Tumor Molecular Subtypes Research Articles

Whole transcriptome analysis of breast tumors during neoadjuvant chemotherapy: association with response to preoperative chemotherapy

Introduction. Treatment of breast cancer often includes systemic neoadjuvant chemotherapy. The frequency of complete morphological response varies significantly depending on the molecular subtype of tumor. However, even in triple negative breast cancer, which is considered the most sensitive, it does not exceed 50 %. Therefore, the search for new genetic predictors of tumor response to preoperative treatment, as well as the assessment of tumor changes during neoadjuvant chemotherapy are highly relevant.Objective – to perform whole-transcriptome analysis of breast cancer during neoadjuvant chemotherapy depending on tumor response to preoperative treatment.Materials and methods. This study included 39 patients with luminal B HER2-positive (human epidermal growth factor receptor 2) breast cancer who received 6 to 8 cycles of neoadjuvant chemotherapy. We performed whole-transcriptome analysis of paired biopsy and surgical specimens using the Clariom™ S Assay, human (Affymetrix, USA).Results. We observed significant differences in the pretreatment expression of 166 genes (13 were up-regulated and 153 were down-regulated) between patients with objective response to therapy and those without it. Comparison of preand post-treatment expression profiles demonstrated 680 differentially expressed genes in patients with complete and partial response and 3240 differentially expressed genes in patients with stable or progressive disease. Venn diagram showed that patients with and without objective response to neoadjuvant chemotherapy shared 105 differentially expressed genes.Conclusion. We performed primary screening of genes in breast tumors before therapy and identified genes whose pretreatment expression differed significantly between patients with objective response to neoadjuvant chemotherapy and those without it. Further validation of these genes in an independent sample will allow the development of a genetic panel to evaluate the response to neoadjuvant chemotherapy. Assessment of changes in the expression of tumor genes during treatment depending on patient’s response to therapy can be useful for further development of a panel of genes, which will enable the evaluation of clinical response to chemotherapy, as well as identification of key cellular processes that change the activity of genes during therapy.

Clinicopathological Factors Affecting Breast Cancer Survival in Jamaican Women: A Retrospective Review.

Breast cancer is the leading cause of cancer affecting women worldwide. The survival rate is primarily affected by the stage of the disease and several other demographic and clinicopathological factors. This study is a retrospective cohort study of female patients of the University Hospital of the West Indies diagnosed with breast cancer between 2011 and 2016. The age, tumor size, SBR/Nottingham grade, tumor histologic subtype, tumor molecular subtype, and survival status of the cohort on November 1, 2019, were determined. The data were summarized. Survival across each variable was compared using univariate log-rank tests, Cox proportional hazard models, and crude and adjusted models. A second wave analysis was performed excluding patients whose survival status was presumed. A total of 503 patients were analyzed. The overall survival rate at 1, 3, and 5years were 96.4%, 84.9%, and 79.0%, respectively, for the entire cohort. The molecular subtype was the most significant clinicopathological factor affecting overall survival. A younger age < 40years, higher histologic grade, estrogen receptor-negative breast cancers, invasive ductal type breast cancers, and T1 lesions were associated with poorer survival outcomes at 5years. The findings were reproduced after a second wave analysis excluding patients who were presumed alive was applied. Breast cancer overall survival in Jamaica is consistent with that of other developing countries in the literature. This study is an important contribution to the growing body of literature available and aids to the overall understanding of the behavior of breast cancer locally.

AKR1B10 as a Potential Novel Serum Biomarker for Breast Cancer: A Pilot Study.

BackgroundAldo-keto reductase 1B10 (AKR1B10) is a secretory protein that is upregulated in breast cancer.ObjectiveThis case-controlled pilot study evaluated the serum level of AKR1B10 in healthy women and patients with a localized or metastatic breast cancer.MethodsAKR1B10 levels were measured by ELISA and IHC in several patient cohorts.ResultsOur data showed that serum AKR1B10 was significantly elevated in patients with localized (6.72 ± 0.92 ng/ml) or metastatic (7.79 ± 1.13 ng/ml) disease compared to cancer-free healthy women (1.69 ± 0.17 ng/ml) (p<0.001); the serum AKR1B10 was correlated with its expression in tumor tissues, but not with the tumor burden, molecular subtypes or histological stages. After surgical removal of primary tumors, the serum AKR1B10 was rapidly decreased within 3 days and plateaued at a level similar to that of healthy controls in most patients. ROC curve analysis suggested the optimal diagnostic cut-off value of serum AKR1B10 at 3.456 ng/ml with AUC 0.9045 ± 0.0337 (95% CI 0.8384 – 0.9706), sensitivity 84.75% (95% CI 73.01% to 92.78%), and specificity 93.88% (95% CI 83.13% to 98.72%).ConclusionsThese data indicate the potential value of serum AKR1B10 as a biomarker of breast cancer.

Abstract P3-05-02: A minimal DNA-methylation signature to estimate tumor content and molecular subtype in breast cancer tissue samples with potential application to liquid biopsy

Abstract Introduction: Breast cancer (BC) is a heterogeneous disease characterized by different molecular "intrinsic" subtypes (PAM50) with distinct prognostic and therapeutic implications. DNA methylation (DNAm) is one of the most studied epigenetic mechanisms involved in BC tumorigenesis and progression. Recently, many studies have demonstrated the capability of DNAm-based assays in detecting and monitoring the disease in liquid biopsy samples from patients with BC, thus confirming promising role of DNAm-based biomarkers in the context of precision oncology. Here we present a novel computational method that exploits a minimal set of informative, clonal DNAm sites to estimate tumor content and molecular subtype in BC tissue samples with potential application for liquid biopsy analyses. Methods: DNAm data of TCGA-BRCA comprising 737 tumor samples, including 135 Basal-like (Basal), 46 HER2-enriched (HER2e) and 556 Luminal A/B (LumA/B) samples, and 96 normal tissue samples were downloaded from GDC Data Portal. To estimate tumor purity, we selected DNAm sites based on the following characteristics: (1) AUC&amp;gt;0.8 or AUC&amp;lt;0.2 (hyper- and hypo-methylated sites, respectively) in tumor versus normal samples; (2) range of beta-values in tumor samples greater than 0.5; (3) max and min beta-values above 0.9 or below 0.1, for hyper- and hypo-methylated sites, respectively; (4) the 3rd and 1st quartiles of normal samples beta-values below 0.3 or above 0.7, for hyper- and hypo-methylated sites, respectively. Tumor purity was then estimated taking the median of beta-values for hyper and 1-beta for hypo of selected sites for each sample. This selection was carried out considering all TCGA-BRCA samples and by PAM50 subtype (Basal, HER2e and LumA/B). After correction for purity, the set of subtype-specific sites (n=89) was also used as input to a generalized multinomial regression model (GLMNET) to classify BC samples into molecular subtypes. The model was trained in the TCGA-BRCA dataset using a 5-fold cross-validation. The performance was then tested in two independent datasets retrieved through the recountmethylation R package: GSE72251 (n=117) and GSE84207 (n=254). Results: Our estimates of sample purities, exploiting only 20 DNAm sites, show high correlation with those from InfiniumPurify (R=0.90, p &amp;lt; 10-16), another DNAm-based tool that requires hundreds of sites for purity estimation. The correlation was further improved using subtype-specific sites (LumA/B: R=0.95, p &amp;lt; 10-16; HER2e: R=0.96, p &amp;lt; 10-16; Basal: R=0.93, p &amp;lt; 10-16). For classification of tumor samples into molecular subtypes, our model obtained high accuracy for all subtypes (99%, 84% and 99%, for Basal, HER2e and LumA/B, respectively) in the training dataset. In the test datasets the F1-scores for Basal, HER2e and LumA/B subtypes were 89%, 60% and 87% for GSE72251, 91%, 42% and 93% for GSE84207. Conclusions: Our computational framework exploiting a minimal signature of DNAm sites demonstrates high accuracy in quantifying tumor purity and predicting molecular subtypes in the training dataset. In the two independent test sets including &amp;gt;350 samples, high accuracy was obtained for LumA/B and Basal samples while HER2e samples showed lower F1-score due to a drop of recall, though obtaining precision &amp;gt;80% in both datasets. Based on these results, a DNAm-based targeted-seq assay has been designed and will be applied to a series of plasma samples from patients with metastatic BC collected within our center. First results of the assay will be presented during the meeting. Citation Format: Dario Romagnoli, Francesca Galardi, Francesca De Luca, Chiara Biagioni, Erica Moretti, Laura Biganzoli, Ilenia Migliaccio, Luca Malorni, Matteo Benelli. A minimal DNA-methylation signature to estimate tumor content and molecular subtype in breast cancer tissue samples with potential application to liquid biopsy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-05-02.

Abstract P1-02-04: Modified Miller-Payne score as a pragmatic and efficient alternative to Residual Cancer Burden

Abstract Background: Several histopathologic classification systems have been described to characterise residual tumour in patients undergoing neoadjuvant chemotherapy (NACT) for breast cancer. Residual Cancer Burden (RCB) has demonstrated prognostic value but requires pathologists to enter specific data items into an external portal to generate a score. This process is time consuming and many measurements are subject to inter-observer variability. The Modified Miller Payne (MMP) score is a global assessment of tumour response in the breast and lymph nodes by pathologists performed as part of routine pathological assessment without the need to measure specific variables and additional data entry. We aimed to assess the performance of the more pragmatic MMP score in predicting patient outcome alongside RCB. Methods: MMP score is a modification of the original Miller Payne method classifying residual tumour into 5 groups (no/minimal response, partial response, minimum residual disease, DCIS, complete response) plus assessment of nodal response. Post treatment histology was reviewed and RCB and MMP scores calculated as per protocol. Cox proportional hazard models were fitted to survival data: two univariate models where overall survival is regressed against RCB class and against MMP score, and a bivariate model for overall survival against MMP score and a binary variable for node response. Akaike Information Criterion (AIC) and Harrell’s C-index were used to assess the performance of each prognostic model. Unweighted and weighted estimates of Cohen’s kappa were used to measure the agreement between RCB class and MMP score. In addition, MMP score categories 4 and 5 were collapsed into a single category, which for the purpose of agreement analysis is considered equivalent to RCB class 0. Results: 412 early breast cancer patients that received NACT at the Edinburgh Breast Unit between 2011-2018, were included , with median follow-up of 5 years. Tumour molecular subtypes were as follows: ER+ HER2- 37%, HER2+ 32%, Triple negative 30%. The univariate Cox model for RCB had AIC 796 and C-index 0.65 (SE 0.03), against AIC 800 and C-index 0.64 (SE 0.04) of the univariate model for MMP score. The bivariate model with MMP score and node response displays an AIC of 795.1 and C-index = 0.66 (se: 0.03). All RCB and MMP categories included in the Cox models are significant to p = 0.0001, while node response is significant up to p = 0.05. The unweighted Cohen’s kappa between RCB class and MMP score is 0.58 (95% CI: 0.52 - 0.64), which increases to 0.85 (p = 0.0001) when accounting for elements off the main diagonal (weighted kappa). Conclusion: The results indicate potentially equivalent prognostication value between MMP score and RCB class. The comparison of model performance suggests that the bivariate Cox model using MMP score and node response can fit the available survival data as well as the univariate model using RCB class. While the estimated agreement on the main diagonal is only moderate, the weighted estimate shows a strong estimated agreement between the two scoring systems. Given the practical and efficient nature of this scoring method, MMP appears to be a robust alternative to RCB. Further investigation and research should focus on the prognostic value of MMP for recurrence-free survival and on external validation of the outlined predictive models. Univariate, OS ~ RCB classHR (CI 95%)Univariate, OS ~ MMP scoreHR (CI 95%)Bivariate, OS ~ MMP score + Node responseHR (CI 95%)Baseline: RCB 3Baseline: MMP 1Baseline: MMP 1 and Node Response 1RCB 20.35 (0.21 - 0.61)MMP 20.37 (0.21 - 0.67)MMP 20.31 (0.17 - 0.58)RCB 10.24 (0.11 - 0.56)MMP 30.28 (0.15 - 0.53)MMP 30.22 (0.11 - 0.43)RCB 00.21 (0.1 - 0.4)MMP 4-50.24 (0.12 - 0.51)MMP 4-50.19 (0.09 - 0.42)Node Resp 00.51 (0.3 - 0.86) Citation Format: Peter S Hall, Alistair Ironside, Giovanni Tramonti, Alex Cavanagh, Katy Quiohilag, Olga Oikonomidou. Modified Miller-Payne score as a pragmatic and efficient alternative to Residual Cancer Burden [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-02-04.

Abstract P1-09-06: Insulinemic potential of diet and risk of total and subtypes of breast cancer among US women

Abstract Background: Insulin resistance and hyperinsulinemia play important roles in the progression of multiple chronic disease and conditions. Diet modulates insulin response; however, evidence is limited regarding whether diet with higher insulinemic potential is associated with invasive breast cancer risk.Objectives: We prospectively evaluated the association between adherence to a food-based empirical dietary index for hyperinsulinemia (EDIH) and the incidence of invasive breast cancer.Methods: We prospectively followed 76,595 women from the Nurses’ Health Study (NHS, 1984-2016) and 93,295 women from the Nurses’ Health Study II (NHSII, 1991-2017). Diet was assessed by food frequency questionnaires every 4 years. The insulinemic potential of diet was evaluated using the EDIH that was pre-defined based on circulating C-peptide concentrations. Higher scores indicate higher insulinemic potential, while lower scores indicate lower insulinemic potential.Results: During 4,215,162 person-years of follow-up, we documented 10,595 breast cancer cases (6,639 NHS; 3,914 NHSII). Being in the highest, compared with the lowest, EDIH quintile was associated with higher breast cancer risk (HRQ5vsQ1 1.18; 95% CI 1.10, 1.27; P-trend&amp;lt;0.01). The association was suggestively strongest among women with current BMI&amp;lt;25 kg/m2 (HRQ5vsQ1 1.20; 95% CI 1.08, 1.34; P-trend&amp;lt;0.01; P-interaction=0.06) compared to overweight/obese women. Although heterogeneity by estrogen receptor (ER) status was non-significant (P=0.17), the strongest association between EDIH and breast cancer was observed with ER-negative tumors (HRQ5vsQ1 1.26; 95% CI 1.04, 1.51; P-trend&amp;lt;0.01). Among tumor molecular subtypes, the strongest associations were observed with HER2-enriched tumors (HRQ5vsQ1 1.75; 95% CI 1.08, 2.82; P-trend=0.01).Conclusions: A dietary pattern contributing to hyperinsulinemia was associated with greater breast cancer risk in women from the NHS/NHSII. In particular, a more hyperinsulinemic diet was associated with higher risk of breast cancer among lean women when compared to overweight or obese women. Moreover, the hyperinsulinemic diet showed a stronger positive association with ER-negative breast tumors, independent of adiposity. Our findings suggest that dietary interventions to reduce insulinemic potential may have a role in breast cancer prevention. Citation Format: Andrea Romanos-Nanclares, Walter C. Willett, Bernard A. Rosner, Rulla M. Tamimi, Fred K. Tabung, Michelle D. Holmes, Wendy Y Chen, A. Heather Eliassen. Insulinemic potential of diet and risk of total and subtypes of breast cancer among US women [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-09-06.

Abstract P1-08-31: Simbiosys tumorscope: Biophysical modeling of patient-specific response to chemotherapy

Abstract Background: Breast Cancer (BC) patients exhibit a wide variety of responses to neoadjuvant chemotherapy (NACT). This is driven by factors both intrinsic (e.g., mutations, dysregulation, metabolic reprogramming) and extrinsic (e.g., nutrient/drug perfusion, interactions with surrounding healthy tissues and the tumor microenvironment (TME)) to the cells that make up each tumor. The SimBioSys TumorScope is a platform for making individualized predictions of the response of each patient's tumor to NACT. It employs 3D biophysical simulations that explicitly model the dynamics of cellular response to the ever-changing chemical milieu of drugs and nutrients that perfuse the TME during treatment, in order to predict when and where different regions of the tumor are growing, dying, and ultimately how a given patient will respond to treatment. Methods: The SimBioSys TumorScope constructs 3D in silico models of each patient's tumor directly from pretreatment DCE-MRIs. It combines this spatial model with personalized genome-scale models of tumor and tissue metabolism, pharmacokinetics, and pharmacodynamics, and vascular perfusion (based on DCE-MRI timeseries). The combined model is then simulated using a custom high-performance reaction-diffusion-material mechanics simulation engine which produces a spatio-temporal trajectory of tumor size, morphology, intra- and extracellular biochemistry. We evaluated the ability of the TumorScope software to predict volumetric response to NACT. A validation set comprising the pretreatment records (including MRIs) of 780 BC patients that underwent NACT was used. These patients spanned a wide range of tumor sizes, molecular subtypes, and NCCN-recommended treatment regimens. Simulations were initialized using each patient’s pretreatment MRI and pathology data and run from the start of therapy to the specified surgical date. Simulated tumor volumetric percent response (calculated as the ratio of change in tumor volume to initial volume) at the time of surgery was then compared with actual tumor volumetric percent response extracted from presurgical MRIs. Among patients for which event free survival data was available (n = 480), we performed a Cox proportional hazard analysis. Results: The SimBioSys TumorScope predicted pre-surgical tumor volumetric response with a median error of 0.03% and median absolute deviation of 8.2%. Among the patients for which EFS data was available, we found a hazard ratio of 1.8 associated with having a final simulated volume greater than 0.01 cc (p = 0.00048). Conclusions: The SimBioSys TumorScope produces accurate patient specific predictions of response to NACT using only standard-of-care pre-treatment data. Such predictions can aid in decision making, enabling physicians to select less-toxic regimens for patients in which a robust response is predicted, and more aggressive treatments and/or clinical trial enrollment when response is likely to be poor. Citation Format: John A Cole, Jr., Joseph R Peterson, Tyler M Earnest, Michael J Hallock, Daniel J Cook, Eduardo Braun, Anu Antony, John R Pfeiffer, Tushar Pandey. Simbiosys tumorscope: Biophysical modeling of patient-specific response to chemotherapy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-08-31.

A Complex Radiomic Signature in Luminal Breast Cancer from a Weighted Statistical Framework: A Pilot Study.

Radiomics is rapidly advancing in precision diagnostics and cancer treatment. However, there are several challenges that need to be addressed before translation to clinical use. This study presents an ad-hoc weighted statistical framework to explore radiomic biomarkers for a better characterization of the radiogenomic phenotypes in breast cancer. Thirty-six female patients with breast cancer were enrolled in this study. Radiomic features were extracted from MRI and PET imaging techniques for malignant and healthy lesions in each patient. To reduce within-subject bias, the ratio of radiomic features extracted from both lesions was calculated for each patient. Radiomic features were further normalized, comparing the z-score, quantile, and whitening normalization methods to reduce between-subjects bias. After feature reduction by Spearman’s correlation, a methodological approach based on a principal component analysis (PCA) was applied. The results were compared and validated on twenty-seven patients to investigate the tumor grade, Ki-67 index, and molecular cancer subtypes using classification methods (LogitBoost, random forest, and linear discriminant analysis). The classification techniques achieved high area-under-the-curve values with one PC that was calculated by normalizing the radiomic features via the quantile method. This pilot study helped us to establish a robust framework of analysis to generate a combined radiomic signature, which may lead to more precise breast cancer prognosis.

Abstract P3-12-32: Long-term outcomes among young Saudi women with breast cancer

Abstract Introduction: Breast cancer (BC) represents 30.1 % of all cancers reported in Saudi females with median age at diagnosis 50 years. BC in young women (≤ 40 years ) accounts for 20% of all female BCs, and is histologically more aggressive as compared to the one seen in wome above 50 years of age. Differences with regard to tumor biology, presentation, genetics and molecular subtypes may contribute to poor prognosis among younger age group. BC in young Saudi women is a crucial problem and limited information exists regarding its pathologic characteristics and long term outcome. Purpose: This study investigated the long-term disease outcomes among young (≤ 40 years) Saudi BC patients as compared to older ones (&amp;gt;40 years), as well as assessed the clinicopathological parameters differeneces among the two groups. Methods: This was a retrospective longitudinal cohort study of 694 female BC patients over a 10-year period (January 2007 to December 2017). Demographic and clinicopathological data was collected. Disease presentation, disease characteristics. Cox regression analysis was performed and Kaplan-Meier curves were generated to assess overall survival. Cross tabulation was used to assess the difference in clinicopatholgical parameeters among the two age groups. Results: Among the included BC cases, 17.1% (N=119) were ≤ 40 years old . The mean survival time was 5.0 ± 2.6 years. ER, PR expression, molecular subtype, tumor grade, and N stage were variables significantly among the two age groups (p= &amp;lt;0.001, 0.002, 0.002, 0.003 and 0.038, respectively). More ER positive cases in older age group compared to the younger (76.2% vs 61.3%). PR was mainly positive in older age group (64.2% vs 49.6%), in contrast, Comparatively greater number of cases were Luminal A in older age group (33% vs 21%) while triple negative cases were more prevalent among the younger age group (23.5% vs 13.5%). Majority of the patients in younger age group had grade 3 tumors (56.3% vs 38.5%). The Nodal stage N2 was significantly more prevalent. among the younger age group (26.9% vs 16.3%). Although not statistically significant, stage 3 &amp; stage 4 were more common among younger age group (22.7% vs 15.6% and 18.5% vs 15.6% respectively), while stage 1 was more common among the older age group (16.7% vs 10.9%). Age did not influence the local therapy in the study cohort. The younger age group was more likely to develop metastasis in comparison to the older group (37.8% vs 24.3%; p=0.002). Recurrence and disease progression were more likely to occur in younger patients, compared to the older ones (12.6% vs 6.3% and 29.4% vs 18.2% respectively), while complete clinical remission was achieved more in older patients compared to the younger ones (76.7% vs 66.4%). The overall survival was not statistically different among two age groups, however, when stratified using molecular subgroup, Luminal A subtype was statistically significant (p=0.02) indicating a poor over all survival among younger patients. Conclusion: The long term overall survival of BC in younger patients (≤ 40 years) was not significantly worse than older patients. But, younger BC patients with luminal A subtype have a poor overall survival in comparison to older ones. ER and PR expression, molecular subtype, tumor grade, and N stage are significantly different among the two groups which may contribute to significanly more local recurrence and distance metastasis among younger patients. Citation Format: Omalkhair Abdullah Aboualkhair, Ahmad Omair, Emad Masuadi, Ghaida Alamri, Alaa Aljehani, Abdulmohsen Alkushi, Ann Partridge. Long-term outcomes among young Saudi women with breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-12-32.

Ferroptosis Mediation Patterns Reveal Novel Tool to Implicate Immunotherapy and Multi-Omics Characteristics in Bladder Cancer.

Background: The regulatory role of ferroptosis in malignant tumours has been recently demonstrated. However, the potential roles of ferroptosis mediation patterns in bladder cancer remain elusive. Materials and Methods: The ferroptosis mediation patterns of 889 bladder cancer samples were comprehensively evaluated based on ferroptosis-related genes. The underlying correlations between these mediation patterns and multi-omic characteristics of bladder cancer were systematically analysed. The ferroptosis mediation patterns of individual samples were quantified by ferropscore using the principal component analysis algorithm. The typical ferroptosis-related genes with prognostic roles were further randomly validated using immunohistochemical staining, real-time polymerase chain reaction and western blotting. Results: Three different ferroptosis mediation patterns were identified. The abundance of infiltration of 23 immune cells was different among the three mediation patterns. The quantification of ferroptosis mediation patterns in individual samples served as a promising tool for predicting patient survival outcomes; immune cell infiltration abundance; tumour mutation burden; oncogenic mutation status and tumour grade, stage and molecular subtypes. Low ferropscore combined with high tumour mutation burden was associated with the best survival prognosis. Expressions of PD-L1 (p < 0.001), PD-1 (p = 0.002) and CTLA-4 (p = 0.003) were all significantly upregulated in the high ferropscore group. Low ferropscores also predicted good immunotherapy response for anti-CTLA4 strategy. The mRNA and protein levels of FADS2, a typical ferroptosis-related gene used in the study, were higher in bladder cancer cell lines than in controlled SV-HUC-1 cells. In addition, immunohistochemical staining revealed significantly higher expression levels of FADS2 in human bladder cancer tumour tissues than in normal tissues. Conclusion: This study identified three distinct ferroptosis mediation patterns in bladder cancer. Quantification of ferroptosis mediation patterns in individual samples may help to improve the understanding of multiomic characteristics and guide future immunotherapy responses to bladder cancer.

Gene Expression Profiling in Early Breast Cancer-Patient Stratification Based on Molecular and Tumor Microenvironment Features.

Patients with early-stage hormone receptor-positive, human epidermal growth factor receptor 2-negative (HER2−) breast cancer (BC) are typically treated with surgery, followed by adjuvant systemic endocrine therapy with or without adjuvant chemotherapy and radiation therapy. Current guidelines regarding the use of adjuvant systemic therapy depend on clinical and pathological factors, such as the morphological assessment of tumor subtype; histological grade; tumor size; lymphovascular invasion; and lymph node status combined with estrogen receptor, progesterone receptor, and HER2 biomarker profiles assessed using immunohistochemistry and in situ hybridization. Additionally, the prognostic and predictive value of tumor-infiltrating lymphocytes and their composition is emerging as a key marker in triple negative (TNBC) and HER2-enriched molecular breast tumor subtypes. However, all these factors do not necessarily reflect the molecular heterogeneity and complexity of breast cancer. In the last two decades, gene expression signatures or profiling (GEP) tests have been developed to predict the risk of disease recurrence and estimate the potential benefit of receiving adjuvant systemic chemotherapy in patients with luminal breast cancer. GEPs have been utilized to help physicians to refine decision-making process, complementing clinicopathological parameters, and can now be used to classify the risk of recurrence and tailoring personalized treatments. Several clinical trials using GEPs validate the increasing value of such assays in different clinical settings, addressing relevant clinical endpoints. Finally, the recent approval of immune checkpoint inhibitors in TNBC and the increasing use of immunotherapy in different molecular BC populations highlight the opportunity to refine current GEPs by including a variety of immune-related genes that may help to improve predicting drug response and finetune prognosis.

A Pan-Cancer Study of KMT2 Family as Therapeutic Targets in Cancer.

Objective Exome sequencing studies have shown that the histone-lysine N-methyltransferase 2 (KMT2) gene is one of the most commonly mutated genes in a range of human malignancies and is linked to some of the most common and deadly solid tumors. However, the connection between this gene family's function and tumor type, immunological subtype, and molecular subtype dependency is still unknown. Methods We examine the expression patterns of the histone-lysine N-methyltransferase 2 (KMT2) gene, as well as their relationship to patient survival. We also used a pan-cancer analysis to link their function to immunological subtypes, the tumor microenvironment, and treatment sensitivity. Results Using the TCGA pan-cancer data, researchers looked at and examined KMT2 expression patterns and their links to patient survival and the tumor microenvironment in 33 cancer types. The expression of the KMT2 family changes significantly across and within cancer types, indicating significant inter- and intracancer heterogeneity. Patients' overall survival was often linked to the expression of KMT2 family members. However, the direction of the link differed depending on the KMT2 isoform and cancer type studied. Notably, in all cancer types examined, nearly all KMT2 family members were substantially linked with overall survival in patients with renal clear cell carcinoma (KIRC). Furthermore, all KMT2 genes have a strong relationship with immune infiltrate subtypes, as well as varying degrees of stromal cell infiltration and tumor cell stemness. Finally, we discovered that higher expression of KMT2s, particularly KMT2F and KMT2G, was linked to greater chemotherapeutic sensitivity in several cell lines. Conclusions The necessity to investigate each KMT2 member as a distinct entity inside each particular cancer type is highlighted by our comprehensive investigation of KMT2 gene expression and its relationship with immune infiltrates, tumor microenvironment, and cancer patient outcomes. Our research also confirmed the identification of KMT2 as a potential therapeutic target in cancer, but further laboratory testing is required.

Scientific research of the Department of Oncology and Medical Radiology of the Dnipro State Medical University

The purpose of the article is to present the results of scientific research of the Department of Oncology and Medical Radiology of the Dnipro State Medical University "Improvement of personalized methods of systemic treatment of malignant tumors taking into account their clinical and molecular genetic characteristics" (state registration 011U003384). The results of 4 research works are presented: "The role of tumor molecular subtypes during personalized treatment approach for metastatic breast cancer", "Prediction, prevention and treatment of hematologic toxicity of systemic therapy for breast cancer", "The rationale for the effectiveness of systemic treatment of breast cancer depending on the body weight index", "Optimization of radiological visualization of vascularization of the skin of soft tissues of patients during reconstructive operations on the lower extremities".

Molecular Subtypes, Metastatic Pattern and Patient Age in Breast Cancer: An Analysis of Italian Network of Cancer Registries (AIRTUM) Data.

Breast cancer stage at diagnosis, patient age and molecular tumor subtype influence disease progression. The aim of this study was to analyze the relationships between these factors and survival in breast cancer patients among the Italian population using data from the AIRTUM national database. We enrolled women with primary breast cancer from 17 population-based cancer registries. Patients were subdivided into older (>69 years), middle (50–69 years) and younger age groups (<50 years) and their primary tumors categorized into four molecular subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. There were 8831 patients diagnosed between 2010 and 2012 included. The most represented age group was 50–69 years (41.7%). In 5735 cases the molecular subtype was identified: HER2–/HR+ was the most frequent (66.2%) and HER2+/HR− the least (6.2%). Of the 390 women with metastases at diagnosis, 38% had simultaneous involvement of multiple sites, independent of age and molecular profile. In women with a single metastatic site, bone (20% of cases), liver (11%), lung (7%) and brain (3%) were the most frequent. In the studied age groups with different receptor expression profiles, the tumor metastasized to target organs with differing frequencies, affecting survival. Five-year survival was lowest in women with triple-negative (HER2−/HR–) tumors and women with brain metastases at diagnosis.

Kinesin Family Member C1 (KIFC1/HSET): A Potential Actionable Biomarker of Early Stage Breast Tumorigenesis and Progression of High-Risk Lesions.

The enigma of why some premalignant or pre-invasive breast lesions transform and progress while others do not remains poorly understood. Currently, no radiologic or molecular biomarkers exist in the clinic that can successfully risk-stratify high-risk lesions for malignant transformation or tumor progression as well as serve as a minimally cytotoxic actionable target for at-risk subpopulations. Breast carcinogenesis involves a series of key molecular deregulatory events that prompt normal cells to bypass tumor-suppressive senescence barriers. Kinesin family member C1 (KIFC1/HSET), which confers survival of cancer cells burdened with extra centrosomes, has been observed in premalignant and pre-invasive lesions, and its expression has been shown to correlate with increasing neoplastic progression. Additionally, KIFC1 has been associated with aggressive breast tumor molecular subtypes, such as basal-like and triple-negative breast cancers. However, the role of KIFC1 in malignant transformation and its potential as a predictive biomarker of neoplastic progression remain elusive. Herein, we review compelling evidence suggesting the involvement of KIFC1 in enabling pre-neoplastic cells to bypass senescence barriers necessary to become immortalized and malignant. We also discuss evidence inferring that KIFC1 levels may be higher in premalignant lesions with a greater inclination to transform and acquire aggressive tumor intrinsic subtypes. Collectively, this evidence provides a strong impetus for further investigation into KIFC1 as a potential risk-stratifying biomarker and minimally cytotoxic actionable target for high-risk patient subpopulations.

Bulk and Single-Cell Profiling of Breast Tumors Identifies TREM-1 as a Dominant Immune Suppressive Marker Associated With Poor Outcomes.

BackgroundTriggering receptor expressed on myeloid cells (TREM)-1 is a key mediator of innate immunity previously associated with the severity of inflammatory disorders, and more recently, the inferior survival of lung and liver cancer patients. Here, we investigated the prognostic impact and immunological correlates of TREM1 expression in breast tumors.MethodsBreast tumor microarray and RNAseq expression profiles (n=4,364 tumors) were analyzed for associations between gene expression, tumor immune subtypes, distant metastasis-free survival (DMFS) and clinical response to neoadjuvant chemotherapy (NAC). Single-cell (sc)RNAseq was performed using the 10X Genomics platform. Statistical associations were assessed by logistic regression, Cox regression, Kaplan-Meier analysis, Spearman correlation, Student’s t-test and Chi-square test.ResultsIn pre-treatment biopsies, TREM1 and known TREM-1 inducible cytokines (IL1B, IL8) were discovered by a statistical ranking procedure as top genes for which high expression was associated with reduced response to NAC, but only in the context of immunologically “hot” tumors otherwise associated with a high NAC response rate. In surgical specimens, TREM1 expression varied among tumor molecular subtypes, with highest expression in the more aggressive subtypes (Basal-like, HER2-E). High TREM1 significantly and reproducibly associated with inferior distant metastasis-free survival (DMFS), independent of conventional prognostic markers. Notably, the association between high TREM1 and inferior DMFS was most prominent in the subset of immunogenic tumors that exhibited the immunologically hot phenotype and otherwise associated with superior DMFS. Further observations from bulk and single-cell RNAseq analyses indicated that TREM1 expression was significantly enriched in polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and M2-like macrophages, and correlated with downstream transcriptional targets of TREM-1 (IL8, IL-1B, IL6, MCP-1, SPP1, IL1RN, INHBA) which have been previously associated with pro-tumorigenic and immunosuppressive functions.ConclusionsTogether, these findings indicate that increased TREM1 expression is prognostic of inferior breast cancer outcomes and may contribute to myeloid-mediated breast cancer progression and immune suppression.

MET-11 Recent advances in targeted therapies and immunotherapy for metastatic brain tumors

This presentation outlines CQ2 of Chapter 2 from the forthcoming updated version of the Clinical Practice Guidelines for Brain Tumors, edited by the Society. These guidelines discuss chemotherapy and other drug therapies for metastatic brain tumors in adult patients. First, there is no noteworthy change in the principle of prioritizing local treatment of symptomatic metastatic brain tumors or those that require local treatment in the near future. However, with recent advances in molecular-targeted drugs and/or immune checkpoint inhibitors, many physicians now consider starting systemic treatment prior to local treatment of brain metastases, even in patients with solid tumors that were once considered insensitive to chemotherapy, given that their symptoms are well-controlled and do not require urgent treatment. In the treatment of non-small cell lung cancer (NSCLC), the molecular subtypes of metastatic brain tumors with EGFR mutations and ALK fusion genes have yielded favorable responses to molecular-targeted drugs. Because small molecule drugs are well delivered to the central nervous system, systemic drug therapy with such targeted drugs is commonly selected for patients with untreated metastatic brain tumors. A recent phase II trial has shown the effectiveness of anti-PD-1 antibody pembrolizumab monotherapy for metastatic brain tumors from NSCLC. Because untreated metastatic brain tumors from renal cell carcinoma are prone to bleeding, local treatment of brain metastases should be prioritized before systemic treatment, even if the patient is asymptomatic. Regardless of BRAF mutation status, immune checkpoint inhibitors alone or in combination (nivolumab and ipilimumab) are effective against malignant melanoma with brain metastases; moreover, a combined treatment with BRAF and MEK inhibitors is effective against BRAF mutation-positive malignant melanoma with brain metastases. A novel HER2 inhibitor, tucatinib (unapproved), is expected to be effective against metastatic brain tumors from HER2-positive breast cancer.

On the Origin of Pancreatic Cancer: Molecular Tumor Subtypes in Perspective of Exocrine Cell Plasticity.

Pancreatic ductal adenocarcinoma (PDAC) is a devastating type of cancer. While many studies have shed light into the pathobiology of PDAC, the nature of PDAC’s cell of origin remains under debate. Studies in adult pancreatic tissue have unveiled a remarkable exocrine cell plasticity including transitional states, mostly exemplified by acinar to ductal cell metaplasia, but also with recent evidence hinting at duct to basal cell transitions. Single-cell RNA sequencing has further revealed intrapopulation heterogeneity among acinar and duct cells. Transcriptomic and epigenomic relationships between these exocrine cell differentiation states and PDAC molecular subtypes have started to emerge, suggesting different ontogenies for different tumor subtypes. This review sheds light on these diverse aspects with particular focus on studies with human cells. Understanding the “masked ball” of exocrine cells at origin of PDAC and leaving behind the binary acinar vs duct cell classification may significantly advance our insights in PDAC biology.

DNA Methylation Modification Map to Predict Tumor Molecular Subtypes and Efficacy of Immunotherapy in Bladder Cancer.

Background: Considering the heterogeneity and complexity of epigenetic regulation in bladder cancer, the underlying mechanisms of global DNA methylation modification in the immune microenvironment must be investigated to predict the prognosis outcomes and clinical response to immunotherapy. Methods: We systematically assessed the DNA methylation modes of 985 integrated bladder cancer samples with the unsupervised clustering algorithm. Subsequently, these DNA methylation modes were analyzed for their correlations with features of the immune microenvironment. The principal analysis algorithm was performed to calculate the DMRscores of each samples for qualification analysis. Findings: Three DNA methylation modes were revealed among 985 bladder cancer samples, and these modes are related to diverse clinical outcomes and several immune microenvironment phenotypes, e.g., immune-desert, immune-inflamed, and immune-excluded ones. Then patients were classified into high- and low-DMRscore subgroups according to the DMRscore, which was calculated based on the expression of DNA methylation related genes (DMRGs). Patients with the low-DMRscore subgroup presented a prominent survival advantage that was significantly correlated to the immune-inflamed phenotype. Further analysis revealed that patients with low DMRscores exhibited less TP53 wild mutation, lower cancer stage and molecular subtypes were mainly papillary subtypes. In addition, an independent immunotherapy cohort confirmed that DMRscore could serve as a signature to predict prognosis outcomes and immune responses. Conclusion: Global DNA methylation modes can be used to predict the immunophenotypes, aggressiveness, and immune responses of bladder cancer. DNA methylation status assessments will strengthen our insights into the features of the immune microenvironment and promote the development of more effective treatment strategies.

Alternative splicing of NF-YA promotes prostate cancer aggressiveness and represents a new molecular marker for clinical stratification of patients

BackgroundApproaches based on expression signatures of prostate cancer (PCa) have been proposed to predict patient outcomes and response to treatments. The transcription factor NF-Y participates to the progression from benign epithelium to both localized and metastatic PCa and is associated with aggressive transcriptional profile. The gene encoding for NF-YA, the DNA-binding subunit of NF-Y, produces two alternatively spliced transcripts, NF-YAs and NF-YAl. Bioinformatic analyses pointed at NF-YA splicing as a key transcriptional signature to discriminate between different tumor molecular subtypes. In this study, we aimed to determine the pathophysiological role of NF-YA splice variants in PCa and their association with aggressive subtypes.MethodsData on the expression of NF-YA isoforms were extracted from the TCGA (The Cancer Genome Atlas) database of tumor prostate tissues and validated in prostate cell lines. Lentiviral transduction and CRISPR-Cas9 technology allowed the modulation of the expression of NF-YA splice variants in PCa cells. We characterized 3D cell cultures through in vitro assays and RNA-seq profilings. We used the rank-rank hypergeometric overlap approach to identify concordant/discordant gene expression signatures of NF-YAs/NF-YAl-overexpressing cells and human PCa patients. We performed in vivo studies in SHO-SCID mice to determine pathological and molecular phenotypes of NF-YAs/NF-YAl xenograft tumors.ResultsNF-YA depletion affects the tumorigenic potential of PCa cells in vitro and in vivo. Elevated NF-YAs levels are associated to aggressive PCa specimens, defined by Gleason Score and TNM classification. NF-YAl overexpression increases cell motility, while NF-YAs enhances cell proliferation in PCa 3D spheroids and xenograft tumors. The transcriptome of NF-YAs-spheroids has an extensive overlap with localized and metastatic human PCa signatures. According to PCa PAM50 classification, NF-YAs transcript levels are higher in LumB, characterized by poor prognosis compared to LumA and basal subtypes. A significant decrease in NF-YAs/NF-YAl ratio distinguishes PCa circulating tumor cells from cancer cells in metastatic sites, consistently with pro-migratory function of NF-YAl. Stratification of patients based on NF-YAs expression is predictive of clinical outcome.ConclusionsAltogether, our results indicate that the modulation of NF-YA isoforms affects prostate pathophysiological processes and contributes to cancer-relevant phenotype, in vitro and in vivo. Evaluation of NF-YA splicing may represent a new molecular strategy for risk assessment of PCa patients.