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Background:Aberrant expression of DNA repair pathways such as homologous recombination (HR) can lead to DNA repair imbalance, genomic instability, and altered chemotherapy response. DNA repair imbalance may predict prognosis, but variation in DNA repair in diverse cohorts of breast cancer patients is understudied.Methods:To identify RNA-based patterns of DNA repair expression, we performed unsupervised clustering on 51 DNA repair-related genes in the Cancer Genome Atlas Breast Cancer [TCGA BRCA (n = 1,094)] and Carolina Breast Cancer Study [CBCS (n = 1,461)]. Using published DNA-based HR deficiency (HRD) scores (high-HRD ≥ 42) from TCGA, we trained an RNA-based supervised classifier. Unsupervised and supervised HRD classifiers were evaluated in association with demographics, tumor characteristics, and clinical outcomes.Results: Unsupervised clustering on DNA repair genes identified four clusters of breast tumors, with one group having high expression of HR genes. Approximately 39.7% of CBCS and 29.3% of TCGA breast tumors had this unsupervised high-HRD (U-HRD) profile. A supervised HRD classifier (S-HRD) trained on TCGA had 84% sensitivity and 73% specificity to detect HRD-high samples. Both U-HRD and S-HRD tumors in CBCS had higher frequency of TP53 mutant-like status (45% and 41% enrichment) and basal-like subtype (63% and 58% enrichment). S-HRD high was more common among black patients. Among chemotherapy-treated participants, recurrence was associated with S-HRD high (HR: 2.38, 95% confidence interval = 1.50–3.78).Conclusions:HRD is associated with poor prognosis and enriched in the tumors of black women.Impact:RNA-level indicators of HRD are predictive of breast cancer outcomes in diverse populations.

Supplementary Figure from RNA-Based Classification of Homologous Recombination Deficiency in Racially Diverse Patients with Breast Cancer

Somatic mutational signatures elucidate molecular vulnerabilities to therapy and therefore detecting signatures and classifying tumors with respect to signatures has clinical value. However, identifying the etiology of the mutational signatures remains a statistical challenge, with both small sample sizes and high variability in classification algorithms posing barriers. As a result, few signatures have been strongly linked to particular risk factors. Here we presentDiffsig, a model and R package for estimating the association of risk factors with mutational signatures, suggesting etiologies for the pre-defined mutational signatures.Diffsigis a Bayesian Dirichlet-multinomial hierarchical model that allows testing of any type of risk factor while taking into account the uncertainty associated with samples with a low number of observations. In simulation, we found that our method can accurately estimate risk factor-mutational signal associations. We appliedDiffsigto breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development.Diffsigis implemented as an R package available at:https://github.com/jennprk/diffsig.

DNA repair pathways have been associated with variability in hepatocellular carcinoma (HCC) clinical outcomes, but the mechanism through which DNA repair varies as a function of liver regeneration and other HCC characteristics is poorly understood. We curated a panel of 199 genes representing 15 DNA repair pathways to identify DNA repair expression classes and evaluate their associations with liver features and clinicopathologic variables in The Cancer Genome Atlas (TCGA) HCC study. We identified two groups in HCC, defined by low or high expression across all DNA repair pathways. The low-repair group had lower grade and retained the expression of classical liver markers, whereas the high-repair group had more clinically aggressive features, increased p53 mutant-like gene expression, and high liver regenerative gene expression. These pronounced features overshadowed the variation in the low-repair subset, but when considered separately, the low-repair samples included three subgroups: L1, L2, and L3. L3 had high DNA repair expression with worse progression-free (HR 1.24, 95% CI 0.81–1.91) and overall (HR 1.63, 95% CI 0.98–2.71) survival. High-repair outcomes were also significantly worse compared with the L1 and L2 groups. HCCs vary in DNA repair expression, and a subset of tumors with high regeneration profoundly disrupts liver biology and poor prognosis.

The AURORA US Metastasis Project was established with the goal to identify molecular features associated with metastasis. We assayed 55 females with metastatic breast cancer (51 primary cancers and 102 metastases) by RNA sequencing, tumor/germline DNA exome and low-pass whole-genome sequencing and global DNA methylation microarrays. Expression subtype changes were observed in ~30% of samples and were coincident with DNA clonality shifts, especially involving HER2. Downregulation of estrogen receptor (ER)-mediated cell-cell adhesion genes through DNA methylation mechanisms was observed in metastases. Microenvironment differences varied according to tumor subtype; the ER

Purpose: Improved risk stratification and predictive biomarkers of treatment response are needed for non–muscle-invasive bladder cancer (NMIBC). Here we assessed the clinical utility of targeted RNA and DNA molecular profiling in NMIBC. Experimental Design: Gene expression in NMIBC samples was profiled by NanoString nCounter, an RNA quantification platform, from two independent cohorts (n = 28, n = 50); targeted panel sequencing was performed in a subgroup (n = 50). Gene signatures were externally validated using two RNA sequencing datasets of NMIBC tumors (n = 438, n = 73). Established molecular subtype classifiers and novel gene expression signatures were assessed for associations with clinicopathologic characteristics, somatic tumor mutations, and treatment outcomes. Results: Molecular subtypes distinguished between low-grade Ta tumors with FGFR3 mutations and overexpression (UROMOL-class 1) and tumors with more aggressive clinicopathologic characteristics (UROMOL-classes 2 and 3), which were significantly enriched with TERT promoter mutations. However, UROMOL subclasses were not associated with recurrence after bacillus Calmette-Guérin (BCG) immunotherapy in two independent cohorts. In contrast, a novel expression signature of an inflamed tumor microenvironment (TME) was associated with improved recurrence-free survival after BCG. Expression of immune checkpoint genes (PD-L1/PD-1/CTLA-4) was associated with an inflamed TME, but not with higher recurrence rates after BCG. FGFR3 mutations and overexpression were both associated with low immune signatures. Conclusions: Assessment of the immune TME, rather than molecular subtypes, is a promising predictive biomarker of BCG response. Modulating the TME in an immunologically “cold” tumor warrants further investigation. Integrated transcriptomic and exome sequencing should improve treatment selection in NMIBC.

Background: Aberrant expression of DNA repair pathways such as homologous recombination (HR) can lead to DNA repair imbalance, genomic instability, and altered chemotherapy response. DNA repair imbalance may predict prognosis, but variation in DNA repair in diverse cohorts of breast cancer patients is understudied. Methods: To identify RNA-based patterns of DNA repair expression, we performed unsupervised clustering on 51 DNA repair-related genes in the Cancer Genome Atlas Breast Cancer [TCGA BRCA (n = 1,094)] and Carolina Breast Cancer Study [CBCS (n = 1,461)]. Using published DNA-based HR deficiency (HRD) scores (high-HRD ≥ 42) from TCGA, we trained an RNA-based supervised classifier. Unsupervised and supervised HRD classifiers were evaluated in association with demographics, tumor characteristics, and clinical outcomes. Results : Unsupervised clustering on DNA repair genes identified four clusters of breast tumors, with one group having high expression of HR genes. Approximately 39.7% of CBCS and 29.3% of TCGA breast tumors had this unsupervised high-HRD (U-HRD) profile. A supervised HRD classifier (S-HRD) trained on TCGA had 84% sensitivity and 73% specificity to detect HRD-high samples. Both U-HRD and S-HRD tumors in CBCS had higher frequency of TP53 mutant-like status (45% and 41% enrichment) and basal-like subtype (63% and 58% enrichment). S-HRD high was more common among black patients. Among chemotherapy-treated participants, recurrence was associated with S-HRD high (HR: 2.38, 95% confidence interval = 1.50–3.78). Conclusions: HRD is associated with poor prognosis and enriched in the tumors of black women. Impact: RNA-level indicators of HRD are predictive of breast cancer outcomes in diverse populations.

Primary liver cancer, consisting of both cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC), is the second leading cause of cancer deaths worldwide. Our goal is to genomically characterize rare HCC subclasses to provide insight into disease biology. Leveraging The Cancer Genome Atlas (TCGA) to perform a combined analysis of CCA (n = 36) and HCC (n = 275), we integrated multiple genomic platforms, to assess transcriptional profiles, mutational signatures, and copy number patterns to uncover underlying etiology and linage specific patterns. We identified two molecular classes distinct from prototypical HCC tumors. The first, CCA-Like, although histologically indistinguishable from HCC, had enrichment of CCA mutations (IDH1, BAP1), mutational signatures, and transcriptional patterns (SOX9, KRT19). CCA-Like, however, retained a copy number landscape similar to HCC, suggesting a hepatocellular linage. The second, Blast-Like, is enriched in TP53 mutations, HBV infection, exposure related mutational signatures and transcriptionally similar to hepatoblasts. Although these subclasses are molecularly distinct, they both have a worse progression-free survival compared to classical HCC tumors, yet are clinically treated the same. The identification of and characterization of CCA-Like and Blast-Like subclasses advance our knowledge of HCC as well as represents an urgent need for the identification of class specific biomarkers and targeted therapy., Jeffrey Damrauer, Markia Smith et al. used existing datasets from cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC) to characterize two subsets of HCC distinct from prototypical HCC tumors, based on comprehensive analysis of molecular data. The two classes differed from HCC by their copy number, gene expression and mutational signature and exhibited worse progression free survival, highlighting the need to identify class-specific biomarkers and develop targeted therapies for these forms of cancer.

INTRODUCTION AND OBJECTIVE:Improved risk stratification and predictive biomarkers of treatment response are needed for non-muscle-invasive bladder cancer (NMIBC). Here we assessed the clinical util...

Background: Black breast cancer patients have p53 loss in 60% of their tumors, compared to 35% p53 loss in white breast cancer patients. The tumor suppressor p53 has pleiotropic effects on DNA repair, as it regulates both error prone and error-free DNA repair pathways. These effects on DNA repair represent molecular vulnerabilities that influence chemotherapy response, both directly and indirectly through the activation of immune responses. While studies have begun to elucidate DNA repair imbalance and immune response in human cancer, little is known about how these pathways differ by race. Methods: To study DNA repair and immune response in breast cancer, we performed gene expression analysis on FFPE samples from the Carolina Breast Cancer Study (CBCS), a large population-based study that oversampled black and younger women. We curated a list of DNA repair genes representing regulators of error prone and error free DNA repair. Pathways included Nucleotide Excision Repair (NER), Fanconi Anemia (FA), Mismatch repair (MMR), Base Excision Repair (BER), Homologous Recombination (HR), Translesion Synthesis (TLS), Alternative End Joining (AEJ), Checkpoint, and APOBEC. In addition, we developed a 50-gene immune panel representing 12 individual immune cell types (B cells, T cells, Treg cells, T help cells, T follicular helper cells, CD8 T cells, NK cells, Eosinophils, Neutrophils, M1 & M2 Macrophages) and both adaptive and innate arms of the immune system. A total of 1464 patients (53% black, 53% under 50) were included in the current analysis. We used consensus clustering to identify groups of patients based on DNA repair gene expression and used linear regression to estimate the relative frequency differences between these classes and demographic and clinical characteristics. Results: We found that breast cancers grouped into four clusters based on DNA repair gene expression. One cluster, ‘Repair High’, represented 32% of the tumors, and had high expression of NER, NHEJ, HR, and FA genes, suggesting a broad DNA repair response. Another group, ‘HR/FA High’ represented 23% of the tumors and was enriched for high expression of HR and FA genes. An “APOBEC High” group consisted of 32% of the tumors and was enriched for high expression of APOBEC family genes (APOBEC3D, APOBEC1, APOBEC3A, APOBEC3H, APOBEC3B). Finally, 13% of tumors, had a ‘Heterogeneous Repair’ pattern of high expression of HR, NHEJ, and FA genes, but lower expression of NER genes. The HR/FA and Heterogeneous Repair groups were enriched for TP53 mutant-like tumors (93% vs. 5% and 61% vs. 38% Mutant vs. Wildtype respectively). In addition, the Heterogeneous Repair group was enriched for Hormone Receptor positive samples ([RFD] 8.2% (0.613, 15.3), 77% vs. 23% in positive vs. negative respectively), while the HR/FA High group was significantly enriched for TNBC ([RFD] HR/FA: 51.2% (45.1, 57.1), 75% vs. 25% TNBC vs. non-TNBC respectively). The Repair High group was the only group enriched for non-black race ([RFD]: 10.4% (4.0, 16.7), 42% vs. 58% in blacks vs. non-blacks respectively). Finally, DNA repair classes were associated with immune scores, with the APOBEC High tumors having a significantly higher Eosinophil score (p = 0.021) and Neutrophil score (p = 0.007) compared to the other four groups. Conclusion: DNA repair expression is highly variable across breast tumors and may depend upon TP53 status, tumor subtype, and race. Differential immune marker expression by DNA repair group suggests some DNA repair groups may have differential response to immune-targeted therapies. DNA repair, immune response, and race are inter-related in breast cancer and unraveling and ultimately targeting breast cancer disparities may require coordinated evaluation of these pathways. Citation Format: Andrea Walens, Alina M Hamilton, Markia A Smith, Xiaohua Gao, Erin L Kirk, Stephen D Hursting, Katherine A Hoadley, Cyrus Vaziri, Melissa A Troester. Dna repair imbalance and immune response in breast cancer mortality disparities [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS19-03.