomic tests are also able to provide intrinsic subtype classification. In this review, we compare the most frequently used and commercially available molecular tests (OncotypeDX®, MammaPrint®, Prosigna®, EndoPredict®, and Breast Cancer Index^SM). Moreover, we discuss the clinical utility of molecular profiling for advanced breast cancer of the luminal subtype.

Key Messages

Multigene assays can help to de-escalate systemic therapy in early-stage breast cancer. Only the Oncotype DX® and MammaPrint®test are validated by entirely prospective and randomized phase 3 trials. More clinical evidence is needed to support the use of genomic tests in node-positive disease. Recent developments in high-throughput sequencing technology will provide further insights to understand the heterogeneity of luminal breast cancers in early-stage and metastatic disease.