Intrinsic Subtypes Research Articles

Analysis of Intrinsic Breast Cancer Subtypes: The Clinical Utility of Epigenetic Biomarkers and TP53 Mutation Status in Triple-Negative Cases

This study aimed at analyzing the DNA methylation pattern and TP53 mutation status of intrinsic breast cancer (BC) subtypes for improved characterization and survival prediction. DNA methylation of 17 genes was tested by methylation-specific PCR in 116 non-familial BRCA mutation-negative BC and 29 control noncancerous cases. At least one gene methylation was detected in all BC specimens and a 10-gene panel statistically significantly separated tumors from noncancerous breast tissues. Methylation of FILIP1L and MT1E was predominant in triple-negative (TN) BC, while other BC subtypes were characterized by RASSF1, PRKCB, MT1G, APC, and RUNX3 hypermethylation. TP53 mutation (TP53-mut) was found in 38% of sequenced samples and mainly affected TN BC cases (87%). Cox analysis revealed that TN status, age at diagnosis, and RUNX3 methylation are independent prognostic factors for overall survival (OS) in BC. The combinations of methylated biomarkers, RUNX3 with MT1E or FILIP1L, were also predictive for shorter OS, whereas methylated FILIP1L was predictive of a poor outcome in the TP53-mut subgroup. Therefore, DNA methylation patterns of specific genes significantly separate BC from noncancerous breast tissues and distinguishes TN cases from non-TN BC, whereas the combination of two-to-three epigenetic biomarkers can be an informative tool for BC outcome predictions.

Abstract IA030: Molecular subtypes and spatial heterogeneity in DCIS

Abstract The large heterogeneity of DCIS complicates the identification of markers for risk of progression to invasive breast cancer. Molecular and cellular heterogeneity is observed across DCIS, between multiple foci of DCIS within a lesion and within mixed lesions of invasive tumors with DCIS foci. The intrinsic breast cancer subtypes represent fundamental biological properties of the disease and are also found at the DCIS stage. However, their frequency and relevance as prognostic markers in pre-invasive stage is still not clear. Novel technologies for spatial characterization of tumors allow detailed mapping of DCIS and the microenvironment and may give us clues to which DCIS have the propensity to invade surrounding stroma. In the presentation, we will discuss results from our ongoing genomic characterization of DCIS and invasive breast carcinomas that illustrate the need for stratification when searching for prognostic markers. We have found disproportionate distribution and characteristics of the intrinsic subtypes in DCIS compared with invasive breast cancer and the dominance of Luminal A and HER2 subtypes. Bona-fide basal-like tumors may rarely be found at the DCIS stage and HER2-enriched DCIS are associated with specific immune cell profiles. Citation Format: Therese Sørlie. Molecular subtypes and spatial heterogeneity in DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA030.

Crosstalk of four kinds of cell deaths defines subtypes of cutaneous melanoma for precise immunotherapy and chemotherapy.

Cell death patterns can give therapeutic and biological clues that facilitate the development of individualized treatments for this lethal form of skin cancer. We employed unsupervised clustering to establish robust classifications based on the four kinds of cell death-associated gene expression of 462 melanoma patients in the Cancer Genome Atlas (TCGA) and tested their reproducibility in two independent melanoma cohorts of 558 patients. We then used dimensionality reduction of graph learning to display the different characteristics of cell death patterns and immune microenvironments. We examined 570 cell death-associated gene expression data of melanoma patients for exploration, independent verification, and comprehensive classification of five reproducible melanoma subtypes (CS1 to CS5) with different genomic and clinical features. Patients in death-inactive subtypes (CS1, CS2, and CS5) had the least immune and stromal cell infiltration, and their prognosis was the poorest. A death-active subtype (CS4), on the other hand, had the highest infiltrated immune and stromal cells and elevated immune-checkpoints. As a result, these patients had the highest response to immunotherapy and the best prognosis. An additional subtype (CS3) had more diversified cell death and immune characteristics with moderate prognoses. Based on graph learning, we successfully divided the CS3 subtype into two subgroups (group A and group B) with distinct survival outcomes and immune features. Finally, we identified eight potential chemical drugs that were specifically targeted for the therapy of melanoma subtypes. This research defines the intrinsic subtypes of melanoma based on the crosstalk of four kinds of cell deaths, which affords a blueprint for clinical strategies and guiding precise immunotherapy and chemotherapy for melanoma patients.

Choice of High-Throughput Proteomics Method Affects Data Integration with Transcriptomics and the Potential Use in Biomarker Discovery.

In recent years, several advances have been achieved in breast cancer (BC) classification and treatment. However, overdiagnosis, overtreatment, and recurrent disease are still significant causes of complication and death. Here, we present the development of a protocol aimed at parallel transcriptome and proteome analysis of BC tissue samples using mass spectrometry, via Data Dependent and Independent Acquisitions (DDA and DIA). Protein digestion was semi-automated and performed on flowthroughs after RNA extraction. Data for 116 samples were acquired in DDA and DIA modes and processed using MaxQuant, EncyclopeDIA, or DIA-NN. DIA-NN showed an increased number of identified proteins, reproducibility, and correlation with matching RNA-seq data, therefore representing the best alternative for this setup. Gene Set Enrichment Analysis pointed towards complementary information being found between transcriptomic and proteomic data. A decision tree model, designed to predict the intrinsic subtypes based on differentially abundant proteins across different conditions, selected protein groups that recapitulate important clinical features, such as estrogen receptor status, HER2 status, proliferation, and aggressiveness. Taken together, our results indicate that the proposed protocol performed well for the application. Additionally, the relevance of the selected proteins points to the possibility of using such data as a biomarker discovery tool for personalized medicine.

In Silico Identification of Genes Associated with Breast Cancer Progression and Prognosis and Novel Therapeutic Targets.

Molecular mechanisms underlying breast cancer (BC) progression are complex and remain unclear. In this study, we used bioinformatic tools to identify genes associated with tumor progression mechanisms and novel therapeutic targets in BC. We identified genes with stepwise upregulated expression overlapping between the T and N stages during BC progression using LinkedOmics. We compared the expression level of each gene in BC tissues with that in normal breast tissues and evaluated differences in expression in their intrinsic subtypes and their prognostic value using UALCAN and GEPIA2. We also investigated the dependency of BC cell lines on these genes and whether they are potential therapeutic targets using DepMap. SPDEF, TRIM3, ABCB9, HSPB1, RHBG, SPINT1, EPN3, LRFN2, and PRPH were found to be involved in BC progression. High expression of ABCB9 and SPINT1 was associated with a poor prognosis. SPDEF, TRIM3, ABCB9, RHBG, SPINT1, and PRPH were found to be essential for survival in some BC cell lines (gene effect score < -0.5). PRPH was newly discovered to be involved in the progression of BC and the growth and survival of BC cell lines. Hence, SPDEF, TRIM3, ABCB9, RHBG, SPINT1, and PRPH may serve as novel potential therapeutic targets in BC.

Identification of a claudin-low subtype in clear cell renal cell carcinoma with implications for the evaluation of clinical outcomes and treatment efficacy.

In bladder and breast cancer, the claudin-low subtype is widely identified, revealing a distinct tumor microenvironment (TME) and immunological feature. Although we have previously identified individual claudin members as prognostic biomarkers in clear cell renal cell carcinoma (ccRCC), the existence of an intrinsic claudin-low subtype and its interplay with TME and clinical outcomes remains unclear. Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA)- kidney clear cell carcinoma (KIRC) cohort and E-MTAB-1980 were derived as the training and validation cohorts, respectively. In addition, GSE40435, GSE53757, International Cancer Genome Consortium (ICGC) datasets, and RNA-sequencing data from local ccRCC patients were utilized as validation cohorts for claudin clustering based on silhouette scores. Using weighted correlation network analysis (WGCNA) and multiple machine learning algorithms, including least absolute shrinkage and selection operator (LASSO), CoxBoost, and random forest, we constructed a claudin-TME related (CTR) risk signature. Furthermore, the CTR associated genomic characteristics, immunity, and treatment sensitivity were evaluated. A claudin-low phenotype was identified and associated with an inferior survival and distinct TME and cancer immunity characteristics. Based on its interaction with TME, a risk signature was developed with robust prognostic prediction accuracy. Moreover, we found its association with a claudin-low, stem-like phenotype and advanced clinicopathological features. Intriguingly, it was also effective in kidney chromophobe and renal papillary cell carcinoma. The high CTR group exhibited genomic characteristics similar to those of claudin-low phenotype, including increased chromosomal instability (such as deletions at 9p) and risk genomic alterations (especially BAP1 and SETD2). In addition, a higher abundance of CD8 T cells and overexpression of immune checkpoints, such as LAG3, CTLA4 and PDCD1, were identified in the high CTR group. Notably, ccRCC patients with high CTR were potentially more sensitive to immune checkpoint inhibitors; their counterparts could have more clinical benefits when treated with antiangiogenic drugs, mTOR, or HIF inhibitors. We comprehensively evaluated the expression features of claudin genes and identified a claudin-low phenotype in ccRCC. In addition, its related signature could robustly predict the prognosis and provide guide for personalizing management strategies.

Molecular intrinsic subtypes, genomic, and immune landscapes of BRCA-proficient but HRD-high ER-positive/HER2-negative early breast cancers

PurposeThe vast majority of research studies that have described the links between DNA damage repair or homologous recombination deficiency (HRD) score, and tumor biology, have concerned either triple negative breast cancers or cancers with mutation of BRCA 1/2. We hypothesized that ER + /HER2- early breast tumors without BRCA 1/2 mutation could have high HRD score and aimed to describe their genomic, transcriptomic, and immune landscapes.Patients and methodsIn this study, we reported BRCA 1/2 mutational status, HRD score, and mutational signature 3 (S3) expression, in all early breast cancer (eBC) subtypes from the TCGA database, with a particular focus in ER + /HER2-. In this subtype, bioinformatics analyses of tumor transcriptomic, immune profile, and mutational landscape were performed, according to HRD status. Overall survival (OS), progression free-interval (PFI), and variables associated with outcome were also evaluated.ResultsAmong the 928 tumor samples analyzed, 46 harbored BRCA 1/2 mutations, and 606 were ER + /HER2- (of which 24 were BRCA 1/2 mutated). We found a subset of BRCA-proficient ER + /HER2— eBC, with high HRD score. These tumors displayed significantly different immune, mutational, and tumor molecular signatures landscapes, compared to BRCA-mutated and BRCA-proficient HRD-low tumors. Outcome did not significantly differ between these 3 groups, but biological factors associated with survival are not the same across the 3 entities.ConclusionThis study highlights possible novel biological differences among ER + /HER2- breast cancer related to HRD status. Our results could have important implications for translational research and/or the design of future clinical trials, but require prospective clinical evaluation.

Next Generation Sequencing of Reactive Stroma and Residual Breast Cancer Cells in Tumor Bed after Neoadjuvant Chemotherapy.

Primary systemic or neoadjuvant chemotherapy of breast cancer has become a standard therapy option in locally advanced or predefined intrinsic subtypes such as triple negative or Her2 positive breast cancer. Neoadjuvant chemotherapy can result in complete pathological response without residual tumor cells (tumor bed) or partial response and non-response with different amounts of reactive stroma and residual tumor cells. The interaction between therapy regimens and tumoral driver mutations have been extensively studied, although the reactive stroma of the tumor bed received less attention. In this study, we characterized the mutational status of residual breast cancer cells and reactive tumor stroma devoid of residual tumor cells in partial or non-responders using next generation sequencing. Twenty-one post-therapeutic breast surgical specimens after neoadjuvant chemotherapy underwent pathogenic driver-mutation screening using microdissected residual breast cancer cells and in reactive stroma adjacent to tumor bed areas. In reactive stroma, no mutations could be validated. In residual breast cancer cells, mutations were detected in sixteen of twenty-one cases (76%). In nine of these twenty-one cases (43%), pathogenic driver mutations (PIK3CA, PTEN, TP53, FN1, PLAG1) were identified. Pathogenic driver-mutations are exclusively restricted to residual carcinoma cells and are absent in reactive stroma independently from intrinsic breast cancer subtypes or tumor stage. These data suggest that the absence of pathogenic mutations in a tumor bed without residual tumor cells may have prognostic implications after neoadjuvant chemotherapy.

208 (PB-032) Poster - Intrinsic tumor subtype in hormone receptor (HR) positive, human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancer (ABC) treated with cyclin-dependent kinase 4/6 inhibitors (CDK 4/6i) and endocrine therapy (ET) – a retrospective analysis of real world data

Background: CDK 4/6 inhibitors significantly improve outcomes for patients (pts) with HR positive, HER2-negative ABC. In this group of patients, the HER2-Low (HER2-L) subtype represents 50–60% and is characterized by poor prognosis. In this retrospective analysis we explore the role of intrinsic tumor subtype (luminal A, luminal B and HER2-L) as a predictor of clinical outcomes in patients treated with ET plus CDK 4/6 inhibitors.

235 (PB-059) Poster - PAM50 genomic test in the management of early breast cancer – the importance of clinical-pathological data

Background: The PAM50 test provides important prognostic information for therapeutic decision in hormone-receptor positive (HR+) and HER2-negative (HER2-) early breast cancer. This genomic signature estimates the risk of recurrence (ROR) at 10 years, for patients treated with adjuvant hormone therapy (HT) alone. It also allows the determination of breast cancer intrinsic subtype. However, its validation results only from retrospective studies. We aimed to analyze the correlation between histopathological variables and risk of breast cancer recurrence, as well as the agreement between subtype-like, obtained by immunohistochemistry (IHC) and breast cancer intrinsic subtype, obtained through this molecular analysis.

Intrinsic subtypes in Ethiopian breast cancer patient

PurposeThe recent development of multi-gene assays for gene expression profiling has contributed significantly to the understanding of the clinically and biologically heterogeneous breast cancer (BC) disease. PAM50 is one of these assays used to stratify BC patients and individualize treatment. The present study was conducted to characterize PAM50-based intrinsic subtypes among Ethiopian BC patients.Patients and methodsFormalin-fixed paraffin-embedded tissues were collected from 334 BC patients who attended five different Ethiopian health facilities. All samples were assessed using the PAM50 algorithm for intrinsic subtyping.ResultsThe tumor samples were classified into PAM50 intrinsic subtypes as follows: 104 samples (31.1%) were luminal A, 91 samples (27.2%) were luminal B, 62 samples (18.6%) were HER2-enriched and 77 samples (23.1%) were basal-like. The intrinsic subtypes were found to be associated with clinical and histopathological parameters such as steroid hormone receptor status, HER2 status, Ki-67 proliferation index and tumor differentiation, but not with age, tumor size or histological type. An immunohistochemistry-based classification of tumors (IHC groups) was found to correlate with intrinsic subtypes.ConclusionThe distribution of the intrinsic subtypes confirms previous immunohistochemistry-based studies from Ethiopia showing potentially endocrine-sensitive tumors in more than half of the patients. Health workers in primary or secondary level health care facilities can be trained to offer endocrine therapy to improve breast cancer care. Additionally, the findings indicate that PAM50-based classification offers a robust method for the molecular classification of tumors in the Ethiopian context.

Correlation of Immunological and Histopathological Features with Gene Expression-Based Classifiers in Colon Cancer Patients.

The purpose of this study was to evaluate the association between four distinct histopathological features: (1) tumor infiltrating lymphocytes, (2) mucinous differentiation, (3) tumor-stroma ratio, plus (4) tumor budding and two gene expression-based classifiers—(1) consensus molecular subtypes (CMS) plus (2) colorectal cancer intrinsic subtypes (CRIS). All four histopathological features were retrospectively scored on hematoxylin and eosin sections of the most invasive part of the primary tumor in 218 stage II and III colon cancer patients from two independent cohorts (AMC-AJCC-90 and AC-ICAM). RNA-based CMS and CRIS assignments were independently obtained for all patients. Contingency tables were constructed and a χ2 test was used to test for statistical significance. Odds ratios with 95% confidence intervals were calculated. The presence of tumor infiltrating lymphocytes and a mucinous phenotype (>50% mucinous surface area) were strongly correlated with CMS1 (p < 0.001 and p = 0.008) and CRIS-A (p = 0.006 and p < 0.001). The presence of mucus (≥ 10%) was associated with CMS3: mucus was present in 64.1% of all CMS3 tumors (p < 0.001). Although a clear association between tumor-stroma ratio and CMS4 was established in this study (p = 0.006), still 32 out of 61 (52.5%) CMS4 tumors were scored as stroma-low, indicating that CMS4 tumors cannot be identified solely based on stromal content. Higher budding counts were seen in CMS4 and CRIS-B tumors (p = 0.045 and p = 0.046). No other associations of the measured parameters were seen for any of the other CRIS subtypes. Our analysis revealed clear associations between histopathologic features and CMS or CRIS subtypes. However, identification of distinct molecular subtypes solely based on histopathology proved to be infeasible. Combining both molecular and morphologic features could potentially improve patient stratification.

Intrinsic Molecular Subtypes of Metastatic Castration-Resistant Prostate Cancer.

Although numerous biology-driven subtypes have been described previously in metastatic castration-resistant prostate cancer (mCRPC), unsupervised molecular subtyping based on gene expression has been less studied, especially using large cohorts. Thus, we sought to identify the intrinsic molecular subtypes of mCRPC and assess molecular and clinical correlates in the largest combined cohort of mCRPC samples with gene expression data available to date. We combined and batch-effect corrected gene expression data from four mCRPC cohorts from the Fred Hutchinson Cancer Research Center (N = 157), a small-cell neuroendocrine (NE) prostate cancer (SCNC)-enriched cohort from Weill Cornell Medicine (N = 49), and cohorts from the Stand Up 2 Cancer/Prostate Cancer Foundation East Coast Dream Team (N = 266) and the West Coast Dream Team (N = 162). Hierarchical clustering of RNA-sequencing data from these 634 mCRPC samples identified two distinct adenocarcinoma subtypes, one of which (adeno-immune) was characterized by higher gene expression of immune pathways, higher CIBERSORTx immune scores, diminished ASI benefit, and non-lymph node metastasis tropism compared with an adeno-classic subtype. We also identified two distinct subtypes with enrichment for an NE phenotype, including an NE-liver subgroup characterized by liver metastasis tropism, PTEN loss, and APC and SPOP mutations compared with an NE-classic subgroup. Our results emphasize the heterogeneity of mCRPC beyond currently accepted molecular phenotypes, and suggest that future studies should consider incorporating transcriptome-wide profiling to better understand how these differences impact treatment responses and outcomes.

Assessment of Prognostic Factors and Molecular Subtypes of Breast Cancer With a Continuous-Time Random-Walk MR Diffusion Model: Using Whole Tumor Histogram Analysis.

The continuous-time random-walk (CTRW) diffusion model to evaluate breast cancer prognosis is rarely reported. To investigate the correlations between apparent diffusion coefficient (ADC) and CTRW-specific parameters with prognostic factors and molecular subtypes of breast cancer. Retrospective. One hundred fifty-seven women (median age, 50 years; range, 26-81 years) with histopathology-confirmed breast cancer. Simultaneous multi-slice readout-segmented echo-planar imaging at 3.0T. The histogram metrics of ADC, anomalous diffusion coefficient (D), temporal diffusion heterogeneity (α), and spatial diffusion heterogeneity (β) were calculated for whole-tumor volume. Associations between histogram metrics and prognostic factors (estrogen receptor [ER], progesterone receptor [PR], human epidermal growth factor receptor 2 [HER2], and Ki-67 proliferation index), axillary lymph node metastasis (ALNM), and tumor grade were assessed. The performance of histogram metrics, both alone and in combination, for differentiating molecular subtypes (HER2-positive, Luminal or triple negative) was also assessed. Comparisons were made using Mann-Whitney test between different prognostic factor statuses and molecular subtypes. Receiver operating characteristic curve analysis was used to assess the performance of mean and median histogram metrics in differentiating the molecular subtypes. A P value <0.05 was considered statistically significant. The histogram metrics of ADC, D, and α differed significantly between ER-positive and ER-negative status, and between PR-positive and PR-negative status. The histogram metrics of ADC, D, α, and β were also significantly different between the HER2-positive and HER2-negative subgroups,and between ALNM-positive and ALNM-negative subgroups. The histogram metrics of α and β significantly differed between high and low Ki-67 proliferation subgroups, and between histological grade subgroups. The combination of αmean and βmean achieved the highest performance (AUC=0.702) to discriminate the Luminal and HER2-positive subtypes. Whole-tumor histogram analysis of the CTRW model has potential to provide additional information on the prognosis and intrinsic subtyping classification of breast cancer. 4 TECHNICAL EFFICACY: Stage 2.

Ultra-Hypofractionation for Whole-Breast Irradiation in Early Breast Cancer: Interim Analysis of a Prospective Study.

We report on the early clinical outcomes of a prospective series of early breast cancer (EBC) patients treated with ultra-hypofractionated post-operative whole-breast irradiation (WBI) after breast-conserving surgery (BCS) and axillary management. Primary endpoints were patient’s compliance and acute toxicity. Secondary endpoints included physician-rated cosmesis and ipsilateral breast tumour recurrence (IBTR). Acute toxicity was evaluated at the end of WBI, 3 weeks and 6 months thereafter, according to the Common Terminology Criteria for Adverse Events (v. 5.0). Patients were treated between September 2021 and May 2022. The treatment schedule for WBI consisted of either 26 Gy in 5 fractions over one week (standard approach) or 28.5 Gy in 5 fractions over 5 weeks (reserved to elders). Inverse planned intensity-modulated radiation therapy (IMRT) was used employing a static technique. A total of 70 patients were treated. Fifty-nine were treated with the 26 Gy/5 fr/1 w and 11 with the 28.5 Gy/5 fr/5 ws schedule. Median age was 67 and 70 in the two groups. Most of the patients had left-sided tumours (53.2%) in the 26 Gy/5 fr/1 w or right-sided lesions (63.6%) in the 28.5 Gy/5 fr/5 ws group. Most of the patients had a clinical T1N0 disease and a pathological pT1pN0(sn) after surgery. Ductal invasive carcinoma was the most frequent histology. Luminal A intrinsic subtyping was most frequent. Most of the patients underwent BCS and sentinel lymph node biopsy and adjuvant endocrine therapy. All patients completed the treatment program as planned. Maximum detected acute skin toxicities were grade 2 erythema (6.7%), grade 2 induration (4.4%), and grade 2 skin colour changes. No early IBTR was observed. Ultra-hypofractionated WBI provides favourable compliance and early clinical outcomes in EBC after BCS in a real-world setting.

A quantitative characterization of the spatial distribution of brain metastases from breast cancer and respective molecular subtypes.

Brain metastases (BM) remain a significant cause of morbidity and mortality in breast cancer (BC) patients. Specific factors promoting the process of BM and predilection for selected neuro-anatomical regions remain unknown, yet may have major implications for prevention or treatment. Anatomical spatial distributions of BM from BC suggest a predominance of metastases in the hindbrain and cerebellum. Systematic approaches to quantifying BM location or location-based analyses based on molecular subtypes, however, remain largely unavailable. We analyzed stereotactic Cartesian coordinates derived from 134 patients undergoing gamma- knife radiosurgery (GKRS) for treatment of 407 breast cancer BMs to quantitatively study BM spatial distribution along principal component axes and by intrinsic molecular subtype (ER, PR, Herceptin). We used kernel density estimators (KDE) to highlight clustering and distribution regions in the brain, and we used the metric of mutual information (MI) to tease out subtle differences in the BM distributions associated with different molecular subtypes of BC. BM location maps according to vascular and anatomical distributions using Cartesian coordinates to aid in systematic classification of tumor locations were additionally developed. We corroborated that BC BMs show a consistent propensity to arise posteriorly and caudally, and that Her2+ tumors are relatively more likely to arise medially rather than laterally. To compare the distributions among varying BC molecular subtypes, the mutual information metric reveal that the ER-PR-Her2+ and ER-PR-Her2- subtypes show the smallest amount of mutual information and are most molecularly distinct. The kernel density contour plots show a propensity for triple negative BC to arise in more superiorly or cranially situated BMs. We present a novel and shareable workflow for characterizing and comparing spatial distributions of BM which may aid in identifying therapeutic or diagnostic targets and interactions with the tumor microenvironment. Further characterization of these patterns with larger multi-institutional data-sets may have major impacts on treatment or management of cancer patients.

Long-term treatment patterns and survival in metastatic breast cancer by intrinsic subtypes – an observational cohort study in Sweden

BackgroundLongitudinal, real-world data on the management of metastatic breast cancer is increasingly relevant to understand breast cancer care in routine clinical practice. Yet such data are scarce, particularly beyond second- and third-line treatment strategies. This study, therefore, examined both the long-term treatment patterns and overall survival (OS) in a regional Swedish cohort of female patients with metastatic breast cancer stratified by subtype in routine clinical practice during a recent eight-year period and correlation to current treatment guidelines.MethodsConsecutive female patients with metastatic breast cancer clinically managed at Uppsala University Hospital, Uppsala, Sweden, during 2009–2016 and followed until the end of September, 2017 (n = 370) were included and, where possible, classified as having one of five, intrinsic subtypes: Luminal A; Luminal B; human epidermal growth factor receptor 2-positive (HER2+)/ estrogen receptor-positive (ER+); HER2+/estrogen receptor-negative (ER-); or triple negative breast cancer (TNBC). Treatment patterns and OS were estimated by subtype using time-to-event methods.ResultsA total of 352/370 patients with metastatic breast cancer (mean age 67.6 years) could be subtyped: 118 (34%) were Luminal A, 119 (34%) Luminal B, 31 (8%) HER2+/ER-, 38 (11%) HER2+/Luminal, and 46 (13%) TNBC. The median number of metastatic treatment lines was 3. Most patients were on active treatment during follow-up (80% of the observation period), except for patients with TNBC who were on treatment for 60% of the observation time. Overall, 67% of patients died whilst on treatment. Among all patients (n = 370), median OS was 32.5 months (95% CI = 28.2–35.7). The 5-year survival rate was highest for HER2+/Luminal (46%) patients, followed by Luminal B (29%), Luminal A (28%), HER2+/ER- (21%), and TNBC (7%). Increasing age and number of metastatic sites also predicted worse survival.ConclusionsMetastatic breast cancer patients in Sweden, irrespective of subtype, generally receive active treatment until time of death. Survival varies considerably across subtypes and is also associated with patient characteristics. Regardless of differences in treatment patterns for Luminal A and B patients, long-term OS was the same.

Molecular Classification of Breast Cancer: Relevance and Challenges.

Appropriate patient management requires precise and meaningful tumor classification. Breast cancer classification continues to evolve from traditional morphologic evaluation to more sophisticated systems with the integration of new knowledge from research being translated into practice. Breast cancer is heterogeneous at the molecular level, with diversified patterns of gene expression, which is presumably responsible for the difference in tumor behavior and prognosis. Since the beginning of this century, new molecular technology has been gradually applied to breast cancer research on issues pertinent to prognosis (prognostic signature) and therapeutic prediction (predictive signature), and much progress has been made. To summarize the current state and the prospective future of molecular classification of breast cancer. Sources include recent medical literature on molecular classification of breast cancer. Identification of intrinsic tumor subtypes has set a foundation for refining the breast cancer molecular classification. Studies have explored the genetic features within the intrinsic cancer subtypes and have identified novel molecular targets that led to the innovation of clinical assays to predict a patient's prognosis and to provide specific guidelines for therapeutic decisions. With the development and implication of these molecular tools, we have remarkably advanced our knowledge and enhanced our power to provide optimal management to patients. However, challenges still exist. Besides accurate prediction of prognosis, we are still in urgent need of more molecular predictors for tumor response to therapeutic regimes. Further exploration along this path will be critical for improving a patient's prognosis.

Overexpression in metastatic breast cancer supports Syndecan-1 as a marker of invasiveness and poor prognosis

BackgroundMetastasis is the main cause of breast cancer (BC) mortality. Increasing evidence points to a role of syndecan-1 (CD138) expression as a prognostic marker involved in BC tissue and leptomeningeal metastasis. Aim of this study was to investigate and compare syndecan-1 tissue expression and localization in primary and secondary BC, focusing on brain metastases.MethodsSyndecan-1 expression was determined by immunohistochemistry. Focal vs diffuse (< or > 50% of cancer cells, respectively) pattern of expression, cellular localization (cytoplasm vs membrane) and intensity of immunostaining on neoplastic cells were evaluated. Moreover, the extent and pattern of expression of syndecan-1 were compared between primary tumors and paired metastases and correlated with the tumor intrinsic subtype.ResultsA total of 23 cases, 10 with paired primary and metastatic tumor and 13 brain metastases, were evaluated. Syndecan-1 was expressed in both primary and metastatic BC. A diffuse cytoplasmic expression was observed in most primary BCs; by contrast, all metastatic lesions showed a membrane pattern of expression, suggesting a shift in cellular localization of syndecan-1 during the metastatic process. Concerning the extent of expression, we observed in metastatic lesions, a trend of association between intrinsic subtypes and extent of positivity. In particular, both BC characterized by overexpression of HER2 and triple-negative tumors were correlated with a diffuse pattern of expression with a moderate to strong intensity.ConclusionA diffuse cytoplasmic expression was observed in most primary BCs; by contrast, all metastatic lesions showed a membrane pattern of expression, suggesting a shift in cellular localization of syndecan-1 during the metastatic process.

KS01.4.A Transcriptional evolution of glioblastoma point towards changes in bulk composition, mesenchymal sub-type as end-state, and a prognostic association with increased extracellular matrix gene expression

Abstract Background Glioblastoma is the most prevalent and severe type of malignant brain tumor in adults. Although the genetic make-up initiating glioblastoma is increasingly better understood, a better understanding in the mechanisms that drive its evolution, heterogeneity and therapy resistance may reveal new directions for therapy development. To get better insights into glioblastoma evolution, we analyzed and deconvoluted transcriptomes of primary and recurrent glioblastoma resections. Material and Methods Matching primary and secondary resections from n=185 uniformly treated glioblastoma patients were collected as part of EORTC Study 1542 and RNA-sequenced. Data was extended with pairs from n=51 patients from the GLASS study. The datasets were subjected to differential and deconvolution analysis using in-house algorithms. Results When projecting the tumor samples into a reduced Glioblastoma Intrinsic Transcriptional Subtype space, visualization of transitions indicated that the CL subtype switches most often. As we found no more transitions from MES to other subtypes than to be expected by chance, we concluded that MES is an end-state. On average, tumor purity percentages decreased from ~67% to ~50%, mostly due to an increase in macrophages/microglia. Differential expression analysis was performed with correction for the fraction of non-malignant cells. While expression of glioblastoma associated oncogenes did not change significantly over time, marker genes for macrophages/microglia, neurons and oligodendrocytes were up-regulated whereas endothelial cell markers were down-regulated. A cluster of ~30 extracellular matrix associated (ECM) genes increased significantly over time. Single cell RNA-seq, IF-staining and RNA-ish indicated the signature is most strongly expressed near intra-tumoral vessels. Since endothelial marker genes were down-regulated over time, this suggests a form of prognostic vessel progression with a representative transcriptome signature. Conclusion Using a large cohort and validation set of uniformly treated patients, we demonstrate how the glioblastoma transcriptome changes over time with in particular changes the composition of the tumor and its environment. The tumor purity decrease over times suggests a more invasive phenotype or recruitment of non-malignant cells or a combination of both. A post-progression increase in expression of ECM-associated genes expressed near blood vessels was associated with poor survival. Concluding, while no consistent path for transcriptional evolution of tumor cells was observed other than transitions to the MES subtype, glioblastoma becomes more aggressive in time by (re-)organizing its environment.